Risk assessment method applied to geological disasters

Abstract

The invention discloses a risk assessment method applied to geological disasters, and relates to the technical field of geological disaster risk assessment, and the method comprises the steps: 6, judging a potential risk point, and outputting the potential risk point and a corresponding positioning coordinate together, thereby solving the technical problem, monitoring the water level value of each monitoring point in real time, and achieving the risk assessment of the geological disasters. And the water level is compared with a preset water level threshold value. If the water level of a certain monitoring point is higher than a preset threshold value, the monitoring point is marked as an early warning monitoring point, and the positioning coordinate of the monitoring point is output. The preset water level threshold value is determined by related workers according to actual requirements, abnormal water level changes can be found in time through real-time water level monitoring, it is ensured that early warning can be triggered in the early stage of a disaster, the response time is shortened, the disaster response efficiency is improved, potential disaster points can be automatically recognized through comparison with the preset threshold value, and the safety of the disaster is improved. Manual judgment errors are reduced, and the accuracy of the early warning system is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of geological disaster risk assessment, and specifically relates to a risk assessment method applied to geological disasters. BACKGROUND

[0002] Geological disasters (such as landslides, collapses, mudslides, etc.) are common disaster types in nature, which have the characteristics of suddenness, strong destructiveness, and large loss of life and property. In the work of geological disaster prevention, accurately assessing the water level changes in the region is an important means to predict and prevent geological disasters. Rainfall is one of the main factors that induce many geological disasters, especially landslides and mudslides. Rainfall infiltration can significantly increase the groundwater level, thereby reducing the effective stress and shear strength of the soil and increasing the weight of the sliding body, which may eventually lead to slope instability. Therefore, real-time or quasi-real-time monitoring of geological disaster-prone areas, especially monitoring of the key inducing indicator of groundwater level, and scientific risk assessment and early warning based on monitoring data are of great significance for disaster prevention and reduction, especially in mountainous and hilly areas. Changes in precipitation will directly affect the fluctuation of groundwater level, and the change of groundwater level is usually closely related to geological disasters such as landslides and mudslides.

[0003] However, traditional geological disaster risk assessment methods mostly rely on single geological data analysis, ignoring the dynamic changes in space and time, resulting in insufficient accuracy of disaster prediction. Existing technologies mostly use static analysis methods based on meteorological data and geological data, but these methods often fail to effectively consider the dynamic changes of key factors such as groundwater level and ground height, making it difficult to respond to disaster risks in real time. Based on this, a risk assessment method applied to geological disasters is proposed. SUMMARY

[0004] The purpose of the present application is to provide a risk assessment method applied to geological disasters to solve the problems mentioned in the background.

[0005] A risk assessment method applied to geological disasters: comprising: Step 1: obtaining the respective groundwater level values of each monitoring point in the monitoring area at a plurality of continuous monitoring time points in a plurality of rainfall events, and obtaining the respective positioning coordinates of each monitoring point; Step 2: analyzing the respective positioning coordinates of each monitoring point in the monitoring area to obtain the respective adjacent area circles of each monitoring point in the monitoring area, and obtaining the respective adjacent monitoring points of each monitoring point according to the respective adjacent area circles of each monitoring point; Step three: analyzing the underground water level values of each monitoring point and its respective adjacent monitoring points at the continuous monitoring time points in multiple rainfall, obtaining the water level following coefficient between each monitoring point and its respective adjacent monitoring points according to the analysis result; Step four: analyzing the water level following coefficient between each monitoring point and its respective adjacent monitoring points, and determining the synchronous monitoring points corresponding to each monitoring point; Step five: comparing and analyzing the real-time water level values of each monitoring point with the preset water level threshold, marking the early warning monitoring points, and outputting the early warning monitoring points and their corresponding positioning coordinates; Step six: determining the potential risk points, and outputting the potential risk points and their corresponding positioning coordinates.

