A hydropower project reservoir area geological disaster information management and risk assessment system

Abstract

The application provides a water and electricity engineering reservoir area geological disaster information management and risk assessment system, and belongs to the field of geological disaster prevention technology. The system hardware part comprises: data acquisition equipment collecting monitoring data obtained by monitoring equipment; a system terminal receiving monitoring data collected by the data acquisition equipment through a wireless network; a solar cell panel for power supply; the software part comprises: a comprehensive interface module for data visualization display; a geological disaster early identification module for identifying and extracting potential geological disaster hidden dangers; a geological disaster information management module for storing geological disaster information and providing a query function; a geological disaster monitoring and early warning module for managing monitoring equipment; a geological disaster risk assessment module for risk assessment; and a geological disaster emergency disposal module for generating and pushing early warning information and disposal plans. Advantageous effects: the newly added potential geological disaster hidden dangers can be early identified, which helps to improve the field geological disaster investigation efficiency and reduce the manpower and time cost investment.

Description

Technical Field

[0001] This invention relates to the field of geological disaster prevention and control technology, specifically to a geological disaster information management and risk assessment system for hydropower reservoir areas. Background Technology

[0002] Geological hazards in reservoir areas are a significant factor affecting the safe construction and stable operation of hydropower projects. Casualties and safety accidents caused by reservoir area geological hazards are commonplace. With the increasing frequency of extreme weather events and the continuous operation of high dams and large reservoirs, the prevention and control of geological hazard risks in hydropower project reservoir areas faces even more severe challenges. Traditional geological hazard information management systems can only store and query routine information such as geological hazards, monitoring equipment, and monitoring data. They are insufficient for managing and utilizing geological hazard images and models, and have not yet integrated optical and InSAR image data to achieve wide-area identification and dynamic updating of potential geological hazard hazards in reservoir areas. Furthermore, they have not yet comprehensively considered historical monitoring data, rainfall conditions, and reservoir operation to achieve scientific projection of geological hazard risks in reservoir areas, thus failing to meet the requirements of refined and intelligent operation management of hydropower projects. Therefore, it is necessary to strengthen the management of geological hazard images and models, while also utilizing artificial intelligence and numerical simulation to achieve scientific assessment of geological hazard risks in reservoir areas. This will provide a scientific basis for hydropower project operation and management units to formulate scientific and reasonable emergency response plans under special operating conditions, ensuring the safe and stable operation of hydropower projects. Summary of the Invention

[0003] The main objective of this invention is to provide a system for managing and assessing geological disaster information in hydropower reservoir areas, thereby addressing the problems mentioned in the background section.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a geological disaster information management and risk assessment system for hydropower project reservoir areas, which is divided into hardware and software parts. The hardware part includes: monitoring equipment for monitoring information of the area where the hydropower project reservoir is located; Data acquisition equipment, which communicates with monitoring equipment, is used to collect monitoring data acquired by the monitoring equipment; The system terminal is connected to the data acquisition equipment and is used to receive monitoring data collected by the data acquisition equipment via a wireless network. Solar panels are electrically connected to monitoring and data acquisition equipment to power the monitoring and data acquisition equipment. The software component is mounted on the system terminal, which provides hardware support. The software component includes: a comprehensive interface module, used for statistical analysis and visualization of data. The early identification module for geological hazards is used to periodically identify and extract potential geological hazard risks within the reservoir area of ​​hydropower projects. The geological disaster information management module is used to store geological disaster information and provide query functions; The geological disaster monitoring and early warning module is used to manage the status of monitoring equipment and to issue early warnings for abnormal monitoring data. The geological hazard risk assessment module is used to assess the risks of landslides and debris flows; The geological disaster emergency response module is used to generate and push geological disaster risk warning information, emergency material information, and emergency response plans.

[0005] Furthermore, the monitoring equipment includes: Rain gauges are used to monitor rainfall in the reservoir area of ​​hydropower projects. Inclinometers are used to monitor deep horizontal displacement in the reservoir area of ​​hydropower projects. Crack gauges are used to monitor the opening and closing degree of cracks in the reservoir area of ​​hydropower projects. Mud level gauges are used to monitor the mud and water level in the reservoir area of ​​hydropower projects. Water level gauges are used to monitor changes in groundwater levels in the reservoir area of ​​hydropower projects. GNSS stations are used to monitor surface displacement in the reservoir area of ​​hydropower projects. Drones are used to acquire images or point cloud data of reservoir areas in hydropower projects. Optical satellites are used to acquire optical image data of hydropower reservoir areas; InSAR satellites are used to acquire InSAR image data of hydropower reservoir areas.

[0006] Furthermore, the early identification module for geological hazards includes: a wide-area early identification submodule for geological hazards and a geological hazard deformation feature extraction submodule; The wide-area early identification submodule for geological hazards is used to periodically identify potential geological hazards in the reservoir area of ​​hydropower projects based on images acquired by optical satellites and InSAR satellites. On this basis, the identified potential geological hazards are compared with existing geological hazards according to key location parameters. The geological disaster deformation feature extraction submodule is used to periodically extract the deformation features of geological disasters based on geological disaster data acquired by UAVs.

[0007] Furthermore, the geological disaster information management module includes: a potential geological disaster hazard management sub-module and a geological disaster information management sub-module; The potential geological hazard management submodule is used to store the basic information of newly added potential geological hazard hazards and provide query functions, and to synchronize the newly added potential geological hazard hazards after review and confirmation to the geological hazard information management submodule; Stability can be categorized as: very stable, basically stable, and unstable; Sizes can be categorized as: small, medium, and large; The geological disaster information management submodule is used to store, query, and display basic information, models, and image information of existing geological disasters.

[0008] Furthermore, basic information on potential geological hazards includes: the reservoir area, distance from the dam, hazard type, geographical coordinates, bank location, scale, stability, and hazard level; The hazard level is determined by the hazard classification score, which is obtained by weighted summation of stability and scale. The expression for this score is: (1); in, To score the level of hazard, , These are the quantitative values ​​for scale and potential hazards, respectively. , The weights for scale and potential risks are respectively. Set a low-level hazard threshold ,when At that time, the hazard level was classified as minor. Set intermediate-level hazard threshold ,when At that time, the hazard level was classified as medium hazard. when At that time, the hazard level was classified as a serious hazard.

