Disaster prevention and emergency treatment system and method applied to barrier lake

Abstract

The embodiment of the invention relates to the technical field of barrier lakes, and particularly discloses a disaster prevention and emergency treatment system and method applied to a barrier lake. According to the embodiment of the invention, the method comprises the steps: carrying out the example patrol monitoring and analysis of a plurality of target bank slope mountains, and screening and recognizing a risky bank slope mountain with a barrier lake risk; key monitoring is carried out, and whether a dammed lake outburst sign exists or not is judged; when there is no dammed lake outburst sign, determining a disaster prevention area, and carrying out disaster prevention alarm on the disaster prevention area; and when the dammed lake outburst sign exists, a disaster emergency area is determined, and emergency processing alarm is carried out on the disaster emergency area. The risk bank slope mountain with the barrier lake risk can be screened and identified, key monitoring is carried out, whether a barrier lake outburst sign exists or not is judged, disaster prevention warning is carried out when the barrier lake outburst sign does not exist, and emergency processing warning is carried out when the barrier lake outburst sign exists. Therefore, automatic and accurate disaster prevention and emergency treatment of the barrier lake are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of barrier lakes, and in particular relates to a disaster prevention and emergency treatment system and method applied to barrier lakes. Background Art

[0002] A barrier lake is formed by the storage of water after a valley, river valley or riverbed is blocked by a landslide caused by volcanic lava flow, glacial till or earthquake activity that causes the collapse of mountain rocks. When the blocking material is washed, eroded, dissolved or collapsed, the barrier lake may burst, causing a flood in an instant and causing devastating damage to the downstream areas.

[0003] In the prior art, there is no effective technical implementation for disaster prevention and emergency response of barrier lakes. It is usually necessary to obtain data from a variety of monitoring and to manually determine the timing of disaster prevention and emergency response. Therefore, accurate judgment cannot be achieved. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a disaster prevention and emergency treatment system and method for a barrier lake, aiming to solve the problems raised in the background technology.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: A disaster prevention and emergency treatment method for a barrier lake, the method specifically comprising the following steps: Carry out routine inspections and analysis of multiple target slopes and mountains, and screen and identify risky slopes and mountains with the risk of barrier lakes; Focus on monitoring the risky slopes and mountains to determine whether there are signs of barrier lake breach; When there is no sign of the barrier lake bursting, determine the disaster prevention area of ​​the risk bank slope mountain, and issue a disaster prevention warning for the disaster prevention area; When there are signs of a barrier lake bursting, the disaster emergency area of ​​the risky slope mountain is determined, and emergency treatment and warning are issued for the disaster emergency area.

[0006] A disaster prevention and emergency response system for a barrier lake, the system comprising a routine monitoring and screening unit, a key monitoring and judgment unit, a disaster prevention alarm unit and an emergency response alarm unit, wherein: The routine monitoring and screening unit is used to conduct routine monitoring and analysis of multiple target slopes and mountains, and screen and identify risky slopes and mountains with the risk of barrier lakes; A key monitoring and judging unit is used to conduct key monitoring on the risky bank slope and mountain to judge whether there are signs of barrier lake breach; A disaster prevention warning unit is used to determine the disaster prevention area of ​​the risk bank slope mountain when there is no sign of the barrier lake bursting, and to issue a disaster prevention warning for the disaster prevention area; The emergency response alarm unit is used to determine the disaster emergency area of ​​the risky slope mountain when there are signs of the barrier lake bursting, and to issue an emergency response alarm to the disaster emergency area.

[0007] Compared with the prior art, the present invention has the following beneficial effects: The embodiment of the present invention screens and identifies risky bank slopes and mountains with the risk of a landslide lake by routine patrol monitoring and analysis of multiple target bank slopes and mountains; performs key monitoring to determine whether there are signs of a landslide lake bursting; when there are no signs of a landslide lake bursting, determines a disaster prevention area and issues a disaster prevention warning for the disaster prevention area; when there are signs of a landslide lake bursting, determines a disaster emergency area and issues an emergency treatment warning for the disaster emergency area. It is possible to screen and identify risky bank slopes and mountains with the risk of a landslide lake, perform key monitoring to determine whether there are signs of a landslide lake bursting, issue a disaster prevention warning when there are no signs of a landslide lake bursting, and issue an emergency treatment warning when there are signs of a landslide lake bursting, thereby achieving automatic and accurate disaster prevention and emergency treatment of landslide lakes. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0009] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0010] Figure 2 A flow chart of screening and identifying risky slopes and mountains in the method provided in an embodiment of the present invention is shown.

[0011] Figure 3 A flow chart of obtaining multiple periodic monitoring data in the method provided by an embodiment of the present invention is shown.

[0012] Figure 4 A flow chart of key monitoring of risky slopes and mountains in the method provided by an embodiment of the present invention is shown.

[0013] Figure 5 A flow chart of performing disaster prevention warning in the method provided in an embodiment of the present invention is shown.

[0014] Figure 6 A flow chart of emergency alarm processing in the method provided by an embodiment of the present invention is shown.