[0006] As a further scheme of the present application: the specific way of obtaining the adjacent area circle corresponding to each monitoring point in the to-be-monitored area is: randomly selecting one from the monitoring points as a target monitoring point, obtaining the interval distance between the target monitoring point and other monitoring points according to the positioning coordinates corresponding to each monitoring point, obtaining the mean value of each interval distance, and taking the target monitoring point as the center and the mean value of each interval distance as the radius to draw a circle, which is taken as the adjacent area circle corresponding to the target monitoring point, and the same way of obtaining the adjacent area circle corresponding to the target monitoring point is adopted to analyze the positioning coordinates corresponding to each of the remaining monitoring points, so that the adjacent area circles corresponding to each monitoring point in the to-be-monitored area are obtained.

[0007] As a further scheme of the present application: the specific way of obtaining the adjacent monitoring points corresponding to each monitoring point is: taking each monitoring point located in the adjacent area circle of the target monitoring point as the adjacent monitoring point corresponding to the target monitoring point, and binding it with the target monitoring point, and the same way is adopted to analyze the remaining monitoring points, so that the adjacent monitoring points corresponding to each monitoring point are obtained.

[0008] As a further scheme of the present application: the specific way of obtaining the water level following coefficient between each monitoring point and its respective adjacent monitoring points is: S1: obtaining the target monitoring point from step two; S2: randomly selecting one from the multiple rainfall as a target rainfall, obtaining the underground water level values of the target monitoring point and its respective adjacent monitoring points at the continuous monitoring time points corresponding to each monitoring point in the target rainfall; A two-dimensional coordinate system is drawn, with multiple monitoring time points as the horizontal axis and the groundwater level values ​​corresponding to the target monitoring point and its adjacent monitoring points at multiple consecutive monitoring time points as the vertical axis. This yields the groundwater level data points corresponding to the target monitoring point and its adjacent monitoring points at multiple consecutive monitoring time points. Multiple water level data points corresponding to the same monitoring point are connected to obtain the water level transformation curves corresponding to the target monitoring point and its adjacent monitoring points. For a single water level transformation curve, the line connecting every two adjacent water level data points on this water level transformation curve is marked as a stage line. The slope of each stage line is obtained based on the coordinates of the two water level data points that make up each stage line. The number A of positive and negative values ​​in each slope is then recorded. 正 1 and A 负 1. Place A 正 1 and A 负 The ratio between 1 and 1 is used as the transformation coefficient corresponding to this water level transformation curve. By analyzing other water level transformation curves in the same way, the transformation coefficients corresponding to the water level transformation curves of the target monitoring point and its adjacent monitoring points can be obtained respectively. Using the same method as in step S2, the groundwater level values ​​corresponding to the target monitoring point and its corresponding adjacent monitoring points at multiple consecutive monitoring time points in the remaining rainfall events are analyzed. Then, the transformation coefficients corresponding to the water level transformation curves of the target monitoring point and its corresponding adjacent monitoring points in multiple rainfall events are obtained. The transformation coefficients corresponding to the water level transformation curves of each adjacent monitoring point in multiple rainfall events are analyzed to obtain the water level follow-up coefficients between the target monitoring point and its corresponding adjacent monitoring points. Using the same method as steps S1-S2, the groundwater level values ​​corresponding to the remaining multiple monitoring points and their corresponding adjacent monitoring points at multiple consecutive monitoring time points in the remaining rainfall events are analyzed, thereby obtaining the water level follow-up coefficient between each monitoring point and its corresponding adjacent monitoring points.

[0009] As a further aspect of the present invention, the specific method for obtaining the water level follow-up coefficient between the target monitoring point and each of its corresponding adjacent monitoring points is as follows: From the transformation coefficients corresponding to the water level transformation curves of the target monitoring point and its corresponding adjacent monitoring points in multiple rainfall events, the average of the maximum and minimum values ​​of the transformation coefficients of a single monitoring point in multiple rainfall events is obtained as the calculated transformation coefficient of the corresponding monitoring point. Then, the calculated transformation coefficients corresponding to each target monitoring point and its corresponding adjacent monitoring points are obtained. The absolute value of the difference between the calculated transformation coefficients of each adjacent monitoring point and the target monitoring point is obtained as the water level follow-up coefficient between the target monitoring point and its corresponding adjacent monitoring points.

