Prediction method for predicting surge disaster caused by landslide based on climbing height

Abstract

The invention relates to the technical field of geological disaster detection, in particular to a prediction method for predicting surge disasters caused by landslide based on climbing height, comprising the following steps: determining a river bank of a landslide occurrence area, determining a point distribution starting point, and recording as P1; taking P1 as a starting point, and uniformly and upwards arranging pressure monitoring points along the normal direction of the slope bank; when the landslide occurs, detecting the pressure data of the slope bank; judging pressure data of the slope bank and detecting whether the number of distribution points is greater than the number of the points with the pressure data, and if the number of the distribution points is equal to the number of the points with the pressure data, increasing distribution points and repeating the steps S2-S4; according to the number change of the points with the pressure data, the maximum climbing length change rule of the landslide on the opposite bank side is obtained; according to the method, the points are uniformly distributed on the opposite bank side where the landslide occurs, the number change of the points with pressure data is observed, and the maximum climbing height of the landslide is judged according to the number change, so that the detection accuracy of the landslide disaster is improved, and casualties and property loss caused by the landslide disaster are greatly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of geological disaster detection, and in particular to a method for predicting surge disasters caused by landslides based on climbing height. Background Art

[0002] Landslide is a geological phenomenon in which the rock mass on a slope slides along a continuous shear failure surface. The mechanism of landslide is that the shear stress on a certain sliding surface exceeds the shear strength of the surface. The surge disaster caused by landslide not only seriously threatens the safety of shipping, but also destroys hydraulic structures such as docks and dams and causes loss of life and property of residents along the coast.

[0003] When a landslide occurs and enters the water, it often generates huge surge waves. When the surge waves spread to the other side of the river or the dam, the height of the surge waves can even reach tens of meters, causing far more damage than the initial formation and propagation stages of the landslide. Therefore, accurately predicting the scope of surge waves caused by landslides is crucial to preventing landslide disasters and reducing economic losses. Summary of the invention

[0004] The technical problem to be solved by the present invention is: in order to solve the problem that the existing prediction methods have low detection accuracy and increase the risk of casualties and property losses caused by landslide disasters, a prediction method for predicting surge disasters caused by landslides based on climbing height is provided.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a prediction method for predicting surge disasters caused by landslides based on the climbing height, and the specific operation includes the following steps:

[0006] S1. First, confirm the river bank in the area where the landslide occurs. The river bank point in this area is recorded as P0. Then confirm the starting point of the distribution point on the opposite bank of the landslide and record it as P1.

[0007] S2, take P1 as the starting point, and evenly arrange pressure monitoring points upward along the normal direction of the slope, with the direction from P0 to P1 as the X-axis, the water depth direction as the Z-axis, the perpendicular to the XZ plane as the Y-axis, the slope angle as α, and the number of points arranged upward along the slope in the XZ plane is recorded as P1, P2...P n , and the distance between two adjacent monitoring points in the XZ plane is recorded as r, and the number of points in the XZ plane and the number of points in the array along the Y axis are recorded as P 1y , P 2y ...P ny , and the distance between two adjacent monitoring points along the X direction in the XY plane is recorded as r·COSα;

[0008] S3. When a landslide occurs, the pressure data of the slope is detected;

[0009] S4, judging whether the number of points is greater than the number of points with pressure data, if the number of points is equal to the number of points with pressure data, the points should be increased and S2-S4 should be repeated;

[0010] S5. According to the change in the number of points with pressure data, the change law of the maximum climbing length of the landslide on the opposite bank is obtained;

[0011] S6, then use the slope of the opposite bank and the Pythagorean theorem to convert the maximum climbing length to obtain the maximum climbing height of the landslide on the opposite bank;

[0012] S7, judging the minimum safe altitude of the landslide prone area according to the maximum climbing height of the landslide obtained in step S6, and taking preventive measures for the areas susceptible to landslides. Compared with the prior art, the prediction method of this scheme evenly distributes points on the opposite bank of the landslide, observes the change in the number of points with pressure data, and uses this to determine the maximum climbing height of the landslide, thereby improving the detection accuracy of landslide disasters and greatly reducing the casualties and property losses caused by landslide disasters.

[0013] In some preferred embodiments, in step S1, the intersection of the midpoint of the river bank in the landslide occurrence area with the water surface is recorded as P0, and the vertical plane passing through point P0 is used as the reference plane. An external normal is established from the midpoint to the opposite bank of the river, and the intersection with the opposite bank is recorded as P1.

[0014] In some preferred embodiments, in step S4, the number of monitoring points that can detect data changes with time. If the number of points is greater than the number of climbing height detection points, that is, when the number of pressure data points is the largest, the number of points is greater than the number of data detection points, then the detection process is determined to be valid and the next step is performed;

[0015] When the number of points is equal to the number of detection points with data, it is impossible to accurately determine whether this point is the farthest point that can be reached by climbing the landslide, so the data cannot be accurately calculated. Therefore, it is recorded as an invalid detection process, and the number of points should be increased and steps S2-S4 should be repeated.