[0015] Figure 7The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0016] Figure 8 A structural block diagram of a patrol monitoring and screening unit in a system provided by an embodiment of the present invention is shown.

[0017] Fig. 9 The structure block diagram of the disaster prevention alarm unit in the system provided by the embodiment of the present invention is shown.

[0018] Fig.10 The structure block diagram of the emergency alarm processing unit in the system provided by the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] It is understandable that in the prior art, there is no effective technical implementation for disaster prevention and emergency response of barrier lakes. It is usually necessary to obtain data from multiple monitoring systems and manually judge the timing of disaster prevention and emergency response. Therefore, accurate judgment cannot be achieved.

[0021] To solve the above problems, the embodiments of the present invention screen and identify risky bank slopes and mountains with the risk of a landslide lake by routine patrol monitoring and analysis of multiple target bank slopes and mountains; focus on monitoring the risky bank slopes and mountains to determine whether there are signs of a landslide lake bursting; when there are no signs of a landslide lake bursting, determine the disaster prevention area of ​​the risky bank slopes and mountains, and issue a disaster prevention warning for the disaster prevention area; when there are signs of a landslide lake bursting, determine the disaster emergency area of ​​the risky bank slopes and mountains, and issue an emergency treatment warning for the disaster emergency area. It is possible to screen and identify risky bank slopes and mountains with the risk of a landslide lake, focus on monitoring, determine whether there are signs of a landslide lake bursting, issue a disaster prevention warning when there are no signs of a landslide lake bursting, and issue an emergency treatment warning when there are signs of a landslide lake bursting, thereby achieving automatic and accurate disaster prevention and emergency treatment of landslide lakes.

[0022] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0023] Specifically, the disaster prevention and emergency treatment method applied to the barrier lake comprises the following steps: Step S101, routine monitoring and analysis are performed on multiple target slopes and mountains, and risky slopes and mountains with the risk of forming a barrier lake are screened and identified.

[0024] In an embodiment of the present invention, multiple target bank slopes are determined, geological survey data (including geological structure, stratigraphic lithology, fault structure, joint development, geomorphic characteristics, water system distribution and other data) of the multiple target bank slopes are obtained, and then historical disaster data (including historical earthquake, landslide, mud-rock flow and other disaster record data) of the multiple target bank slopes are obtained. According to a preset mountain monitoring cycle, periodic remote sensing detection is performed on the multiple target bank slopes (remote sensing technology, such as satellite remote sensing, drone aerial photography, etc., can be used to obtain high-resolution images of the mountain), multiple remote sensing detection data are obtained, and according to a preset mountain monitoring cycle, periodic remote sensing detection is performed on the multiple target bank slopes. Conduct systematic mountain monitoring (which can be done through ground displacement monitoring stations, groundwater level observation wells, rain gauges, etc., to monitor the deformation, displacement, groundwater level changes, etc. of the mountain in real time), obtain multiple mountain monitoring data, organize multiple geological exploration data, multiple historical disaster data, multiple remote sensing detection data and multiple mountain monitoring data, generate multiple periodic monitoring data, use numerical simulation technology (such as finite element analysis, discrete element analysis, etc.) to simulate and predict the stability of the mountain based on multiple periodic monitoring data, obtain multiple periodic analysis results, and then, according to the multiple periodic analysis results, screen and identify risky bank slopes with the risk of barrier lakes from multiple target bank slopes.

[0025] Specifically, Figure 2 A flow chart of screening and identifying risky slopes and mountains in the method provided in an embodiment of the present invention is shown.

[0026] Among them, in the preferred embodiment provided by the present invention, the routine monitoring and analysis of multiple target bank slopes and mountains, screening and identifying risky bank slopes and mountains with the risk of barrier lakes specifically includes the following steps: Step S1011, performing periodic monitoring on a plurality of target slope mountains according to a preset mountain monitoring cycle, and obtaining a plurality of periodic monitoring data.

[0027] Specifically, Figure 3 A flow chart of obtaining multiple periodic monitoring data in the method provided by an embodiment of the present invention is shown.

[0028] Among them, in the preferred embodiment provided by the present invention, the periodic monitoring of the plurality of target slope mountains according to the preset mountain monitoring cycle and the acquisition of the plurality of periodic monitoring data specifically include the following steps: Step S10111, obtaining geological survey data of a plurality of target slopes and mountains; Step S10112, obtaining historical disaster data of a plurality of target slopes and mountains; Step S10113, performing periodic remote sensing detection on the plurality of target slope mountains according to a preset mountain monitoring cycle to obtain a plurality of remote sensing detection data; Step S10114, performing periodic mountain monitoring on the plurality of target slope mountains according to a preset mountain monitoring cycle to obtain a plurality of mountain monitoring data; Step S10115, sorting out the plurality of geological survey data, the plurality of historical disaster data, the plurality of remote sensing detection data and the plurality of mountain monitoring data to generate a plurality of periodic monitoring data.