[0010] As a further aspect of the present invention, the specific method for determining the synchronous monitoring points corresponding to each monitoring point is as follows: From step three, obtain the water level follow-up coefficients between the target monitoring point and each of its corresponding adjacent monitoring points. Use the average value of each water level follow-up coefficient as the water level follow-up threshold. Mark adjacent monitoring points whose water level follow-up coefficients are less than the water level follow-up threshold as synchronous monitoring points of the target monitoring point, and otherwise, do not process them. Use the same analysis method to analyze the water level follow-up coefficients between each of the remaining monitoring points and each of its corresponding adjacent monitoring points, and then obtain the synchronous monitoring points corresponding to each monitoring point.

[0011] As a further aspect of the present invention, the specific method for marking early warning monitoring points is as follows: The real-time water level values ​​corresponding to each monitoring point are acquired and compared with the preset water level threshold. Monitoring points with real-time water level values ​​greater than the preset water level threshold are marked as early warning monitoring points, and the early warning monitoring points and their corresponding positioning coordinates are output together.

[0012] As a further aspect of the present invention, the specific method for determining potential risk points is as follows: Obtain the synchronous monitoring points corresponding to each early warning monitoring point, output the synchronous monitoring points that are not early warning monitoring points as potential risk points, and output the location coordinates corresponding to the potential risk points.

[0013] As a further aspect of the present invention: monitoring points located on the boundary line of the adjacent area circle of the target monitoring point are also regarded as adjacent monitoring points of the target monitoring point.

[0014] Compared with the prior art, the beneficial effects of the present invention are: (1) This invention analyzes the location coordinates of each monitoring point, calculates the distance between monitoring points, and then identifies the regional circles formed by adjacent monitoring points. The specific method is to start from any monitoring point, calculate its average distance from other monitoring points, and draw a circular area with the average distance as the radius. The monitoring points in this area are identified as the adjacent monitoring points of the target monitoring point. The average distance circle method is used to define the spatial adjacency relationship. This avoids the deviation that may occur when the fixed radius method or the nearest neighbor method is unevenly distributed. By calculating the average distance from all other points, the adjacent regional circle of each monitoring point can dynamically adapt to the overall density of the monitoring points in the area. By defining the adjacent regional circle, the spatial data is transformed into a monitoring area with practical significance, providing a clear spatial structure for subsequent data analysis and relationship analysis between monitoring points. The accurate adjacent monitoring point identification mechanism makes the correlation between each monitoring point and the surrounding area clearer, providing useful geographical and geological information for subsequent analysis. This is achieved by introducing the concept of regional circles. (2) This invention draws water level change curves between a target monitoring point and its adjacent monitoring points by selecting data from specific time points during multiple rainfall periods. By calculating the slope of each stage line in the water level change curve, the trend of water level change is analyzed. The slope of the stage line represents the speed and magnitude of water level change. By calculating the ratio of positive to negative slopes, the water level change coefficient is obtained. Then, based on the change coefficient of each rainfall, the average of the maximum and minimum values ​​of each monitoring point and its adjacent monitoring points is obtained as the final water level follow-up coefficient. By calculating the water level follow-up coefficient, the dynamic relationship between water level change and monitoring points can be revealed, thereby more accurately reflecting the impact of water level change on other monitoring points in the area. By calculating the slope of the stage line and the change coefficient, a quantitative indicator is provided for analyzing the speed of water level change, further improving the accuracy of disaster assessment. The dynamic water level follow-up coefficient can provide a basis for the linkage between different monitoring points in the area. (3) In this invention, by analyzing the water level follow-up coefficient of each monitoring point, it is determined which adjacent monitoring points have water level changes that are highly consistent with the target monitoring point. The mean value of the water level follow-up coefficient is used as a threshold. Adjacent monitoring points below this threshold are marked as synchronous monitoring points. After determining the synchronous monitoring points, water level changes in the same area can be monitored more effectively. (4) This invention monitors the water level at each monitoring point in real time and compares it with a preset water level threshold. If the water level at a monitoring point is higher than the preset threshold, the monitoring point is marked as an early warning monitoring point, and its location coordinates are output. The preset water level threshold is determined by relevant personnel according to actual needs. Real-time water level monitoring can promptly detect abnormal water level changes, ensuring that early warnings can be triggered in the early stages of a disaster, reducing reaction time, improving disaster response efficiency, and automatically identifying potential disaster points by comparing with the preset threshold, reducing human judgment errors, and improving the accuracy of the early warning system. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the method framework structure of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1: Please refer to Figure 1 This application provides a risk assessment method for geological hazards, comprising the following steps: Step 1: Set up multiple monitoring points in the area to be monitored, and acquire historical monitoring data for each monitoring point in the area during multiple rainfall events at various consecutive monitoring time points, while obtaining the location coordinates of each monitoring point. The historical monitoring data specifically refers to the groundwater level values ​​at each monitoring point; It should be noted that the time intervals between multiple consecutive monitoring points are all equal; the groundwater level values ​​at each monitoring point are monitored and recorded using groundwater level gauges. Geological hazards, especially rainfall-induced landslides, are closely related to changes in groundwater levels. Continuous, multi-point historical water level and ground elevation data are fundamental for establishing risk assessment models and analyzing regional hydrological responses. This is achieved by deploying multiple monitoring points within the monitored area and using groundwater level gauges to monitor the groundwater level and ground elevation at each point. Data is recorded at multiple time points with equal intervals during consecutive rainfall events. The location information (latitude and longitude) of each monitoring point is also collected, providing basic data for subsequent spatial analysis. This ensures a comprehensive understanding of groundwater level and ground elevation changes within the monitored area. The acquisition of location coordinates provides accurate basic data for subsequent spatial relationship analysis, guaranteeing the accuracy of spatial data. The real-time and continuous nature of the monitoring data ensures dynamic tracking of water level changes, helping to promptly identify potential geological hazard risks and providing high-quality, high spatiotemporal resolution input data for subsequent spatial analysis and dynamic correlation analysis.