[0016] In some preferred embodiments, in step S5, when the number of pressure data points is the largest during the effective detection process, the point at which the pressure change is detected last is recorded as P n According to the interval distance of monitoring points, the maximum climbing length d of the landslide on the opposite bank can be calculated as: d = (n-1)r.

[0017] In some preferred implementations, in step S6, the angle of the slope is obtained by consulting the data as α, and the calculation formula for the maximum climbing height h is: h=(n-1)r×sinα.

[0018] The beneficial effect of the present invention is that when the prediction method of the present invention for predicting surge disasters caused by landslides based on climbing height is used, points are evenly distributed on the opposite bank side where the landslide occurs, the change in the number of points with pressure data is observed, and the maximum climbing height of the landslide is determined based on this, thereby improving the detection accuracy of landslide disasters, greatly reducing casualties and property losses caused by landslide disasters, and avoiding the problem of low detection accuracy of existing prediction methods and increased risk of casualties and property losses caused by landslide disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0020] Figure 1 The figure is a schematic diagram of the process of the maximum height detection method of the landslide climbing on the opposite bank side of the present invention;

[0021] Figure 2 The schematic diagram of the point arrangement operation of the present invention using the method to detect the maximum climbing height of the landslide Figure 1 ;

[0022] Figure 3 The schematic diagram of the point arrangement operation of the present invention using the method to detect the maximum climbing height of the landslide Figure 2 ;

[0023] Figure 4 The schematic diagram of the point arrangement operation of the present invention using the method to detect the maximum climbing height of the landslide Figure 3 ;

[0024] Figure 5 It is a schematic diagram of the process of the landslide reaching the other side and starting to climb and the pressure detection point acting in the actual simulation process of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below in conjunction with embodiments:

[0026] The present invention is not limited to the following specific embodiments. A person skilled in the art can implement the present invention in various other specific embodiments according to the contents disclosed in the present invention, or any simple changes or modifications made to the design structure and ideas of the present invention fall within the protection scope of the present invention. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0027] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0028] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0029] like Figure 1-5 As shown, a prediction method for predicting surge disasters caused by landslides based on climbing height includes the following steps:

[0030] S1. First, confirm the river bank in the area where the landslide occurs, and confirm the starting point of the deployment on the opposite bank of the landslide and record it as P1. The intersection of the midpoint of the river bank in the area where the landslide occurs and the water surface is recorded as P0. The vertical plane passing through P0 is used as the reference plane. From the midpoint, an external normal is established to the opposite bank of the river, and the intersection with the opposite bank is recorded as P1. S2. Take P1 as the starting point, and evenly arrange pressure monitoring points upward along the normal of the slope bank, with the direction from P0 to P1 as the X-axis, the water depth direction as the Z-axis, the perpendicular to the XZ plane as the Y-axis, the slope bank angle as α, and the number of points arranged upward along the slope bank in the XZ plane is recorded as P1, P2...P n , and the distance between two adjacent monitoring points in the XZ plane is recorded as r, and the number of points in the XZ plane and the number of points in the array along the Y axis are recorded as P 1y , P 2y ...P ny , and the distance between two adjacent monitoring points along the X direction in the XY plane is recorded as r·COSα;

[0031] S3. When a landslide occurs, the pressure data of the slope is detected;

[0032] S4. Determine whether the number of points is greater than the number of points with pressure data. The number of monitoring points that can detect data changes with time. If the number of points is greater than the number of climbing height detection points, that is, when the number of pressure data points is the largest, the number of points is greater than the number of detection points with data, then the detection process is determined to be valid and the next step is performed;

[0033] When the number of points is equal to the number of detection points with data, it is impossible to accurately determine whether this point is the farthest point that can be reached by climbing the landslide, so the data cannot be accurately calculated. Therefore, it is recorded as an invalid detection process, and the number of points should be increased and steps S2-S4 should be repeated;

[0034] S5. According to the change in the number of points with pressure data, the maximum climbing length change law of the landslide on the opposite bank is obtained, that is, in the effective detection process, when the number of pressure data points is the largest, the point where the pressure change is detected at the last climbing height detection point is recorded as P. n According to the interval between monitoring points, the maximum climbing length d of the landslide on the opposite bank can be calculated as follows: d = (n-1)r, where the unit of d can be set to cm, and n is the number of arrangement points;

[0035] S6. Then use the slope of the opposite bank and the Pythagorean theorem to convert the maximum climbing length to obtain the maximum climbing height of the landslide on the opposite bank. By consulting the data, the angle of the slope is α, and the calculation formula for the maximum climbing height h is: h = (n-1)r × sinα, where the unit of h can be set to cm, n is the number of layout points, and r is the distance between two adjacent monitoring points P. n and P n+1 The distance between the two, the unit of r can be set to cm, but it is not limited to cm. Select the appropriate unit according to the experiment and engineering size;

[0036] S7. Determine the minimum safe altitude of the landslide prone area according to the maximum climbing height of the landslide obtained in step S6, and take preventive measures for the areas susceptible to landslide.