[0029] Furthermore, the routine monitoring and analysis of multiple target bank slopes and mountains to screen and identify risky bank slopes and mountains with the risk of barrier lakes also includes the following steps: Step S1012, using numerical simulation technology, simulate and predict the stability of the mountain for the plurality of periodic monitoring data to obtain a plurality of periodic analysis results.

[0030] Step S1013, screening and identifying risky bank slopes and mountains with the risk of barrier lake from the multiple target bank slopes and mountains according to the multiple periodic analysis results.

[0031] Among them, in the preferred embodiment provided by the present invention, the use of numerical simulation technology to simulate and predict the stability of the mountain for multiple periodic monitoring data, and obtaining multiple periodic analysis results specifically includes the following steps: Acquire a multi-source monitoring data set, which includes stress-strain data, rainfall time series data, geological properties, and surface displacement gradients; Based on chaotic dynamics, the nonlinear dynamic model of mountain behavior is constructed by utilizing geological characteristics and gravity influence, and then solved to obtain the prediction results of the dynamic model. The corresponding process has the following relationship: ; in, represents the prediction results of the kinetic model, represents the partial derivative, Indicates the mountain at time t The displacement vector field at denote the damping coefficient and diffusion coefficient respectively, The acceleration term representing the displacement is used to reflect the dynamic response of the mountain; represents the damping term, which is used to describe the energy loss due to internal resistance; represents the diffusion term, which is used to describe the distribution change of stress or displacement inside the mountain; represents the geological driving force, represents gravity, Indicates geological features; An adaptive landslide probability model is constructed based on rainfall time series data and geological characteristics to calculate the probability of landslide occurrence. The corresponding process has the following relationship: ; in, represents the probability of landslide occurrence, ranging from [0,1]; represents the exponential function, which is used to map linear combinations to nonlinear probabilities; represents the weight coefficient of the corresponding feature, represents the number of features, Indicates rainfall, Indicates the slope angle, represents the combined characteristic function; Construct a deep learning model, use historical disaster event data to train the deep learning model, obtain a trained deep learning model, pre-process the multi-source monitoring data set, and input it into the trained deep learning model to calculate and determine the landslide prediction probability; The prediction results of the dynamic model, the probability of landslide occurrence and the predicted probability of landslide are fused using the fusion model to obtain the stability factor of the mountain and the final probability of landslide occurrence. The corresponding process has the following relationship: ; in, represents the stability factor of the mountain, It means the mountain is stable. It means the mountain is unstable; Indicates the final probability of landslide occurrence, ranging from [0,1]; Represents different weight coefficients in the fusion model, represents the fusion model, Represents the predicted probability of landslide.

[0032] In an embodiment of the present invention, starting from multi-source data, combining dynamic models, adaptive probability models and deep learning models, the traditional physical model is integrated with the data-driven model, which can accurately predict and assess risks under complex geological conditions.

[0033] Among them, in the preferred embodiment provided by the present invention, the process of obtaining the optimal weight coefficient in the fusion model specifically includes the following steps: The stability factor of the historical mountain is obtained, and the stability factor of the historical mountain is used as the first true value. Based on the square of the error, the first loss function is constructed using the first true value and the stability factor of the mountain predicted by the fusion model. The corresponding process has the following relationship: ; in, represents the first loss function, Indicates the total length of time, represents the first true value; The historical landslide probability is obtained and used as the second true value. Based on the square of the error, the second loss function is constructed using the second true value and the final landslide probability predicted by the fusion model. The corresponding process has the following relationship: ; in, represents the second loss function, represents the second real value; Add the first loss function and the second loss function to get the global loss function. The corresponding process has the following relationship: ; in, represents the global loss function; The optimal weight parameters of the fusion model are calculated by minimizing the global loss function.

[0034] Among them, in the preferred embodiment provided by the present invention, the calculation process of the combined characteristic function has the following relationship: ; in, represents the rainfall impact function, represents the slope aggregate influence function, represents the geological characteristics influence function, represents the time-varying characteristic function, They represent the weight coefficients corresponding to the rainfall influence function, the slope aggregate influence function, the geological characteristic influence function and the time transformation characteristic function respectively; Indicates the current time; The calculation process of rainfall impact function has the following relationship: ; in, represents the critical rainfall, Indicates the duration of rainfall. represents the saturation time constant of the rock and soil layer; The calculation process of the slope collective influence function has the following relationship: ; in, Indicates the slope tangent value, represents the internal friction angle of the rock layer, represents the critical internal friction angle; The calculation process of geological characteristics influence function has the following relationship: ; in, represents the density of the rock layer, represents the acceleration due to gravity, Indicates the slope height, represents the effective stress, represents the tangent of the internal friction angle, Indicates the cohesion of rock and soil layers; The calculation process of the time-transformation characteristic function has the following relationship: ; in, represents the amplitude coefficient, Indicates the time period, Represents pi.