[0018] Step Two: Analyze the location coordinates of each monitoring point within the monitoring area to obtain the distance between each monitoring point and other monitoring points. Based on multiple distances, analyze and obtain the adjacent area circles corresponding to each monitoring point within the monitoring area. Then, obtain the adjacent monitoring points corresponding to each monitoring point based on the adjacent area circles. The specific method is as follows: One monitoring point is randomly selected from all monitoring points as the target monitoring point. Based on the positioning coordinates of each monitoring point, the distance between the target monitoring point and other monitoring points is obtained, and the average value between each distance is obtained. At the same time, a circle is drawn with the target monitoring point as the center and the average value between each distance as the radius R. This circle is used as the adjacent area circle corresponding to the target monitoring point. Each monitoring point located within the adjacent area circle of the target monitoring point is considered as the adjacent monitoring point of the target monitoring point (monitoring points located on the boundary line of the adjacent area circle of the target monitoring point are also considered as the adjacent monitoring points of the target monitoring point). These are then bound to the target monitoring point. The same method is used to analyze the remaining monitoring points to obtain the adjacent monitoring points corresponding to each monitoring point. By analyzing the positioning coordinates of each monitoring point within the monitoring area in the same way as obtaining the adjacent area circle corresponding to the target monitoring point, the adjacent area circle corresponding to each monitoring point within the monitoring area can be obtained. By analyzing the location coordinates of each monitoring point and calculating the distances between them, adjacent monitoring points are identified, forming regional circles. Specifically, starting from any monitoring point, the average distance to other monitoring points is calculated. A circular area is drawn with this average distance as the radius. Monitoring points within this area are considered adjacent to the target monitoring point. The average distance circle method defines spatial adjacency relationships. This avoids the biases that may occur with the fixed radius method or the nearest neighbor method when monitoring points are unevenly distributed. By calculating the average distance to all other points, the adjacent regional circle of each monitoring point can dynamically adapt to the overall density of monitoring points within the area. By defining the adjacent regional circle, spatial data is transformed into a meaningful monitoring area, providing a clear spatial structure for subsequent data analysis and relationship analysis between monitoring points. The precise adjacent monitoring point identification mechanism makes the correlation between each monitoring point and its surrounding area clearer, providing useful geographical and geological information for subsequent analysis. By introducing the concept of regional circles, the spatial layout between monitoring points is optimized, providing the necessary spatial structure for comprehensive risk assessment. The spatial influence range between monitoring points is scientifically and rationally delineated, defining key related objects for subsequent water level dynamic analysis.