[0009] Furthermore, the geological disaster monitoring and early warning module includes: a monitoring equipment management submodule, a monitoring data management submodule, and an anomaly early warning submodule; The monitoring equipment management submodule is used to store and query the equipment information of the monitoring equipment, and to issue alarms for abnormal status of the monitoring equipment; the information includes: storage area, installation location, installation time, associated geological disaster points, working status, and communication method; The monitoring data management submodule is used to store, query, output, and visualize the time-series data of monitored physical quantities, including: rainfall, displacement, groundwater level, mud water level, and crack opening degree. The anomaly warning submodule is used to manage the anomaly warning model of the monitored physical quantity, set the warning threshold and frequency, and provide graded warnings for anomaly monitoring data.

[0010] Furthermore, the process for setting the warning threshold and frequency is as follows: Select the monitored physical quantity as the early warning parameter; set the basic threshold and frequency base value for each early warning parameter; The basic threshold and frequency values ​​of each warning parameter are adjusted according to the operating conditions to obtain the real-time warning threshold and real-time warning frequency. Operating conditions include rainfall intensity, rainfall duration, and reservoir water level. For each operating condition, a low operating condition threshold and a high operating condition threshold are set. The operating condition status is determined based on the high and low operating condition thresholds as follows: It is considered a high operating condition when it exceeds the high operating condition threshold. It is considered a low operating condition when it is less than the low operating condition threshold. All other conditions are normal operating conditions; For each operating condition factor, its adjustment weight is determined under each operating condition. The expression for the real-time warning threshold is then: (2); in, The real-time warning threshold for the warning parameter. The basic threshold for early warning parameters, , , These are the adjustment weights corresponding to rainfall intensity, rainfall duration, and reservoir water level, respectively. The weighting of the hazard level; The warning frequency is related to the operating conditions. Specifically, when all operating factors are at a low operating condition, the warning frequency is reduced. When the operating conditions are normal and there are no high operating conditions, the basic value of the warning frequency is directly used as the real-time warning frequency. When there are high operating conditions, increase the warning frequency; when all operating conditions are high, increase the warning frequency to the maximum.

[0011] Furthermore, the geological hazard risk assessment module includes: a landslide risk assessment submodule and a debris flow risk assessment submodule; The landslide risk assessment submodule includes: landslide susceptibility assessment unit, landslide hazard assessment unit, landslide vulnerability assessment unit for affected bodies, and landslide risk assessment unit; The landslide susceptibility assessment unit is used to assess landslide susceptibility under specific conditions by combining regional landslide geometry, slope structure, rainfall conditions, and reservoir water level, and using artificial intelligence algorithms. Landslide geometry includes: slope height and slope gradient; slope structure types include: dip slope and reverse slope; rainfall conditions include: rainfall intensity and rainfall duration; changes in rainfall conditions and reservoir water levels constitute different working conditions; The landslide hazard assessment unit is used to invert geotechnical mechanical parameters based on boundary conditions and historical monitoring data; on this basis, it performs numerical simulation of the entire process of landslide movement, ingress, and surge under specific working conditions and determines its potential impact range; based on the numerical simulation results, considering landslide failure characteristics, it assesses the landslide hazard under specific working conditions; and it adjusts the landslide hazard assessment value according to the importance level of the hydropower project. Landslide boundary conditions include: landslide geometry, rainfall conditions, and reservoir operation conditions; reservoir operation conditions include: reservoir water level and underwater topography; geotechnical parameters include: cohesion, internal friction angle, unit weight, elastic modulus, and Poisson's ratio; landslide failure characteristics include: sliding volume, sliding distance, and sliding velocity. The landslide vulnerability assessment unit for disaster-bearing bodies is used to assess the landslide vulnerability of disaster-bearing bodies based on three vulnerability characteristics: social attributes, economic value, and operation of hydropower projects. The landslide risk assessment unit is used to calculate the landslide risk value under a specific working condition by using a weighted summation method based on the predicted probability of landslide susceptibility, the landslide hazard assessment value, and the landslide vulnerability score of the affected body. The debris flow risk assessment submodule includes: debris flow susceptibility assessment unit, debris flow hazard assessment unit, debris flow vulnerability assessment unit for disaster-bearing bodies, and debris flow risk assessment unit; The debris flow susceptibility assessment unit is used to assess the susceptibility to debris flows under specific working conditions by combining information on the topographic conditions, rainfall conditions, and material source conditions of the watershed unit and using artificial intelligence algorithms. Topographic conditions of a watershed unit include: area, elevation difference, length of the main ditch, and slope of the main ditch; sediment source conditions include: vegetation cover, sediment source area, and distribution of loose deposits. The debris flow hazard assessment unit is used to invert key physical parameters based on historical debris flow monitoring data and boundary conditions; on this basis, it performs numerical simulation of the entire process of debris flow movement, inflow, and surge under specific working conditions and determines its potential impact range; based on the numerical simulation results and considering key dynamic parameters, it assesses the hazard range of the potential impact of debris flow under specific working conditions; and it adjusts the debris flow hazard assessment value according to the importance level of the hydropower project. The boundary conditions for debris flows include: topographic conditions of the watershed unit, source conditions, rainfall conditions, and reservoir operation conditions; key physical parameters include: unit weight, base friction coefficient, and turbulence coefficient; key dynamic parameters include: debris flow velocity, flow depth, deposition depth, deposition range, and impact momentum. The debris flow vulnerability assessment unit for disaster-bearing bodies is used to assess the debris flow vulnerability of disaster-bearing bodies based on three vulnerability characteristics: social attributes, economic value, and hydropower project operation. The debris flow risk assessment unit is used to comprehensively assess the susceptibility, hazard, and vulnerability of the affected body to debris flows, and to calculate the debris flow risk value under specific working conditions through a weighted summation method.

[0012] Furthermore, the adjustment expressions for the landslide hazard assessment value and the debris flow hazard assessment value are as follows: (3); in, This is the adjusted landslide or debris flow hazard assessment value. Values ​​to be processed for landslide or debris flow hazard assessment. This is an adjustment factor for landslides or debris flows. The importance level of the hydropower reservoir area.

[0013] Furthermore, the geological disaster emergency response module includes: an emergency supplies management submodule, an emergency rescue management submodule, an emergency plan management submodule, and an emergency response submodule; The emergency supplies management submodule is used to add, query, and update emergency supplies information; The emergency rescue management submodule is used to add, query, and update contact information for the management departments involved in the reservoir area; The emergency response plan management submodule is used to generate geological disaster emergency response plans based on geological disaster risk level, type of bearing structure, regional traffic conditions, medical and fire-fighting force configuration, and the operational status of hydropower projects. The emergency response submodule is used to push geological disaster risk warning information, emergency material information, and emergency response plans to the emergency rescue contacts of the relevant management departments, professional institutions, and hydropower project operation and management units in the reservoir area.

