CN114333245A - Multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring - Google Patents
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Abstract
The invention discloses a multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring, which comprises the following steps: primarily evaluating the stability of the current situation of the main monitored object according to the deformation characteristics of the landslide monitoring area to obtain a primary evaluation result; setting an early warning criterion threshold according to the primary evaluation result, the landslide disaster development history and the development mechanism; according to the type selection of monitoring equipment of a main monitoring object, a multi-parameter early warning model is constructed in combination with main inducing factors of landslide disasters; dynamically adjusting an early warning criterion threshold value and a multi-parameter early warning model, and setting an abnormal strategy to reduce the false alarm rate; and when the monitoring value reaches the early warning criterion threshold range after dynamic adjustment, triggering the multi-parameter early warning model and sending landslide early warning information. By dynamically adjusting the early warning criterion and the model, the accuracy of the monitoring and early warning model can be improved along with the increase of monitoring information and the definition of the development trend; the method is beneficial to promoting the research of the geological disaster monitoring and early warning system and improving the accuracy of the geological disaster monitoring and early warning.
Description
Technical Field
The invention belongs to the technical field of geological disaster monitoring and early warning, and particularly relates to a multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring.
Background
Geological disasters such as collapse, landslide, debris flow and the like widely exist in mountainous and hilly areas in China, and cause great hidden dangers to the development of the economy and the society and the safety of lives and properties of people. Accurate landslide disaster monitoring and early warning are important ways for improving the disaster prevention and reduction capability. As a complex system engineering, the method not only relates to landslide disaster site investigation, developmental mechanism analysis and stability evaluation, but also comprises monitoring equipment type selection, early warning criterion threshold setting, early warning model design and the like.
Common regional landslide hazard monitoring and early warning are single in setting of early warning criterion threshold values, and deformation damage threshold values of specific monitoring points cannot be well reflected; secondly, the early warning model is single, the error of single-parameter early warning is large under the complex geological environment, and false warning is often caused; in addition, the static multi-parameter early warning model cannot achieve the monitoring and early warning effect on the landslide disaster in a longer time scale.
In the prior art, chinese patent CN111784070A discloses a landslide short-term intelligent early warning method based on XGBoost algorithm. Collecting characteristic data of the landslide body in real time, and constructing a landslide body characteristic vector; the characteristic vector of the landslide body comprises rainfall, soil moisture content and landslide body surface deformation characteristics; the XGboost model predicts the land surface deformation characteristics of the landslide body on the prediction day according to the landslide body characteristic vector constructed by the historical time sequence before the prediction day and the rainfall predicted by the weather forecast on the prediction day; and if the predicted value is greater than the safety threshold value, sending out intelligent early warning. Dynamic adjustment of the pre-warning criterion threshold and model based on factors such as equipment is not considered in this patent.
In the prior art, chinese patent CN113139020A discloses a self-adaptive migration method of a landslide monitoring and early warning model, which first analyzes the geographic environment similarity of a newly-built monitoring point and an existing monitoring point within a certain spatial range to obtain the similarity between the newly-built monitoring point and the existing monitoring point; then, based on the early warning model of the existing monitoring point, combining with the similarity metric value, deducing an initial early warning model of the newly-built monitoring point; and finally, after the newly-built monitoring point operates, the initial early warning model can automatically adjust the similarity weight coefficient according to the monitoring early warning result, and the gradual optimization of the model is realized. The patent does not consider that the type selection or layout position of the equipment can affect the early warning criterion threshold value or the model, and does not consider that the abnormal strategy is used for eliminating the factors affecting the accuracy of the early warning result.
Disclosure of Invention
Aiming at the technical problems, the invention aims to provide a multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring, and improve the accuracy of regional landslide disaster monitoring and early warning.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring comprises the following steps:
analyzing basic characteristics of landslide hidden danger points in a monitoring area, and performing primary evaluation on the current state stability of a main monitoring object according to deformation characteristics of the landslide monitoring area to obtain a primary evaluation result; selecting proper monitoring parameters and monitoring equipment to form a landslide three-dimensional monitoring scheme;
setting an early warning criterion threshold according to the primary evaluation result, the landslide disaster development history and the development mechanism;
according to the type selection of monitoring equipment of a main monitoring object, a multi-parameter early warning model is constructed in combination with main inducing factors of landslide disasters;
dynamically adjusting the early warning criterion threshold value and the multi-parameter early warning model based on the monitoring result, and setting an abnormal strategy to reduce the false alarm rate;
and when the monitoring value reaches the early warning criterion threshold range after dynamic adjustment, triggering the multi-parameter early warning model and sending landslide early warning information.