[0019] Step 3: Analyze the groundwater level values ​​at multiple consecutive monitoring time points during multiple rainfall events for each monitoring point and its adjacent monitoring points. Based on the analysis results, obtain the water level variation coefficient between each monitoring point and its corresponding adjacent monitoring points. The specific method is as follows: S1: Obtain the target monitoring point from step two; S2: Randomly select one of the multiple rainfall events as the target rainfall event; Obtain the groundwater level values ​​at multiple consecutive monitoring time points for the target monitoring point and its corresponding adjacent monitoring points during the target rainfall event; A two-dimensional coordinate system is drawn, with multiple monitoring time points as the horizontal axis and the groundwater level values ​​corresponding to the target monitoring point and its corresponding adjacent monitoring points at multiple consecutive monitoring time points as the vertical axis. The groundwater level data points corresponding to the target monitoring point and its corresponding adjacent monitoring points at multiple consecutive monitoring time points are obtained. Multiple water level data points corresponding to the same monitoring point are connected to obtain the water level transformation curves corresponding to the target monitoring point and its corresponding adjacent monitoring points. For a single water level change curve, the line connecting each two adjacent water level data points on this water level change is marked as a stage line, and the slope Ka corresponding to each stage line is obtained according to the coordinates of the two water level data points that make up each stage line. Where a represents different stage lines, a = 1, 2, ..., b, where b represents the number of stage lines, b is a positive integer, and b is equal to the total number of monitoring time points c minus 1; The number of positive and negative values ​​in the slope Ka are respectively labeled as A. 正 1 and A 负 1. Place A 正 1 and A 负 The ratio between 1 and 1 is used as the transformation coefficient corresponding to this water level transformation curve; The specific method for obtaining the slope Ka corresponding to each stage line is as follows: The ratio of the absolute value of the difference between the ordinate of the next water level data point and the ordinate of the previous water level data point on each stage line to the absolute value of the difference between their corresponding abscissas, i.e., the monitoring time points, is taken as the slope Ka of each stage line. It should be noted that the first endpoint on the stage line refers to the water level data point closer to the origin among the two data points that make up the stage line, while the second endpoint refers to the water level data point located at the right endpoint of the stage line. By analyzing other water level transformation curves in the same way, the transformation coefficients B1i corresponding to the water level transformation curves of the target monitoring point and its various adjacent monitoring points can be obtained, where i represents any one of the water level transformation curves of the target monitoring point and its various adjacent monitoring points. Using the same method as in step S2, the groundwater level values ​​corresponding to the target monitoring point and its corresponding adjacent monitoring points at multiple consecutive monitoring time points in the remaining rainfall events are analyzed, thereby obtaining the transformation coefficients Bji corresponding to the water level transformation curves of the target monitoring point and its corresponding adjacent monitoring points in multiple rainfall events, where j represents different rainfall events. From the transformation coefficients Bji corresponding to the water level transformation curves of the target monitoring point and its corresponding adjacent monitoring points in multiple rainfalls, the average of the maximum and minimum values ​​of the transformation coefficients of a single monitoring point in multiple rainfalls is obtained as the calculated transformation coefficient of the corresponding monitoring point. Then, the calculated transformation coefficients corresponding to each target monitoring point and its corresponding adjacent monitoring points are obtained. The absolute value of the difference between the calculated transformation coefficients of each adjacent monitoring point and the target point is obtained as the water level follow-up coefficient between the target monitoring point and its corresponding adjacent monitoring points. Using the same method as steps S1-S2, the groundwater level values ​​corresponding to the remaining multiple monitoring points and their corresponding adjacent monitoring points at multiple consecutive monitoring time points in each of the remaining rainfall events are analyzed, thereby obtaining the water level follow-up coefficient between each monitoring point and its corresponding adjacent monitoring points. By selecting data from specific time points across multiple rainfall periods, water level transformation curves are plotted between the target monitoring point and its adjacent monitoring points. The trend of water level change is analyzed by calculating the slope of each stage line in the water level transformation curve. The slope of the stage line represents the speed and magnitude of water level change. The water level transformation coefficient is obtained by calculating the ratio of positive to negative slopes. Next, based on the transformation coefficient for each rainfall period, the average of the maximum and minimum values ​​for each monitoring point and its adjacent monitoring points is calculated as the final water level follow-up coefficient. The calculation of the water level follow-up coefficient reveals the dynamic relationship between water level changes and monitoring points, thus more accurately reflecting the impact of water level changes on other monitoring points in the region. By calculating the slope of the stage lines and the transformation coefficient, a quantitative indicator is provided for analyzing the speed of water level changes, further improving the accuracy of disaster assessment. The dynamic water level follow-up coefficient can provide a basis for the linkage between different monitoring points in the region, helping to identify potential disaster development trends in advance.