[0014] The beneficial effects are as follows: (1) This system can realize the early identification of newly added potential geological hazards in the reservoir area of ​​hydropower projects, provide goals and guidance for hydropower project operation and management units to carry out field geological hazard investigations, help improve the work efficiency of field geological hazard investigations and reduce manpower and time costs; at the same time, it can include newly added geological hazard hazards in the management scope and realize dynamic management of geological hazards in the reservoir area. (2) Since the urgency level of the same data varies under different working conditions, this system sets a dynamic warning threshold and warning frequency. The warning threshold and frequency can be determined according to the actual situation to ensure that no warning is missed in an emergency and that no resources are wasted in a non-emergency situation. (3) The warning threshold takes into account not only the working conditions but also the level of hidden dangers, thus improving the comprehensiveness of the warning. (4) The risk assessment values ​​of landslides and debris flows were adjusted according to the importance level of the hydropower project, taking into account the importance of the hydropower project itself, and ensuring that important hydropower projects are given priority protection. Attached Figure Description

[0015] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a system architecture diagram of the present invention; Figure 2 This is the landslide risk assessment submodule of the present invention; Figure 3 This is a schematic diagram of the debris flow risk assessment submodule of the present invention; In the diagram: 1-Monitoring equipment, 11-Rain gauge, 12-Inclinometer, 13-Crack gauge, 14-Mud level gauge, 15-Water level gauge, 16-GNSS station, 17-UAV, 18-Optical satellite, 19-InSAR satellite, 2-Data acquisition equipment, 3-Solar panel, 4-System terminal, 5-Integrated interface module, 6-Early identification module for geological hazards, 61-Wide-area early identification sub-module for geological hazards, 62-Deformation feature extraction sub-module for geological hazards, 7-Geological hazard information management module, 71-Potential geological hazard management sub-module, 72-Geological hazard information management sub-module, 8-Geological hazard monitoring and early warning module, 81-Monitoring equipment management sub-module, 82-Monitoring data management Sub-modules: 83-Abnormal Early Warning Sub-module, 9-Geological Hazard Risk Assessment Sub-module, 91-Landslide Risk Assessment Sub-module, 911-Landslide Susceptibility Assessment Unit, 912-Landslide Hazard Assessment Unit, 913-Landslide Vulnerability Assessment Unit for Disaster-Bearing Bodies, 914-Landslide Risk Assessment Unit, 92-Debris Flow Risk Assessment Sub-module, 921-Debris Flow Susceptibility Assessment Unit, 922-Debris Flow Hazard Assessment Unit, 923-Debris Flow Vulnerability Assessment Unit for Disaster-Bearing Bodies, 924-Debris Flow Risk Assessment Unit, 10-Geological Hazard Emergency Response Module, 101-Emergency Material Management Sub-module, 102-Emergency Rescue Management Sub-module, 103-Emergency Plan Management Sub-module, 104-Emergency Response Sub-module. Detailed Implementation

[0016] Example 1 like Figures 1-3 As shown, a geological disaster information management and risk assessment system for hydropower reservoir areas can be divided into hardware and software components. The hardware component includes: monitoring equipment 1, data acquisition equipment 2, solar panels 3, and system terminal 4. The software component includes: integrated interface module 5, early identification module for geological disasters 6, geological disaster information management module 7, geological disaster monitoring and early warning module 8, geological disaster risk assessment module 9, and geological disaster emergency response module 10.

[0017] The monitoring equipment 1 includes a rain gauge 11, an inclinometer 12, a crack gauge 13, a mud level gauge 14, a water level gauge 15, a GNSS station 16, a drone 17, an optical satellite 18, and an InSAR satellite 19, all installed at geological disaster sites. Rain gauge 11 is used to monitor rainfall in the area where the reservoir of a hydropower project is located; Inclinometer 12 is used to monitor deep horizontal displacement in the reservoir area of ​​hydropower projects; The crack gauge 13 is used to monitor the opening and closing degree of crack development in the reservoir area of ​​hydropower projects; The mud level gauge 14 is used to monitor the mud and water level in the reservoir area of ​​a hydropower project. Water level gauge 15 is used to monitor changes in groundwater level in the reservoir area of ​​hydropower projects; GNSS station 16 is used to monitor surface displacement in the area where the hydropower project reservoir is located; The UAV 17 is used to periodically acquire images or point cloud data of the reservoir area of ​​hydropower projects; Optical Satellite 18 is used to periodically acquire optical image data of hydropower project reservoir areas; InSAR Satellite 19 is used to periodically acquire InSAR image data of reservoir areas for hydropower projects.

[0018] Data acquisition device 2 and monitoring device 1 can communicate with each other through various means such as wired or wireless communication, and are used to collect monitoring data acquired by monitoring device 1.

[0019] System terminal 4 can be a smartphone, tablet, personal computer, etc., connected to data acquisition device 2, and used to receive monitoring data collected by data acquisition device 2 via wireless network.

[0020] Solar panel 3 is installed near the reservoir area of ​​the hydropower project and is electrically connected to monitoring equipment 1 and data acquisition equipment 2. It is used to power rain gauge 11, inclinometer 12, crack gauge 13, mud level gauge 14, water level gauge 15, GNSS station 16, UAV 17 and data acquisition equipment 2.

[0021] In a preferred embodiment, the data acquisition device 2 and the monitoring device 1 are connected via an RS485 serial port, the communication protocol is Modbus-RTU, the data transmission format is hexadecimal, and the acquisition frequency is 15 minutes / time. GNSS station 16 connects to the data acquisition equipment via a 4G wireless module. The communication protocol is NMEA-0183, the data transmission format is ASCII, and the acquisition frequency is 1 minute / time. Data acquisition device 2 is connected to system terminal 4 via 5G wireless communication. The communication protocol is TCP / IP, and data transmission uses encrypted data packet format to ensure data transmission security. The solar panel 3 is electrically connected to the monitoring device 1 and the data acquisition device 2, with an output voltage of 12V and an output current of 5A. It is equipped with a 100Ah lithium battery as a backup power source to ensure that the equipment can operate continuously for more than 72 hours without other external power supply. There can be multiple solar panels 3, or they can be distributed in different areas, depending on the distribution of the monitoring device 1 and the data acquisition device 2.