[0037] When the above-mentioned prediction method for predicting surge disasters caused by landslides based on climbing height is used, the above-mentioned method embodiment can complete the detection of the landslide climbing height without climbing height measurement equipment. The following Table 1 is a pressure detection table for the climbing height detection of five different volumes of landslide movements using the array point method under the conditions of 30° slope angle α, 20 cm water depth, and point spacing r=0.1 cm in the actual simulation process. The small interval of the points is used to improve the detection accuracy. If the distance is too large, the position without the points cannot be measured, which reduces the detection accuracy and affects the prediction results.

[0038] Table 1

[0039]

[0040]

[0041] Table 2 shows the maximum climbing heights of the five landslides calculated based on Table 1. The results show that the maximum climbing heights of the five sliding blocks increase with the increase of their volumes, which is in line with actual rules. The method described in the embodiment of the present invention can effectively complete the detection of the maximum climbing height of the landslide and can quickly obtain accurate measurement results.

[0042] Table 2

[0043]

[0044] In summary, the method described in the embodiment of the present invention uses a uniform point distribution method to make the measurement of the maximum climbing height of the landslide accurate and systematic, greatly improving the detection efficiency and reducing the workload of the staff; at the same time, this method can not only be used for the established landslide climbing height measurement, but also can be applied to other slope areas where height measurement is inconvenient by changing the point distribution method and density, thereby detecting geological disasters at a relatively low cost and meeting the data analysis needs for disaster prediction, and has unique advantages in both technology and market prospects.

[0045] The above-mentioned ideal embodiments of the present invention are for inspiration. Through the above-mentioned description, relevant staff can make various changes and modifications without departing from the technical idea of ​​the present invention. The technical scope of the present invention is not limited to the contents of the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A method for predicting surge disasters caused by landslides based on climbing height, characterized in that: The specific operation includes the following steps: S1. First, confirm the river bank in the area where the landslide occurs. The river bank point in this area is recorded as P0. Then confirm the starting point of the distribution point on the opposite bank of the landslide and record it as P1. S2, take P1 as the starting point, and evenly arrange pressure monitoring points upward along the normal direction of the slope, with the direction from P0 to P1 as the X-axis, the water depth direction as the Z-axis, the perpendicular to the XZ plane as the Y-axis, the slope angle as α, and the number of points arranged upward along the slope in the XZ plane is recorded as P1, P2...P n , and the distance between two adjacent monitoring points in the XZ plane is recorded as r, and the number of points in the XZ plane and the number of points in the array along the Y axis are recorded as P 1y , P 2y ...P ny , and the distance between two adjacent monitoring points along the X direction in the XY plane is recorded as r·COSα; S3. When a landslide occurs, the pressure data of the slope is detected; S4, judging whether the number of points is greater than the number of points with pressure data, if the number of points is equal to the number of points with pressure data, the points should be increased and S2-S4 should be repeated; S5. According to the change in the number of points with pressure data, the change law of the maximum climbing length of the landslide on the opposite bank is obtained; S6, then use the slope of the opposite bank and the Pythagorean theorem to convert the maximum climbing length to obtain the maximum climbing height of the landslide on the opposite bank; S7. Determine the minimum safe altitude of the landslide prone area according to the maximum climbing height of the landslide obtained in step S6, and take preventive measures for the areas susceptible to landslide.

2. The method for predicting surge disasters caused by landslides based on climbing height according to claim 1, characterized in that: In step S1, the intersection of the midpoint of the river bank in the landslide occurrence area with the water surface is recorded as P0, and the vertical plane passing through point P0 is used as the reference plane. An external normal is established from the midpoint to the opposite bank of the river, and the intersection with the opposite bank is recorded as P1.

3. The method for predicting surge disasters caused by landslides based on climbing height according to claim 1, characterized in that: In step S4, the number of monitoring points that can detect data changes with time. If the number of points is greater than the number of climbing height detection points, that is, when the number of pressure data points is the largest, the number of points is greater than the number of data detection points, then the detection process is determined to be valid and the next step is performed; When the number of points is equal to the number of detection points with data, it is impossible to accurately determine whether this point is the farthest point that can be reached by climbing the landslide, so the data cannot be accurately calculated. Therefore, it is recorded as an invalid detection process, and the number of points should be increased and steps S2-S4 should be repeated.

4. The method for predicting surge disasters caused by landslides based on climbing height according to claim 1, characterized in that: In step S5, when the number of pressure data points is the largest during the effective detection process, the point at which the pressure change is detected at the last point of the climbing height detection point is recorded as P. n According to the interval between monitoring points, the maximum climbing length d of the landslide on the opposite bank can be calculated as: d = (n-1)r.

5. The method for predicting surge disasters caused by landslides based on climbing height according to claim 1, characterized in that: In step S6, the angle of the slope is obtained by consulting the data as α, and the calculation formula of the maximum climbing height h is: h=(n-1)r×sinα.

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