[0020] Step 4: Analyze the water level follow-up coefficient between each monitoring point and its corresponding adjacent monitoring points, and determine the synchronous monitoring points corresponding to each monitoring point; the specific method is as follows: From step three, obtain the water level following coefficients between the target monitoring point and each of its corresponding adjacent monitoring points. Use the average value of each water level following coefficient as the water level following threshold. Mark adjacent monitoring points whose water level following coefficients are less than the water level following threshold as synchronous monitoring points of the target monitoring point. Use the average value of each water level following coefficient as the water level following threshold. Do not process adjacent monitoring points whose water level following coefficients are greater than or equal to the water level following threshold. The same analytical method was used to analyze the water level follow-up coefficients between each of the remaining monitoring points and their respective adjacent monitoring points, thereby obtaining the synchronous monitoring points corresponding to each monitoring point. By analyzing the water level follow-up coefficients at each monitoring point, it is determined which adjacent monitoring points exhibit water level changes highly consistent with the target monitoring point. The average water level follow-up coefficient is used as a threshold; adjacent monitoring points below this threshold are marked as synchronous monitoring points. This step calculates the water level follow-up coefficients of each monitoring point and its adjacent monitoring points, analyzes their synchronicity, and ultimately determines which monitoring points have consistent change trends. This allows for further refinement of the monitoring network, clarifying which monitoring points have similar water level change trends within the same time period. This is crucial for disaster prediction and early warning. Dynamically adjusting the water level follow-up coefficient threshold helps address different rainfall amounts and regional differences, enhancing the adaptability and flexibility of the scheme. After identifying synchronous monitoring points, water level changes in the same area can be monitored more effectively, reducing data analysis errors caused by unclear relationships between monitoring points.

[0021] Step 5: Obtain the real-time water level values ​​corresponding to each monitoring point and compare them with the preset water level threshold. Mark the monitoring points with real-time water level values ​​greater than the preset water level threshold as early warning monitoring points. Output the early warning monitoring points and their corresponding positioning coordinates. It should be noted that the specific value of the preset water level threshold shall be determined by relevant personnel according to actual needs. By monitoring the water level at each monitoring point in real time and comparing it with preset water level thresholds, the system marks a monitoring point as an early warning monitoring point and outputs its location coordinates if the water level at a certain monitoring point exceeds the preset threshold. The preset water level thresholds are determined by relevant personnel based on actual needs. Real-time water level monitoring can promptly detect abnormal water level changes, ensuring that early warnings are triggered in the early stages of a disaster, reducing reaction time and improving disaster response efficiency. By comparing the water level with the preset thresholds, the system can automatically identify potential disaster points, reducing human judgment errors and improving the accuracy of the early warning system. The combination of real-time data acquisition and early warning functions enables the system to dynamically respond under changing environmental conditions, improving disaster response capabilities.