[0022] Image / point cloud data collected by UAV17, optical satellite18, and InSAR satellite19 are imported via wired or wireless transmission to system terminal4.

[0023] The software adopts a modular design, including: a comprehensive interface module 5, a geological disaster early identification module 6, a geological disaster information management module 7, a geological disaster monitoring and early warning module 8, a geological disaster risk assessment module 9, and a geological disaster emergency response module 10. Each module has independent functions and works in synergy. The integrated interface module 5 is used to perform statistical analysis and visualization of geological disasters, the number and type of monitoring equipment, as well as early identification results, monitoring and early warning results, and risk assessment results.

[0024] The geological hazard early identification module 6 includes: a geological hazard wide-area early identification submodule 61 and a geological hazard deformation feature extraction submodule 62; The wide-area early identification submodule 61 for geological hazards is used to periodically identify potential geological hazards in the reservoir area of ​​hydropower projects based on optical images and InSAR images acquired by optical satellite 18 and InSAR satellite 19. On this basis, according to key location parameters such as the reservoir area, geographical coordinates, and distance from the dam, the identified potential geological hazards are compared with the existing geological hazards stored in the geological hazard information management submodule 72, and newly added potential geological hazards are synchronized to the potential geological hazard management submodule 71. In the preferred embodiment, a specific execution step of the wide-area early identification submodule 61 for geological hazards is given as follows: A1. Perform radiometric correction, geometric correction, and denoising on the reservoir area images acquired by Optical Satellite 18 and InSAR Satellite 19 to obtain standardized images and eliminate image distortion and noise interference. A2. Use the small baseline set algorithm to extract surface deformation of the reservoir area from InSAR images. Set the specific deformation threshold for the hydropower reservoir area as follows: 10 mm for annual deformation and 3 mm for monthly deformation. Mark areas with deformation exceeding the threshold as suspected potential hazard areas. A3. Extract texture and topographic features from optical images of suspected potential hazard areas, extracting core features such as slope height, slope gradient, and slope structure. If the features match the typical topographic features of geological disasters in hydropower reservoir areas, the area is identified as a potential hazard area. Typical terrain features include a slope of ≥30° and a downslope. A4. The geographic coordinates, distance from the dam, bank type, disaster type, and other attributes of the potential hazard area are matched with the existing hazards in the geological hazard information management submodule 72 in both spatial and attribute aspects. If the match fails, it is determined to be a new potential geological hazard and is automatically synchronized to the potential geological hazard management submodule 71 through the geographic coordinate interface. The matching criteria are: spatial distance ≤ 50m and disaster type and shore type are consistent.

[0025] The geological disaster deformation feature extraction submodule 62 is used to periodically extract the deformation features of geological disasters based on the geological disaster images or point cloud data acquired by the UAV 17, and synchronize the geological disaster deformation data or labeled image data to the geological disaster information management submodule 72. Deformation characteristics include: three-dimensional deformation amount, deformation rate, deformation area, and the proportion of the deformation area to the total area of ​​the disaster body; Three-dimensional deformation refers to the deformation expressed in a spatial coordinate system. Common spatial coordinate systems use the horizontal east direction as the positive x-axis, the horizontal north direction as the positive y-axis, and the vertical upward direction as the positive z-axis. Deformation rate is the ratio of the amount of deformation between two samples to the sampling interval.

[0026] The geological disaster information management module 7 includes: potential geological disaster hazard management sub-module 71 and geological disaster information management sub-module 72; The potential geological hazard management submodule 71 is used to store and query basic information such as the reservoir area, distance from the dam, hazard type, geographical coordinates, bank location, scale, stability and hazard level of newly added potential geological hazard, and synchronize the newly added potential geological hazard after review and confirmation to the geological hazard information management submodule 72. Stability can be categorized into: very stable, basically stable, and unstable, with quantization values ​​of 1, 2, and 3, respectively. The size can be divided into: small, medium and large, with quantitative values ​​of 1, 2 and 3 respectively; The hazard level is determined by the hazard classification score, which is obtained by weighted summation of stability and scale. The expression for this score is: (1); in, To score the level of hazard, , These are the quantitative values ​​for scale and potential hazards, respectively. , The weights for scale and potential risks are respectively. Set a low-level hazard threshold ,when At that time, the hazard level was classified as minor. Set intermediate-level hazard threshold ,when At that time, the hazard level was classified as medium hazard. when At that time, the hazard level was classified as a serious hazard; The geological disaster information management submodule 72 is used to store, query and display basic information such as the reservoir area to which the existing geological disaster belongs, distance from the dam, disaster type, geographical coordinates, bank location, scale, stability and hazard level, as well as geological models, simulation models, video images and other models and image information.

[0027] The geological disaster monitoring and early warning module 8 includes: a monitoring equipment management submodule 81, a monitoring data management submodule 82, and an anomaly early warning submodule 83; The monitoring equipment management submodule 81 is used to store and query equipment information such as the storage area, installation location, installation time, associated geological disaster points, working status, and communication method of the monitoring equipment 1, and to alarm for abnormal status of the monitoring equipment. The monitoring data management submodule 82 is used to store, query, output, and visualize time-series data of monitored physical quantities such as rainfall, displacement, groundwater level, mud water level, and crack opening degree. The anomaly warning submodule 83 is used to manage the anomaly warning model based on monitored physical quantities such as rainfall, displacement, groundwater level, mud water level, and crack opening degree, set warning thresholds and frequencies, and perform graded warnings on anomaly monitoring data. The process for setting the warning threshold and frequency is as follows: The selected early warning parameters are: rainfall, displacement, groundwater level, mud water level, and crack opening degree. Set the basic threshold and frequency value for each warning parameter; The basic threshold and frequency values ​​of each warning parameter are adjusted according to the operating conditions to obtain the real-time warning threshold and real-time warning frequency. Operating conditions include rainfall intensity, rainfall duration, and reservoir water level. For each operating condition, a low operating condition threshold and a high operating condition threshold are set, and the operating condition status is determined based on the high and low operating condition thresholds. It is considered a high operating condition when it exceeds the high operating condition threshold. It is considered a low operating condition when it is less than the low operating condition threshold. All other conditions are normal operating conditions; For example, regarding rainfall intensity, set low-condition rainfall intensity thresholds and high-condition rainfall intensity thresholds, and classify them into low-condition, normal-condition, or high-condition based on the set thresholds. For each operating condition factor, when it is under high operating conditions, its adjustment weight is set to 0.9; when it is under normal operating conditions, its adjustment weight is set to 1; and when it is under low operating conditions, its adjustment weight is set to 1.1. The expression for the real-time warning threshold is: (2); in, The real-time warning threshold for the warning parameter. The basic threshold for early warning parameters, , , These are the adjustment weights corresponding to rainfall intensity, rainfall duration, and reservoir water level, respectively. The weight of the hazard level is as follows: when it is a minor hazard, the weight of the hazard level is 1.1; when it is a moderate hazard, the weight of the hazard level is 1; when it is a serious hazard, the weight of the hazard level is 0.9. The warning frequency is related to the operating conditions. Specifically, when all operating conditions are low, the warning frequency is reduced. In a preferred embodiment, the real-time warning frequency can be set to half of the base value of the warning frequency. When the operating conditions are normal and there are no high operating conditions, the warning frequency remains unchanged, that is, the basic value of the warning frequency is directly used as the real-time warning frequency. When there are high operating conditions, the warning frequency should be increased. In a preferred solution, the real-time warning frequency can be directly set to twice the base value of the warning frequency. When all operating conditions are at a high level, the warning frequency will be increased to the maximum.