[0035] Among them, in the preferred embodiment provided by the present invention, the preprocessing of the multi-source monitoring data set and inputting it into the trained deep learning model to calculate and determine the landslide prediction probability specifically includes the following steps: Fill missing values ​​in multi-source monitoring data sets, and then perform normalization operations to obtain preprocessed data; Divide the preprocessed data into segments of fixed length according to the time window to obtain the time window data; 1D convolution is used to extract features from time window data to obtain convolution features. The corresponding process has the following relationship: ; in, represents the convolution feature, represents the convolution kernel parameters, represents the activation function, represents the bias parameter of the convolution, Represents time window data; The convolutional features are fed into the LSTM unit to extract long-term dependencies and obtain the hidden state. The corresponding process has the following relationship: ; in, Indicates the hidden state, Represents an LSTM unit; The hidden state is passed into the fully connected layer and the landslide prediction probability is obtained through the Sigmoid activation function. The corresponding process has the following relationship: ; in, represents the Sigmoid activation function, represents the weight of the fully connected layer, Represents the bias parameters of the fully connected layer.

[0036] Among them, in the preferred implementation manner provided by the present invention, the deep learning model is trained using historical disaster event data to obtain the trained deep learning model, which specifically includes the following steps: Obtain historical disaster event data and historical multi-source monitoring data sets; Feed the historical multi-source monitoring data set into the deep learning model to obtain the landslide prediction probability; Taking historical disaster event data as the true label and landslide prediction probability as the prediction label, based on the binary cross entropy loss probability, the landslide risk prediction loss function is constructed using the true label and the prediction label. The corresponding process has the following relationship: ; in, represents the landslide risk prediction loss function, represents the number of samples, represents the logarithmic function, Indicates n The true labels of samples, Represents the predicted label of the nth sample; Set the weight decay strategy and learning parameters of the Adam optimizer, and input the risk prediction loss function into the Adam optimizer for optimization training; After the training is completed, the trained deep learning model is obtained.

[0037] Furthermore, the disaster prevention and emergency treatment method applied to the barrier lake also includes the following steps: Step S102: focus on monitoring the risky bank slope to determine whether there are signs of the barrier lake bursting.

[0038] In an embodiment of the present invention, after determining the risky bank slope mountain body, key remote sensing detection is performed on the risky bank slope mountain body to continuously obtain key detection data, and key mountain monitoring is performed on the risky bank slope mountain body to continuously obtain key monitoring data, and then based on the key detection data and the key monitoring data, a burst analysis is performed on the risky bank slope mountain body to determine whether there are signs of a barrier lake burst (for example: the blockage begins to loosen, slide or crack; heavy rain, continuous rainfall and other weather conditions cause the water level to rise sharply; changes in water flow speed and direction).

[0039] Specifically, Figure 4 A flow chart of key monitoring of risky slopes and mountains in the method provided by an embodiment of the present invention is shown.

[0040] Among them, in the preferred embodiment provided by the present invention, the key monitoring of the risky bank slope mountain and judging whether there are signs of barrier lake breach specifically include the following steps: Step S1021, performing key remote sensing detection on the risky bank slope and mountain, and continuously acquiring key detection data; Step S1022, performing key mountain monitoring on the risky bank slope mountain, and continuously acquiring key monitoring data; Step S1023, based on the key detection data and the key monitoring data, a collapse analysis is performed on the risky bank slope to determine whether there are signs of a barrier lake collapse.

[0041] Furthermore, the disaster prevention and emergency treatment method applied to the barrier lake also includes the following steps: Step S103, when there is no sign of the barrier lake bursting, determining the disaster prevention area of ​​the risky bank slope mountain, and issuing a disaster prevention warning for the disaster prevention area.

[0042] In an embodiment of the present invention, when there is no sign of a barrier lake bursting, a disaster prevention instruction is generated, and based on the disaster prevention instruction, a disaster prevention area for the risky slope mountain is determined, and then in the disaster prevention area, a disaster prevention warning is issued to relocate or protect personnel and infrastructure, and to improve the flood control standards of the downstream flooded area. In addition, in the disaster prevention area, a second drainage channel is deployed in advance, and a disaster prevention warning is issued to block the formation of a barrier dam or reduce the formation height of the barrier dam (also including: preventing and controlling mountain landslides or reducing the amount of landslides, cascade development of the basin, etc.).

[0043] Specifically, Figure 5 A flow chart of performing disaster prevention warning in the method provided in an embodiment of the present invention is shown.

[0044] Among them, in the preferred embodiment provided by the present invention, when there is no sign of the barrier lake bursting, determining the disaster prevention area of ​​the risk bank slope mountain, and issuing a disaster prevention warning to the disaster prevention area specifically comprises the following steps: Step S1031, when there is no sign of the barrier lake bursting, generating a disaster prevention instruction; Step S1032, determining the disaster prevention area of ​​the risky bank slope mountain according to the disaster prevention instruction; Step S1033, in the disaster prevention area, relocate or protect personnel and infrastructure, and issue a disaster prevention warning to improve the flood control standard of the downstream flooded area; Step S1034, in the disaster prevention area, a disaster prevention warning is issued to lay out the second drainage channel in advance, block the formation of a landslide dam, or reduce the formation height of the landslide dam.