[0022] Step 6: Obtain the synchronous monitoring points corresponding to each early warning monitoring point, output the synchronous monitoring points that are not early warning monitoring points as potential risk points, and output the location coordinates corresponding to the potential risk points; By identifying the synchronous monitoring points corresponding to each early warning monitoring point, synchronous monitoring points that are not part of the early warning monitoring points are marked as potential risk points. Finally, the system outputs the location coordinates of these potential risk points so that relevant personnel can take appropriate disaster prevention measures. Accurate identification of potential risk points improves the accuracy and spatial coverage of disaster risk assessment. Through the location output of potential risk points, relevant departments can take timely prevention and control measures to reduce losses caused by disasters.

[0023] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A risk assessment method applied to geological disasters, characterized by, The application relates to a method for monitoring a potential risk point in a monitoring area. Step one: obtaining the underground water level values of each monitoring point in the monitoring area at continuous monitoring time points in multiple rainfalls, and obtaining the positioning coordinates of each monitoring point; Step two: analyzing the positioning coordinates of each monitoring point in the monitoring area to obtain the adjacent area circle of each monitoring point, and obtaining the adjacent monitoring point of each monitoring point according to the adjacent area circle of each monitoring point; Step three: analyzing the underground water level values of each monitoring point and each adjacent monitoring point of the monitoring point at continuous monitoring time points in multiple rainfalls, and obtaining the water level following coefficient between each monitoring point and each adjacent monitoring point of the monitoring point according to the analysis result; Step four: analyzing the water level following coefficient between each monitoring point and each adjacent monitoring point of the monitoring point, and determining the synchronous monitoring point of each monitoring point; Step five: comparing and analyzing the real-time water level value of each monitoring point with a preset water level threshold, marking the early warning monitoring point, and outputting the early warning monitoring point and the corresponding positioning coordinates; Step six: determining the potential risk point, and outputting the potential risk point and the corresponding positioning coordinates.

2. The risk assessment method for geological disasters according to claim 1, characterized in that, The specific way of obtaining the adjacent area circle of each monitoring point in the monitoring area is as follows: randomly selecting one from the monitoring points as a target monitoring point; obtaining the interval distance between the target monitoring point and other monitoring points according to the positioning coordinates of each monitoring point, obtaining the mean value of each interval distance, and taking the mean value of each interval distance as the radius to draw a circle with the target monitoring point as the center, which is taken as the adjacent area circle of the target monitoring point; the positioning coordinates of the remaining monitoring points are analyzed in the same way as obtaining the adjacent area circle of the target monitoring point, so that the adjacent area circle of each monitoring point in the monitoring area is obtained. The specific way of obtaining the adjacent monitoring point of each monitoring point is as follows: taking each monitoring point in the adjacent area circle of the target monitoring point as the adjacent monitoring point of the target monitoring point, and binding the target monitoring point and the adjacent monitoring point; the remaining monitoring points are analyzed in the same way, so that the adjacent monitoring point of each monitoring point is obtained.