[0028] Geological hazard risk assessment module 9 includes: landslide risk assessment submodule 91 and debris flow risk assessment submodule 92; The landslide risk assessment submodule 91 includes: landslide susceptibility assessment unit 911, landslide hazard assessment unit 912, landslide vulnerability assessment unit 913, and landslide risk assessment unit 914; The landslide susceptibility assessment unit 911 is used to assess landslide susceptibility under specific working conditions by combining regional landslide geometry, slope structure, rainfall conditions, and reservoir water level, and using artificial intelligence algorithms such as machine learning. Landslide geometry includes: slope height and slope gradient; slope structure types include: dip slope and reverse slope; rainfall conditions include: rainfall intensity and rainfall duration. Changes in rainfall conditions and reservoir water level constitute different working conditions. In a preferred embodiment, an LSTM neural network is used to build a landslide susceptibility model; the model includes: an input layer, an LSTM layer, and an output layer. The input to the input layer includes the following features: slope height, slope gradient, slope structure type, number of landslides, rainfall intensity, rainfall duration, and reservoir water level; here, the time step is set to 168, and the step size is 1 hour. For the numerical features in the input, normalization processing is required to adjust their value range to between 0 and 1. For the slope structure type, take 1 when it is a downhill slope and 0 when it is a downhill slope. The model uses a basic LSTM layer, which includes a forget gate, an input gate, and an output gate. The output of the LSTM layer is the hidden state at the last time step. The output layer outputs the landslide probability; when the landslide probability is greater than 0.7, it is a high risk level; when the landslide probability is less than 0.3, it is a low risk level; otherwise, it is a medium risk level. The loss function used for model training is binary cross-entropy, expressed as follows: (3); in, The loss value. The total number of samples, For the first The true label of each sample For the first The predicted probability of landslides for each sample; The stochastic gradient descent method was used to optimize the weights and biases in the model. Landslide hazard assessment unit 912 is used to invert geotechnical parameters such as cohesion, internal friction angle, unit weight, and elastic modulus of key structures such as the landslide body and sliding zone, based on historical monitoring data, by combining boundary conditions such as landslide geometry, rainfall conditions, and reservoir operation. On this basis, it performs numerical simulation of the entire process of landslide movement, reservoir entry, and surge under specific working conditions and determines its potential impact range. Based on the numerical simulation results, it assesses the landslide hazard under specific working conditions, considering landslide failure characteristics such as sliding volume, sliding distance, and sliding velocity. Reservoir operating conditions include: reservoir water level and underwater topography. The detailed process of landslide hazard assessment is as follows: B1. Collect historical monitoring data and perform preprocessing operations; historical monitoring data includes: landslide geometric parameters, rainfall condition parameters, and reservoir operation condition parameters. B2. Inverse the geotechnical mechanics parameters; First, use the finite element method or finite difference method, based on the geotechnical mechanics model, to calculate the mechanical response of the landslide under historical working conditions with specific parameter values, and then use the least squares method to construct the objective function. The accurate values ​​of the geotechnical mechanics parameters can be inverted through iteration. Geotechnical parameters include: cohesion, internal friction angle, unit weight, elastic modulus, and Poisson's ratio; among which, Poisson's ratio refers to the ratio of lateral deformation to longitudinal deformation of the landslide rock mass. The objective function expression for the inversion is as follows: (4); in, To monitor the number of data points, For the first The actual monitoring value of each point For the first Numerical simulation values ​​for each point This is a vector composed of the geotechnical mechanics parameters to be inverted; B3. Conduct numerical simulations of the entire process of landslide movement, entry into the reservoir, and surge under specific working conditions; The simulation output results are: dynamic evolution time series data of the entire process of landslide movement, intrusion into the reservoir, and surge; potential impact range map of the reservoir area, bank slope, and core area of ​​hydropower project after the landslide; the potential impact range map includes: the landslide accumulation range, the surge inundation range, and the dam / powerhouse / reservoir facility areas affected by the surge. B4. Extract landslide failure characteristics to obtain a set of quantitative indicators for landslide failure characteristics; landslide failure characteristics include: sliding volume, sliding distance, sliding velocity, maximum wave height, wave arrival time at the dam, and the proportion of volume sliding into the reservoir; among which, sliding velocity refers to the maximum instantaneous velocity during the movement of the landslide body; B5. Determine the importance level of hydropower projects; referring to the "Classification of Hydropower Projects and Design Safety Standard" SL252-2017, hydropower projects can be classified into levels 1 to 5 based on dam height, specifically: Level 1 importance when dam height is greater than or equal to 150m; Level 2 importance when dam height is greater than or equal to 100m but less than 150m; Level 3 importance when dam height is greater than or equal to 30m but less than 100m; Level 4 importance when dam height is greater than or equal to 15m but less than 30m; and Level 5 importance when dam height is less than 15m. B6. Conduct a landslide hazard assessment of the hydropower reservoir area; The landslide failure characteristic values ​​are normalized to obtain landslide failure characteristic index values. For positive indices, i.e., the larger the index, the better, the minimum value is 0 and the maximum value is 1. For negative indices, i.e., the smaller the index, the better, the minimum value is 1 and the maximum value is 0. The expression for the landslide hazard assessment value is as follows: (5); in, The values ​​to be processed in the landslide hazard assessment The number of landslide failure characteristics. For the first Individual landslide damage characteristic index values, For the first Weights of each landslide damage characteristic indicator; Hydropower projects vary in importance. For example, less important hydropower projects have a smaller impact area. Therefore, when facing the same danger, more important hydropower projects will be prioritized for protection. Thus, the landslide hazard assessment value is adjusted according to the importance level of the hydropower project, as shown in the following expression: (6); in, This is the adjusted landslide hazard assessment value. This is the landslide adjustment coefficient. The