[0045] Furthermore, the disaster prevention and emergency treatment method applied to the barrier lake also includes the following steps: Step S104, when there are signs of the barrier lake bursting, determining the disaster emergency area of ​​the risky slope mountain, and conducting emergency processing and warning for the disaster emergency area.

[0046] In an embodiment of the present invention, when there are signs of a barrier lake bursting, an emergency handling instruction is generated, and according to the emergency handling instruction, a disaster emergency zone of the risky slope mountain is determined, and then in the disaster emergency zone, emergency handling alarms are issued for digging spillways, removing barrier bodies or lowering their heights, reinforcing barrier dams, opening emergency discharge channels, or mechanically pumping out water (also including: building dams upstream to block water), and in the disaster emergency zone, emergency handling alarms are issued for organizing personnel, asset transfers, and protection of important infrastructure.

[0047] Specifically, Figure 6 A flow chart of emergency alarm processing in the method provided by an embodiment of the present invention is shown.

[0048] Among them, in the preferred embodiment provided by the present invention, when there are signs of the barrier lake bursting, determining the disaster emergency area of ​​the risk bank slope mountain, and conducting emergency treatment and warning for the disaster emergency area specifically include the following steps: Step S1041, when there are signs of the barrier lake bursting, generating an emergency processing instruction; Step S1042, determining the disaster emergency area of ​​the risky bank slope mountain according to the emergency processing instruction; Step S1043, in the disaster emergency area, an emergency treatment alarm is issued for excavating a spillway, removing a damming body or lowering its height, reinforcing a damming body, opening an emergency spillway, or mechanically pumping out water; Step S1044, in the disaster emergency area, organize emergency response alerts for personnel and asset transfer and protection of important infrastructure.

[0049] Furthermore, Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0050] Among them, in another preferred embodiment provided by the present invention, the disaster prevention and emergency treatment system applied to the barrier lake includes: The routine monitoring and screening unit 101 is used to perform routine monitoring and analysis on multiple target slopes and mountains, and screen and identify risky slopes and mountains with the risk of forming a barrier lake.

[0051] In the embodiment of the present invention, after determining multiple target bank slopes, the patrol monitoring and screening unit 101 obtains geological survey data of multiple target bank slopes (including geological structure, stratum lithology, fault structure, joint development, geomorphic characteristics, water system distribution and other data), and then obtains historical disaster data of multiple target bank slopes (including historical earthquake, landslide, mud-rock flow and other disaster record data), and performs periodic remote sensing detection of multiple target bank slopes according to a preset mountain monitoring cycle (remote sensing technology, such as satellite remote sensing, drone aerial photography, etc., can be used to obtain high-resolution images of the mountain), obtains multiple remote sensing detection data, and performs a periodic remote sensing detection of multiple target bank slopes according to a preset mountain monitoring cycle. Conduct periodic mountain monitoring on the slope mountain (this can be achieved through ground displacement monitoring stations, groundwater level observation wells, rain gauges, etc., to monitor the deformation, displacement, groundwater level changes, etc. of the mountain in real time), obtain multiple mountain monitoring data, organize multiple geological survey data, multiple historical disaster data, multiple remote sensing detection data and multiple mountain monitoring data, generate multiple periodic monitoring data, use numerical simulation technology (such as finite element analysis, discrete element analysis, etc.) to simulate and predict the stability of the mountain based on multiple periodic monitoring data, obtain multiple periodic analysis results, and then, according to the multiple periodic analysis results, screen and identify risky slope mountains with the risk of barrier lakes from multiple target slope mountains.

[0052] Specifically, Figure 8 It shows a structural block diagram of the patrol monitoring and screening unit 101 in the system provided by an embodiment of the present invention.

[0053] Among them, in the preferred embodiment provided by the present invention, the patrol monitoring and screening unit 101 specifically includes: The periodic monitoring module 1011 is used to perform periodic monitoring on the plurality of target slope mountains according to a preset mountain monitoring period, and obtain a plurality of periodic monitoring data; The mountain simulation prediction module 1012 is used to simulate and predict the stability of the mountain based on the multiple periodic monitoring data using numerical simulation technology to obtain multiple periodic analysis results; The screening and identification module 1013 is used to screen and identify risky bank slopes and mountains with the risk of forming a barrier lake from the multiple target bank slopes and mountains according to the multiple periodic analysis results.

[0054] Furthermore, the disaster prevention and emergency response system applied to the barrier lake also includes: The key monitoring and judging unit 102 is used to perform key monitoring on the risky bank slope and mountain to judge whether there are signs of the barrier lake bursting.

[0055] In an embodiment of the present invention, after determining the risky bank slope mountain, the key monitoring and judgment unit 102 performs key remote sensing detection on the risky bank slope mountain, continuously obtains key detection data, and performs key mountain monitoring on the risky bank slope mountain, continuously obtains key monitoring data, and then performs a collapse analysis on the risky bank slope mountain based on the key detection data and the key monitoring data to determine whether there are signs of a barrier lake collapse (for example: the blockage begins to loosen, slide or crack; heavy rain, continuous rainfall and other weather conditions cause the water level to rise sharply; changes in water flow speed and direction).