3. The risk assessment method for geological disasters according to claim 2, characterized in that, The specific way of obtaining the water level following coefficient between each monitoring point and each adjacent monitoring point of the monitoring point is as follows: S1: obtaining the target monitoring point from step two; 4. The risk assessment method for geological disasters according to claim 2, characterized in that, S2: randomly selecting one from multiple rainfalls as a target rainfall, and obtaining the underground water level values of the target monitoring point and each adjacent monitoring point of the target monitoring point at continuous monitoring time points in the target rainfall; S3: obtaining the water level following coefficient between the target monitoring point and each adjacent monitoring point of the target monitoring point according to the underground water level values of the target monitoring point and each adjacent monitoring point of the target monitoring point at continuous monitoring time points in the target rainfall; and S4: obtaining the water level following coefficient between each monitoring point and each adjacent monitoring point of the monitoring point according to the water level following coefficients obtained in steps S1-S3. A two-dimensional coordinate system is drawn, with multiple monitoring time points as the horizontal axis and the groundwater level values ​​corresponding to the target monitoring point and its adjacent monitoring points at multiple consecutive monitoring time points as the vertical axis. This yields the groundwater level data points corresponding to the target monitoring point and its adjacent monitoring points at multiple consecutive monitoring time points. Multiple water level data points corresponding to the same monitoring point are connected to obtain the water level transformation curves corresponding to the target monitoring point and its adjacent monitoring points. For a single water level transformation curve, the line connecting every two adjacent water level data points on this water level transformation curve is marked as a stage line. The slope of each stage line is obtained based on the coordinates of the two water level data points that make up each stage line. The number A of positive and negative values ​​in each slope is then recorded. 正 1 and A 负 1. Place A 正 1 and A 负 The ratio between 1 and 1 is used as the transformation coefficient corresponding to this water level transformation curve. By analyzing other water level transformation curves in the same way, the transformation coefficients corresponding to the water level transformation curves of the target monitoring point and its adjacent monitoring points can be obtained respectively. In the same way as step S2, the underground water level values of the target monitoring point and each corresponding adjacent monitoring point at the continuous monitoring time points in the remaining rainfall are analyzed, and then the transformation coefficients of the water level transformation curves of the target monitoring point and each corresponding adjacent monitoring point in the multiple rainfall are obtained, and the water level following coefficients between the target monitoring point and each corresponding adjacent monitoring point are obtained by analyzing the transformation coefficients of the water level transformation curves of each adjacent monitoring point in the multiple rainfall. In the same way as steps S1-S2, the underground water level values of the remaining monitoring points and each corresponding adjacent monitoring point at the continuous monitoring time points in the remaining rainfall are analyzed, and then the water level following coefficients between each monitoring point and each corresponding adjacent monitoring point are obtained.

5. The risk assessment method for geological disasters according to claim 4, characterized in that, The specific way of obtaining the water level following coefficients between the target monitoring point and each corresponding adjacent monitoring point is as follows: The average of the maximum value and the minimum value of the transformation coefficients of a single monitoring point in the multiple rainfall is obtained as the calculation transformation coefficient of the corresponding monitoring point from the transformation coefficients of the water level transformation curves of the target monitoring point and each corresponding adjacent monitoring point in the multiple rainfall, and then the calculation transformation coefficients of each target monitoring point and each corresponding adjacent monitoring point are obtained, and the absolute value of the difference between the calculation transformation coefficients of each adjacent monitoring point and the target monitoring point is obtained as the water level following coefficient between the target monitoring point and each corresponding adjacent monitoring point.

6. The risk assessment method for geological disasters according to claim 5, characterized in that, The specific way of determining the synchronous monitoring point corresponding to each monitoring point is as follows: The average of the water level following coefficients is taken as the water level following threshold value from the water level following coefficients between the target monitoring point and each corresponding adjacent monitoring point obtained in step three, and the adjacent monitoring points with water level following coefficients less than the water level following threshold value are marked as the synchronous monitoring points of the target monitoring point, otherwise, no processing is performed; the water level following coefficients between the remaining monitoring points and each corresponding adjacent monitoring point are analyzed in the same way, and then the synchronous monitoring points corresponding to each monitoring point are obtained.

7. The risk assessment method for geological disasters according to claim 6, characterized in that, The specific way of marking the early warning monitoring point is as follows: The real-time water level values corresponding to each monitoring point are obtained, and compared with the preset water level threshold value, and the monitoring points with real-time water level values greater than the preset water level threshold value are marked as early warning monitoring points, and the early warning monitoring points and the corresponding positioning coordinates are output together. 8.The method for risk assessment of geological disasters according to claim 7, characterized in that, The specific way of determining the potential risk point is as follows: The synchronous monitoring points corresponding to each early warning monitoring point are obtained, and the synchronous monitoring points that are not early warning monitoring points are taken as potential risk points and output, and the positioning coordinates corresponding to the potential risk points are output. 9.The risk assessment method for geological disasters according to claim 2, wherein, The monitoring points located on the boundary line of the adjacent area of the target monitoring point are also taken as the adjacent monitoring points corresponding to the target monitoring point.

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