importance level of hydropower projects; The landslide vulnerability assessment unit 913 is used to assess the landslide vulnerability of the affected body based on three vulnerability characteristics: social attributes, economic value, and hydropower project operation. Social attributes refer to the social attributes of typical carriers such as people, buildings, roads, and farmland within the potential impact range of a landslide; hydropower operation characteristics refer to the adverse effects that landslides entering the reservoir and surge waves may have on the operation of the reservoir and hydropower projects. Social attribute characteristics include the following influencing factors: personnel exposure risk and dependence on public facilities; the social attribute characteristic value is obtained by weighted summation of its influencing factors; in a preferred scheme, a quantitative scoring standard for social attribute characteristics is given: For disaster-bearing areas, the risk factor score for human exposure is 1 when the area has no population or very few mobile populations; 3 when the area has a small number of permanent residents or low-frequency mobile populations; 5 when the area has a medium-sized permanent population or moderate-frequency mobile populations; 7 when the area has a large number of permanent residents or high-frequency mobile populations; and 9 when the area is a densely populated area or a gathering point for people. For disaster-bearing bodies, the dependence factor on public facilities is 1 when there are no public facilities; 3 when there are a few simple public facilities; 5 when there are medium-sized basic public facilities; 7 when there are important public facilities such as township hospitals; and 9 when there are core public facilities such as county hospitals. The influencing factors of economic value characteristics are economic value factors; the quantitative scoring criteria for economic value characteristics are as follows: For a disaster-bearing entity, the economic value factor is 1 when it has no assets; 3 when it includes low-value assets; 5 when it includes medium-value assets; 7 when it includes high-value assets; and 9 when it includes high-value assets. The economic value factor is the characteristic value of the economic value. The influencing factor on the operating characteristics of hydropower is the operational interruption factor; the quantitative scoring standard for the operating characteristics of hydropower is as follows: For disaster-bearing bodies, when there is no operational interruption, the operational interruption factor is taken as 1; when there is a minor interruption, the operational interruption factor is taken as 3; when there is a moderate interruption, the operational interruption factor is taken as 5; when there is a major interruption, the operational interruption factor is taken as 7; when there is a severe interruption, the operational interruption factor is taken as 9; the operational interruption factor is the characteristic value of hydropower operation. The expression for the landslide vulnerability score is as follows: (7); in, To score the vulnerability of landslides, For the first One vulnerable feature, For the first Weights of each vulnerable feature; The landslide risk assessment unit 914 is used to calculate the landslide risk value under a specific working condition by weighted summation based on the predicted probability of landslide susceptibility, the landslide hazard assessment value and the landslide vulnerability score of the affected body, thereby realizing the assessment of landslide risk. The predicted probability of landslide susceptibility, the landslide hazard assessment value, and the vulnerability score of the disaster-bearing body need to be normalized and the values ​​adjusted to 0~100. The landslide risk value is calculated using a weighted summation method, and its expression is as follows: (8); in, This represents the landslide risk value. , , These represent the normalized predicted probability, the landslide hazard assessment value, and the vulnerability score of the affected body, respectively. , , These are the weights corresponding to the predicted probability, the landslide hazard assessment value, and the vulnerability score of the affected body, respectively. The debris flow risk assessment submodule 92 includes: debris flow susceptibility assessment unit 921, debris flow hazard assessment unit 922, debris flow vulnerability assessment unit 923, and debris flow risk assessment unit 924. The debris flow susceptibility assessment unit 921 is used to assess debris flow susceptibility under specific conditions by combining information on watershed unit topography, rainfall, and sediment source conditions, and employing artificial intelligence algorithms such as machine learning. Watershed unit topography conditions include: area, elevation difference, main channel length, and main channel slope. Sediment source conditions include: vegetation cover, sediment source area, and distribution of loose deposits. Similarly, an LSTM neural network is used to build the debris flow susceptibility model. The model structure is consistent with the landslide susceptibility model, only the inputs differ. The debris flow susceptibility model inputs include: area, elevation difference, main channel length, main channel slope, sediment source conditions, debris flow occurrence frequency, rainfall, and reservoir water level; the output is the debris flow probability. The debris flow hazard assessment unit 922 is used to combine the topographic conditions, sediment source conditions, rainfall conditions, and reservoir operation boundary conditions of the watershed unit, and based on historical debris flow monitoring data, to invert key physical parameters such as unit weight, base friction coefficient, and turbulence coefficient. On this basis, it performs numerical simulations of the entire process of debris flow movement, inflow into the reservoir, and surge under specific working conditions, and determines its potential impact range. Based on the numerical simulation results, considering key dynamic parameters such as debris flow velocity, flow depth, deposition depth, deposition range, and impact momentum, it assesses the hazard of the potential impact range of debris flow under specific working conditions. The debris flow hazard assessment method is consistent with the landslide hazard method. After the hazard assessment, a debris flow hazard assessment value can be obtained; similarly, the debris flow hazard assessment value is adjusted according to the importance level of the hydropower project. The debris flow vulnerability assessment unit 923 is used to assess the debris flow vulnerability of the disaster-bearing body based on three vulnerability characteristics: social attributes, economic value, and hydropower project operation. The debris flow vulnerability assessment method is the same as the landslide vulnerability assessment method. After the vulnerability assessment, a debris flow vulnerability score can be obtained. The debris flow risk assessment unit 924 is used to comprehensively assess the susceptibility, hazard, and vulnerability of the affected body to debris flows. It calculates the debris flow risk value under specific working conditions through a weighted summation method, thereby achieving the assessment of debris flow risk.