Further, based on the characteristics of wide development distribution, complex deformation characteristics and multiple induction factors of geological disasters in mountainous and hilly areas, a landslide hidden danger point is selected as a main monitoring object.
Further, basic information of landslide disaster points and current landslide hidden danger points which occur in a monitoring area is collected before primary evaluation, wherein the basic information of the landslide disaster points comprises geological conditions, landslide occurrence backgrounds, deformation characteristics, early rainfall, formation mechanism and loss conditions, and the basic information of the landslide hidden danger points comprises geological conditions, rainfall, deformation signs, landslide body scale and threat range;
and selecting rainfall, surface displacement, cracks, dip angles and water content as main monitoring parameters according to the scale, the influence range, the development characteristics and the engineering environmental conditions of the landslide hidden danger points, so as to realize the landslide three-dimensional monitoring.
Further, primarily evaluating the stability of the current situation of a main monitoring object according to deformation characteristics of a landslide monitoring area to obtain a primary evaluation result, wherein the deformation characteristics mainly comprise deformation conditions of a front edge, a middle part, a rear edge and a side edge of a slope of the monitoring area and deformation signs of houses and trees on the surface of a slope body;
according to the deformation characteristics of the landslide monitoring area, scoring the current stability of the landslide hidden danger points;
and dividing the monitoring area according to a drainage basin or an administrative division, and summarizing and forming a database by combining the current stability score condition of the landslide hidden danger points.
Further, setting a pre-warning criterion threshold according to the preliminary evaluation result, the landslide disaster development history and the development mechanism, wherein the pre-warning criterion threshold comprises the following steps:
dividing monitoring areas according to drainage basins or administrative divisions, analyzing background and early rainfall at landslide disaster points of each area, and setting rainfall monitoring and early warning thresholds at monitoring points with the same current situation and stability scores in each area;
and setting monitoring and early warning thresholds of earth surface displacement, cracks and dip angles according to the slope deformation characteristics, the development mechanism and the equipment installation position.
Further, the difference of the induction factors of different landslide hidden danger points and the difference of the development mechanisms are comprehensively considered, the weight relation of different monitoring equipment parameters is analyzed, and a multi-parameter early warning model is constructed.
Furthermore, the monitoring and early warning system operates, monitoring data of a monitoring area are obtained in real time through monitoring and early warning equipment, and emergency response is conducted on monitoring points which perform effective early warning according to geological disaster management regulations.
Furthermore, after the monitoring and early warning system gives false alarms, the monitoring curve is analyzed, and the early warning criterion threshold value and the multi-parameter early warning model are adjusted in the aspects of equipment errors, deformation characteristics and layout positions.
Further, adjusting the early warning criterion threshold value according to the error of the equipment, the deformation characteristics and the false alarm caused by the arrangement position;
and readjusting the model logic relation according to errors caused by problems of the multi-parameter early warning model.
Further, the method further comprises:
and analyzing the monitoring data of the monitoring area, and setting an abnormal strategy for the monitoring equipment according to the monitoring curve feedback condition and the disaster evolution mechanism.
Compared with the prior art, the invention has the following advantages:
(1) the method has reasonable logical relationship, and comprehensively considers the development history of landslide disaster in the monitoring area, the development mechanism and the development trend of the monitoring object;
(2) according to the landslide disaster development mechanism and the monitoring condition, an abnormal strategy is set, so that the false alarm rate is reduced, and abnormal instruments and equipment are quickly found;
(3) the method has certain generalizability, and can be used for monitoring and early warning in different areas and different equipment types;
(4) the method realizes the dynamic adjustment of the early warning criterion and the early warning model, improves the precision of the monitoring and early warning model along with the increase of monitoring information and the definition of development trend, is favorable for promoting the research of a landslide disaster monitoring and early warning system, and improves the accuracy of landslide disaster monitoring and early warning.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is obvious that the drawings in the following description are some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive exercise.
FIG. 1 is a schematic flow chart of a multi-parameter model dynamic early warning method for monitoring points according to the present invention;
FIG. 2 is a present stability scoring exemplary scale in accordance with the present invention;
FIG. 3 illustrates an exemplary pre-warning criterion for a monitoring device in accordance with the present invention;
FIG. 4 is a schematic diagram of a multi-parameter early warning model design according to the present invention;
FIG. 5 is an example of exception policy settings in the present invention;
FIG. 6 is an example of dynamic adjustment of a multi-parameter model in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The examples are given for the purpose of better illustration of the invention, but the invention is not limited to the examples. Therefore, those skilled in the art should make insubstantial modifications and adaptations to the embodiments of the present invention in light of the above teachings and remain within the scope of the invention.