[0056] The disaster prevention warning unit 103 is used to determine the disaster prevention area of ​​the risky bank slope mountain when there is no sign of the barrier lake bursting, and to issue a disaster prevention warning for the disaster prevention area.

[0057] In an embodiment of the present invention, when there is no sign of the bursting of the barrier lake, the disaster prevention warning unit 103 generates a disaster prevention instruction, and determines the disaster prevention area of ​​the risky slope mountain according to the disaster prevention instruction, and then in the disaster prevention area, a disaster prevention warning is issued to relocate or protect personnel and infrastructure, and to improve the flood control standards of the downstream flooded area. In the disaster prevention area, a disaster prevention warning is issued to lay out the second drainage channel in advance, block the formation of the barrier dam, or reduce the formation height of the barrier dam (also including: preventing and controlling mountain landslides or reducing the amount of landslides, cascade development of the basin, etc.).

[0058] Specifically, Fig. 9 It shows a structural block diagram of the disaster prevention alarm unit 103 in the system provided by the embodiment of the present invention.

[0059] Among them, in the preferred implementation mode provided by the present invention, the disaster prevention warning unit 103 specifically includes: The prevention instruction generation module 1031 is used to generate a disaster prevention instruction when there is no sign of the barrier lake bursting; A prevention area determination module 1032 is used to determine the disaster prevention area of ​​the risky bank slope mountain according to the disaster prevention instruction; The first prevention warning module 1033 is used for disaster prevention warning in the disaster prevention area to relocate or protect personnel and infrastructure and improve the flood prevention standard of the downstream flooded area; The second prevention warning module 1034 is used to provide disaster prevention warnings for early deployment of the second drainage channel, blocking the formation of a dam, or reducing the formation height of the dam in the disaster prevention area.

[0060] Furthermore, the disaster prevention and emergency response system applied to the barrier lake also includes: The emergency processing alarm unit 104 is used to determine the disaster emergency area of ​​the risk slope mountain when there are signs of the barrier lake bursting, and to issue an emergency processing alarm to the disaster emergency area.

[0061] In an embodiment of the present invention, when there are signs of a barrier lake bursting, the emergency processing alarm unit 104 generates an emergency processing instruction, and according to the emergency processing instruction, determines the disaster emergency area of ​​the risky slope mountain, and then in the disaster emergency area, performs emergency processing alarms for digging spillways, removing barrier bodies or lowering their heights, reinforcing barrier dams, opening emergency discharge channels, or mechanically pumping out water (also including: building dams upstream to block water), and in the disaster emergency area, performs emergency processing alarms for organizing personnel, asset transfers, and protection of important infrastructure.

[0062] Specifically, Fig.10 It shows a structural block diagram of the emergency processing alarm unit 104 in the system provided by the embodiment of the present invention.

[0063] Among them, in the preferred implementation mode provided by the present invention, the emergency processing alarm unit 104 specifically includes: The emergency instruction generation module 1041 is used to generate emergency processing instructions when there are signs of the barrier lake bursting; The emergency area determination module 1042 is used to determine the disaster emergency area of ​​the risk bank slope mountain body according to the emergency processing instruction; The first emergency warning module 1043 is used to issue emergency warnings for excavating spillways, removing dam bodies or lowering their height, reinforcing dams, opening emergency spillways, or mechanically pumping out water in the disaster emergency area; The second emergency warning module 1044 is used to organize emergency response warnings for personnel and asset transfer and protection of important infrastructure in the disaster emergency area.

[0064] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0065] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0066] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0067] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0068] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A disaster prevention and emergency treatment method for a barrier lake, characterized in that: The method specifically comprises the following steps: Carry out routine inspections and analysis of multiple target slopes and mountains, and screen and identify risky slopes and mountains with the risk of barrier lakes; Focus on monitoring the risky slopes and mountains to determine whether there are signs of barrier lake breach; When there is no sign of the barrier lake bursting, determine the disaster prevention area of ​​the risk bank slope mountain, and issue a disaster prevention warning for the disaster prevention area; When there are signs of a barrier lake bursting, determine the disaster emergency area of ​​the risk bank slope and mountain, and issue emergency treatment warnings to the disaster emergency area; The routine monitoring and analysis of multiple target bank slopes and mountains to screen and identify risky bank slopes and mountains with the risk of barrier lakes specifically includes the following steps: According to a preset mountain monitoring cycle, periodic monitoring is performed on the plurality of target slope mountains to obtain a plurality of periodic monitoring data; Using numerical simulation technology, simulate and predict the stability of the mountain based on the multiple periodic monitoring data to obtain multiple periodic analysis results; According to the analysis results of the multiple cycles, risky bank slopes and mountains with the risk of barrier lakes are screened and identified from the multiple target bank slopes and mountains.