[0029] The geological disaster emergency response module 10 includes: emergency supplies management submodule 101, emergency rescue management submodule 102, emergency plan management submodule 103, and emergency response submodule 104; The Emergency Supplies Management Submodule 101 is used to add, query, and update emergency supplies information such as type, quantity, storage location, custodian, custodian contact person, and contact number; The Emergency Rescue Management Submodule 102 is used to add, query, and update contact information for emergency rescue personnel, contact numbers, and affiliated departments of government departments at all levels, medical and fire-fighting professional institutions, and hydropower project operation and management units involved in the reservoir area. The emergency response plan management submodule 103 is used to generate geological disaster emergency response plans based on the geological disaster risk level, the type of carrier within the potential impact range, the regional traffic situation, the configuration of medical and fire-fighting forces, and the operation status of hydropower projects. The emergency response submodule 104 is used to push geological disaster risk warning information, emergency material information and emergency response plans to emergency rescue contacts of government departments at all levels, medical and fire protection institutions and hydropower project operation and management units within the potential impact range of geological disasters.

[0030] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A geological hazard information management and risk assessment system for hydropower reservoir areas, comprising hardware and software components, characterized in that... The hardware component includes: monitoring equipment (1), used to monitor information about the area where the hydropower project reservoir is located; The data acquisition device (2) is connected to the monitoring device (1) for collecting the monitoring data acquired by the monitoring device (1); The system terminal (4) is connected to the data acquisition device (2) for receiving monitoring data collected by the data acquisition device (2) via a wireless network; The solar panel (3) is electrically connected to the monitoring equipment (1) and the data acquisition equipment (2) to supply power to the monitoring equipment (1) and the data acquisition equipment (2); The software is mounted on the system terminal (4) and is supported by the system terminal (4); the software includes: a comprehensive interface module (5) for statistical analysis and visualization of data; The geological hazard early identification module (6) is used to periodically identify and extract potential geological hazard hazards in the reservoir area of ​​hydropower projects. The geological disaster information management module (7) is used to store geological disaster information and provide query functions; The geological disaster monitoring and early warning module (8) is used to manage the status of the monitoring equipment (1) and to issue early warnings for abnormal monitoring data. The geological hazard risk assessment module (9) is used to assess the risks of landslides and debris flows; The geological disaster emergency response module (10) is used to generate and push geological disaster risk warning information, emergency material information and emergency response plans.

2. The system for managing and assessing geological disaster information in hydropower reservoir areas according to claim 1, characterized in that, The monitoring equipment (1) includes: Rain gauge (11) is used to monitor rainfall in the area where the reservoir of a hydropower project is located; Inclinometer (12) is used to monitor the deep horizontal displacement of the reservoir area of ​​hydropower projects; Crack gauge (13) is used to monitor the opening and closing degree of crack development in the reservoir area of ​​hydropower projects; Mud level gauge (14) is used to monitor the mud and water level in the reservoir area of ​​hydropower projects; Water level gauge (15) is used to monitor changes in groundwater level in the reservoir area of ​​hydropower projects; GNSS stations (16) are used to monitor surface displacement in the reservoir area of ​​hydropower projects; Unmanned aerial vehicles (UAVs) (17) are used to acquire images or point cloud data of the reservoir area of ​​hydropower projects; Optical satellite (18) is used to acquire optical image data of reservoir areas for hydropower projects; InSAR satellite (19) is used to acquire InSAR image data of reservoir areas for hydropower projects.

3. The system for managing and assessing geological disaster information in hydropower reservoir areas according to claim 1, characterized in that, The geological hazard early identification module (6) includes: a geological hazard wide-area early identification submodule (61) and a geological hazard deformation feature extraction submodule (62). The wide-area early identification submodule for geological hazards (61) is used to periodically identify potential geological hazards in the reservoir area of ​​hydropower projects based on images acquired by optical satellites (18) and InSAR satellites (19); on this basis, the identified potential geological hazards are compared with existing geological hazards according to key location parameters. The geological disaster deformation feature extraction submodule (62) is used to periodically extract the deformation features of geological disasters based on the geological disaster data obtained by the UAV (17).

4. The hydropower project reservoir area geological disaster information management and risk assessment system according to claim 3, characterized in that, The geological disaster information management module (7) includes: a potential geological disaster hazard management sub-module (71) and a geological disaster information management sub-module (72); The potential geological hazard management submodule (71) is used to store the basic information of newly added potential geological hazards and provide query functions, and to synchronize the newly added potential geological hazards after review and confirmation to the geological hazard information management submodule (72). Stability can be categorized as: very stable, basically stable, and unstable; Sizes can be categorized as: small, medium, and large; The geological disaster information management submodule (72) is used to store, query and display the basic information, model and image information of existing geological disasters.

5. A geological hazard information management and risk assessment system for hydropower reservoir areas according to claim 4, characterized in that, Basic information on potential geological hazards includes: the reservoir area, distance from the dam, hazard type, geographical coordinates, bank location, scale, stability, and hazard level; The hazard level is determined by the hazard classification score, which is obtained by weighted summation of stability and scale. The expression for this score is: （1）； in, To score the level of hazard, , These are the quantitative values ​​for scale and potential hazards, respectively. , The weights for scale and potential risks are respectively. Set a low-level hazard threshold ,when At that time, the hazard level was classified as minor. Set intermediate-level hazard threshold ,when At that time, the hazard level was classified as medium hazard. when At that time, the hazard level was classified as a serious hazard.

6. The system for managing and assessing geological disaster information in hydropower reservoir areas according to claim 5, characterized in that, The geological disaster monitoring and early warning module (8) includes: a monitoring equipment management submodule (81), a monitoring data management submodule (82), and an anomaly early warning submodule (83); The monitoring equipment management submodule (81) is used to store the equipment information of the monitoring equipment (1) and provide query functions, and to alarm the abnormal status of the monitoring equipment; the information includes: the storage area, installation location, installation time, associated geological disaster point, working status, and communication method; The monitoring data management submodule (82) is used to store, query, output and visualize the time series data of the monitored physical quantities; the monitored physical quantities include: rainfall, displacement, groundwater level, mud water level and crack opening degree; The anomaly warning submodule (83) is used to manage the anomaly warning model of the monitored physical quantity, set the warning threshold and frequency, and perform hierarchical warnings for the anomaly monitoring data.