2. The disaster prevention and emergency treatment method for a barrier lake according to claim 1, characterized in that: The method of using numerical simulation technology to simulate and predict the stability of a mountain based on a plurality of periodic monitoring data and obtaining a plurality of periodic analysis results specifically includes the following steps: Acquire a multi-source monitoring data set, which includes stress-strain data, rainfall time series data, geological properties, and surface displacement gradients; Based on chaotic dynamics, the nonlinear dynamic model of mountain behavior is constructed by utilizing geological characteristics and gravity influence, and then solved to obtain the prediction results of the dynamic model. The corresponding process has the following relationship: ； in, represents the prediction results of the kinetic model, represents the partial derivative, Indicates the mountain at time t The displacement vector field at denote the damping coefficient and diffusion coefficient respectively, The acceleration term representing the displacement is used to reflect the dynamic response of the mountain; represents the damping term, which is used to describe the energy loss due to internal resistance; represents the diffusion term, which is used to describe the distribution change of stress or displacement inside the mountain; represents the geological driving force, represents gravity, Indicates geological features; An adaptive landslide probability model is constructed based on rainfall time series data and geological characteristics to calculate the probability of landslide occurrence. The corresponding process has the following relationship: ； in, represents the probability of landslide occurrence, ranging from [0,1]; represents the exponential function, which is used to map linear combinations to nonlinear probabilities; represents the weight coefficient of the corresponding feature, represents the number of features, Indicates rainfall, Indicates the slope angle, represents the combined characteristic function; Construct a deep learning model, use historical disaster event data to train the deep learning model, obtain a trained deep learning model, pre-process the multi-source monitoring data set, and input it into the trained deep learning model to calculate and determine the landslide prediction probability; The prediction results of the dynamic model, the probability of landslide occurrence and the predicted probability of landslide are fused using the fusion model to obtain the stability factor of the mountain and the final probability of landslide occurrence. The corresponding process has the following relationship: ； in, represents the stability factor of the mountain, It means the mountain is stable. It means the mountain is unstable; Indicates the final probability of landslide occurrence, ranging from [0,1]; Represents different weight coefficients in the fusion model, represents the fusion model, Represents the predicted probability of landslide.

3. The disaster prevention and emergency treatment method for a barrier lake according to claim 2, characterized in that: The process of obtaining the optimal weight coefficient in the fusion model specifically includes the following steps: The stability factor of the historical mountain is obtained, and the stability factor of the historical mountain is used as the first true value. Based on the square of the error, the first loss function is constructed using the first true value and the stability factor of the mountain predicted by the fusion model. The corresponding process has the following relationship: ； in, represents the first loss function, Indicates the total length of time, represents the first true value; The historical landslide probability is obtained and used as the second true value. Based on the square of the error, the second loss function is constructed using the second true value and the final landslide probability predicted by the fusion model. The corresponding process has the following relationship: ； in, represents the second loss function, represents the second real value; Add the first loss function and the second loss function to get the global loss function. The corresponding process has the following relationship: ； in, represents the global loss function; The optimal weight parameters of the fusion model are determined by minimizing the global loss function.

4. The disaster prevention and emergency treatment method for a barrier lake according to claim 3, characterized in that: The calculation process of the combined characteristic function has the following relationship: ； in, represents the rainfall impact function, represents the slope aggregate influence function, represents the geological characteristics influence function, represents the time-varying characteristic function, They represent the weight coefficients corresponding to the rainfall influence function, the slope aggregate influence function, the geological characteristic influence function and the time transformation characteristic function respectively; Indicates the current time; The calculation process of rainfall impact function has the following relationship: ； in, represents the critical rainfall, Indicates the duration of rainfall. represents the saturation time constant of the rock and soil layer; The calculation process of the slope collective influence function has the following relationship: ； in, Indicates the slope tangent value, represents the internal friction angle of the rock layer, represents the critical internal friction angle; The calculation process of geological characteristics influence function has the following relationship: ； in, represents the density of the rock layer, represents the acceleration due to gravity, Indicates the slope height, represents the effective stress, represents the tangent of the internal friction angle, Indicates the cohesion of rock and soil layers; The calculation process of the time-transformation characteristic function has the following relationship: ； in, represents the amplitude coefficient, Indicates the time period, Represents pi.

5. The disaster prevention and emergency treatment method for a barrier lake according to claim 4, characterized in that: The preprocessing of the multi-source monitoring data set and inputting it into the trained deep learning model to calculate and determine the landslide prediction probability specifically includes the following steps: Fill missing values ​​in multi-source monitoring data sets, and then perform normalization operations to obtain preprocessed data; Divide the preprocessed data into segments of fixed length according to the time window to obtain the time window data; 1D convolution is used to extract features from time window data to obtain convolution features. The corresponding process has the following relationship: ； in, represents the convolution feature, represents the convolution kernel parameters, represents the activation function, represents the bias parameter of the convolution, Represents time window data; The convolutional features are fed into the LSTM unit to extract long-term dependencies and obtain the hidden state. The corresponding process has the following relationship: ； in, Indicates the hidden state, Represents an LSTM unit; The hidden state is passed into the fully connected layer and the landslide prediction probability is obtained through the Sigmoid activation function. The corresponding process has the following relationship: ； in, represents the Sigmoid activation function, represents the weight of the fully connected layer, Represents the bias parameters of the fully connected layer.