7. A geological hazard information management and risk assessment system for hydropower reservoir areas according to claim 6, characterized in that, The process for setting the warning threshold and frequency is as follows: Select the monitored physical quantity as the early warning parameter; set the basic threshold and frequency base value for each early warning parameter; The basic threshold and frequency values ​​of each warning parameter are adjusted according to the operating conditions to obtain the real-time warning threshold and real-time warning frequency. Operating conditions include rainfall intensity, rainfall duration, and reservoir water level. For each operating condition, a low operating condition threshold and a high operating condition threshold are set. The operating condition status is determined based on the high and low operating condition thresholds as follows: It is considered a high operating condition when it exceeds the high operating condition threshold. It is considered a low operating condition when it is less than the low operating condition threshold. All other conditions are normal operating conditions; For each operating condition factor, its adjustment weight is determined under each operating condition. The expression for the real-time warning threshold is then: （2）； in, The real-time warning threshold for the warning parameter. The basic threshold for early warning parameters, , , These are the adjustment weights corresponding to rainfall intensity, rainfall duration, and reservoir water level, respectively. The weighting of the hazard level; The warning frequency is related to the operating conditions. Specifically, when all operating factors are at a low operating condition, the warning frequency is reduced. When the operating conditions are normal and there are no high operating conditions, the basic value of the warning frequency is directly used as the real-time warning frequency. When there are high operating conditions, increase the warning frequency; when all operating conditions are high, increase the warning frequency to the maximum.

8. The hydropower project reservoir area geological disaster information management and risk assessment system according to claim 7, characterized in that, The geological hazard risk assessment module (9) includes: landslide risk assessment submodule (91) and debris flow risk assessment submodule (92); The landslide risk assessment submodule (91) includes: landslide susceptibility assessment unit (911), landslide hazard assessment unit (912), landslide vulnerability assessment unit (913), and landslide risk assessment unit (914). The landslide susceptibility assessment unit (911) is used to assess landslide susceptibility under specific working conditions by combining regional landslide geometry, slope structure, rainfall conditions and reservoir water level with artificial intelligence algorithms. Landslide geometry includes: slope height and slope gradient; slope structure types include: dip slope and reverse slope; rainfall conditions include: rainfall intensity and rainfall duration; changes in rainfall conditions and reservoir water levels constitute different working conditions; The landslide hazard assessment unit (912) is used to invert geotechnical mechanical parameters based on boundary conditions and historical monitoring data; on this basis, it performs numerical simulation of the entire process of landslide movement, ingress, and surge under specific working conditions and determines its potential impact range; based on the numerical simulation results, considering landslide failure characteristics, it assesses the landslide hazard under specific working conditions; and adjusts the landslide hazard assessment value according to the importance level of the hydropower project. Landslide boundary conditions include: landslide geometry, rainfall conditions, and reservoir operation conditions; reservoir operation conditions include: reservoir water level and underwater topography; geotechnical parameters include: cohesion, internal friction angle, unit weight, elastic modulus, and Poisson's ratio; landslide failure characteristics include: sliding volume, sliding distance, and sliding velocity. The landslide vulnerability assessment unit (913) is used to assess the landslide vulnerability of disaster-bearing bodies based on three vulnerability characteristics: social attributes, economic value, and hydropower project operation. The landslide risk assessment unit (914) is used to calculate the landslide risk value under a specific working condition by using a weighted summation method based on the predicted probability of landslide susceptibility, the landslide hazard assessment value and the landslide vulnerability score of the affected body. The debris flow risk assessment submodule (92) includes: debris flow susceptibility assessment unit (921), debris flow hazard assessment unit (922), debris flow vulnerability assessment unit for disaster-bearing bodies (923), and debris flow risk assessment unit (924). The debris flow susceptibility assessment unit (921) is used to assess the debris flow susceptibility under specific working conditions by combining information on the topographic conditions, rainfall conditions and material source conditions of the watershed unit and using artificial intelligence algorithms. Topographic conditions of a watershed unit include: area, elevation difference, length of the main ditch, and slope of the main ditch; sediment source conditions include: vegetation cover, sediment source area, and distribution of loose deposits. The debris flow hazard assessment unit (922) is used to invert key physical parameters based on historical debris flow monitoring data and boundary conditions; on this basis, it performs numerical simulation of the entire process of debris flow movement, inflow, and surge under specific working conditions and determines its potential impact range; based on the numerical simulation results, considering key dynamic parameters, it assesses the hazard range of the potential impact of debris flow under specific working conditions; and it adjusts the debris flow hazard assessment value according to the importance level of the hydropower project. The boundary conditions for debris flows include: topographic conditions of the watershed unit, source conditions, rainfall conditions, and reservoir operation conditions; key physical parameters include: unit weight, base friction coefficient, and turbulence coefficient; key dynamic parameters include: debris flow velocity, flow depth, deposition depth, deposition range, and impact momentum. The debris flow vulnerability assessment unit (923) is used to assess the debris flow vulnerability of disaster-bearing bodies based on three vulnerability characteristics: social attributes, economic value, and hydropower project operation. The debris flow risk assessment unit (924) is used to comprehensively assess the susceptibility, hazard and vulnerability of the disaster-bearing body of debris flow, and to calculate the debris flow risk value under specific working conditions through a weighted summation method.

9. A geological hazard information management and risk assessment system for hydropower reservoir areas according to claim 8, characterized in that, The adjustment expressions for landslide hazard assessment values ​​and debris flow hazard assessment values ​​are as follows: （3）； in, This is the adjusted landslide or debris flow hazard assessment value. Values ​​to be processed for landslide or debris flow hazard assessment. This is an adjustment factor for landslides or debris flows. The importance level of the hydropower reservoir area.

10. A geological hazard information management and risk assessment system for hydropower reservoir areas according to claim 8, characterized in that, The geological disaster emergency response module (10) includes: emergency material management sub-module (101), emergency rescue management sub-module (102), emergency plan management sub-module (103) and emergency response sub-module (104). The emergency supplies management submodule (101) is used to add, query, and update emergency supplies information; The emergency rescue management submodule (102) is used to add, query, and update contact information of the management departments involved in the reservoir area; The emergency response plan management submodule (103) is used to generate geological disaster emergency response plans based on geological disaster risk level, type of bearing structure, regional traffic conditions, configuration of medical and fire-fighting forces, and operation status of hydropower projects. The emergency response submodule (104) is used to push geological disaster risk warning information, emergency material information and emergency response plans to the emergency rescue contacts of the relevant management departments, professional institutions and hydropower project operation and management units in the reservoir area.

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