6. The disaster prevention and emergency treatment method for a barrier lake according to claim 5, characterized in that: The method of training the deep learning model using historical disaster event data to obtain the trained deep learning model specifically includes the following steps: Obtain historical disaster event data and historical multi-source monitoring data sets; Feed the historical multi-source monitoring data set into the deep learning model to obtain the landslide prediction probability; Taking historical disaster event data as the true label and landslide prediction probability as the prediction label, based on the binary cross entropy loss probability, the landslide risk prediction loss function is constructed using the true label and the prediction label. The corresponding process has the following relationship: ； in, represents the landslide risk prediction loss function, represents the number of samples, represents the logarithmic function, Indicates n The true labels of samples, Represents the predicted label of the nth sample; Set the weight decay strategy and learning parameters of the Adam optimizer, and input the risk prediction loss function into the Adam optimizer for optimization training; After the training is completed, the trained deep learning model is obtained.

7. The disaster prevention and emergency treatment method for a barrier lake according to claim 6, characterized in that: The method of periodically monitoring the plurality of target slope mountains according to the preset mountain monitoring cycle and obtaining a plurality of periodic monitoring data specifically comprises the following steps: Acquire geological survey data of a plurality of target slopes and mountains; Acquire historical disaster data of a plurality of target slopes and mountains; According to a preset mountain monitoring cycle, periodic remote sensing detection is performed on the plurality of target slope mountains to obtain a plurality of remote sensing detection data; According to a preset mountain monitoring cycle, periodic mountain monitoring is performed on the plurality of target slope mountains to obtain a plurality of mountain monitoring data; The plurality of geological survey data, the plurality of historical disaster data, the plurality of remote sensing detection data and the plurality of mountain monitoring data are sorted out to generate a plurality of periodic monitoring data.

8. The disaster prevention and emergency treatment method for a barrier lake according to claim 7, characterized in that: The key monitoring of the risky bank slope and mountain to determine whether there are signs of barrier lake breach specifically includes the following steps: Conduct key remote sensing detection on the risky slopes and mountains, and continuously obtain key detection data; Conduct key mountain monitoring on the risky slopes and mountains, and continuously obtain key monitoring data; Based on the key detection data and the key monitoring data, a collapse analysis is conducted on the risky slope mountain to determine whether there are signs of a barrier lake collapse.

9. The disaster prevention and emergency treatment method for a barrier lake according to claim 8, characterized in that: When there is no sign of the barrier lake bursting, determining the disaster prevention area of ​​the risk bank slope mountain, and issuing a disaster prevention warning to the disaster prevention area specifically comprises the following steps: Generate disaster prevention instructions when there is no sign of the barrier lake bursting; Determine the disaster prevention area of ​​the risky bank slope mountain according to the disaster prevention instruction; Disaster prevention warnings to relocate or protect personnel and infrastructure in the disaster prevention areas and to improve flood control standards in downstream flooded areas; In the disaster prevention area, a disaster prevention warning is issued to lay out the second drainage channel in advance, block the formation of a dam, or reduce the formation height of the dam; When there are signs of a barrier lake bursting, determining the disaster emergency area of ​​the risk bank slope mountain, and conducting emergency treatment and warning for the disaster emergency area specifically include the following steps: Generate emergency response instructions when there are signs of a barrier lake breach; Determine the disaster emergency area of ​​the risky bank slope mountain according to the emergency handling instruction; In the disaster emergency area, emergency treatment warnings are issued for digging spillways, removing the dam or lowering its height, reinforcing the dam, opening emergency spillways or mechanically pumping out water; In the disaster emergency area, emergency response alerts are issued to organize the transfer of personnel and assets and the protection of important infrastructure.

10. A disaster prevention and emergency treatment system applied to a barrier lake, the system being applied to a disaster prevention and emergency treatment method applied to a barrier lake as claimed in any one of claims 1 to 9, characterized in that: The system includes a routine patrol monitoring and screening unit, a key monitoring and judgment unit, a disaster prevention alarm unit and an emergency handling alarm unit, wherein: The routine monitoring and screening unit is used to conduct routine monitoring and analysis of multiple target slopes and mountains, and screen and identify risky slopes and mountains with the risk of barrier lakes; A key monitoring and judging unit is used to conduct key monitoring on the risky bank slope and mountain to judge whether there are signs of barrier lake breach; A disaster prevention warning unit is used to determine the disaster prevention area of ​​the risk bank slope mountain when there is no sign of the barrier lake bursting, and to issue a disaster prevention warning for the disaster prevention area; The emergency response alarm unit is used to determine the disaster emergency area of ​​the risky slope mountain when there are signs of the barrier lake bursting, and to issue an emergency response alarm to the disaster emergency area.

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