Example 1
As shown in fig. 1, the embodiment is a multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring, and the monitoring of landslide hidden danger points is known by using historical data of landslide disaster points, and meanwhile, effective early warning of landslide disasters is realized. The landslide hazard point in the embodiment is a place where a landslide hazard is formed, and casualties or economic losses are caused; the landslide hazard point is a slope which can cause life and property loss.
The early warning method in the embodiment comprises the following steps:
s1, surveying landslide hazard points and landslide hidden danger points in the monitoring area on site, collecting basic information of the landslide hazard points, and performing primary evaluation on the stability status of the landslide hidden danger points in a scoring mode
And performing site survey, determining the basic situation of a monitoring point, recording the deformation characteristics of the rear edge, the side edge, the middle part and the front edge of the slope in detail, and the deformation signs of houses, trees and the like on the slope surface, and scoring and evaluating the current stability of the slope by using a current stability scoring example scale shown in figure 2.
Step S1 includes the following steps:
(1) collecting basic information of landslide hazard points and hidden danger points in a monitoring area, wherein the basic information of the landslide hazard points comprises geological conditions, landslide occurrence backgrounds, deformation characteristics, early rainfall, formation mechanisms, loss conditions and the like, and the basic information of the landslide hidden danger points comprises the geological conditions, the rainfall, deformation signs, landslide body scales, threat ranges and the like;
(2) according to the field investigation condition, scoring the stability current situation of the landslide hidden danger points;
(3) and dividing the monitoring area according to a drainage basin or an administrative division, and summarizing and forming a database by combining the stability status scoring situation.
S2, according to the terrain condition, the development scale and the engineering condition of the landslide hidden trouble point, the type selection of the monitoring equipment is carried out
According to the scale, threat range, development characteristics, engineering environmental conditions and the like of the landslide hidden danger points, proper monitoring and early warning equipment is selected, and the monitoring and early warning equipment in the embodiment comprises one or more of a rain gauge, a ground surface displacement monitoring station, a crack meter, an inclinometer and the like.
Specifically, step S2 includes:
(1) analyzing geological features of the hidden danger points, including developmental mechanisms, induction factors, evolution processes, threat ranges and the like;
(2) determining monitoring parameters, monitoring equipment and layout point positions according to the analysis result;
(3) and (4) according to the type selection of the monitoring equipment, building a single monitoring point early warning system.
S3, according to the landslide disaster development historical data of the monitoring area and in combination with the current situation of stability of the monitoring point, preliminarily setting the threshold value of the monitoring early warning criterion of each device
Historical development data of landslide disasters in a monitoring area are statistically analyzed, and early warning criterion thresholds are preliminarily designed by combining stability and development trend of monitoring points, wherein the early warning criterion thresholds are illustrated in fig. 3, and early warnings are divided into four types, namely blue early warning, yellow early warning, orange early warning and red early warning.
Specifically, step S3 includes:
(1) analyzing historical data of landslide disaster development in a monitoring area, mainly comprising rainfall, rainfall type, rainfall duration and the like, summarizing characteristic parameters and a disaster development rule, and selecting landslide hidden danger point monitoring and early warning criteria, wherein the criteria comprise accumulated rainfall, effective rainfall, surface displacement deformation rate, deformation, continuous deformation condition, crack deformation rate, deformation, continuous deformation condition, inclination angle variation rate, continuous variation rate frequency, mud water level value, mud water level variation and the like;
(2) considering the deformation development trend by combining the current stability of the monitoring points, as shown in fig. 3, designing early warning criterion thresholds of each monitoring device;
(3) designing early warning criterion threshold values based on a landslide disaster development mechanism, for example, for traction type landslides and push type landslides, arranging surface displacement monitoring equipment at the front edge and the rear edge, wherein the early warning criterion threshold values are different; for landslides in different deformation stages, the threshold setting of the crack meter should be different;
(4) for different hidden danger points of the threat object, the difference of the early warning threshold value setting is considered.
S4, according to the type selection of the monitoring equipment and the main inducing factors of landslide disasters, preliminarily designing the multi-parameter early warning model of each monitoring point
And constructing a multi-parameter early warning model according to the type selection and the main induction parameters of the monitoring equipment.
Specifically, step S4 includes:
(1) in combination with specific monitoring points, the main inducing factors of landslide disasters are considered, and a multi-parameter early warning model is constructed, wherein the multi-parameter model constructed in the embodiment is shown in fig. 4;
(2) the multi-parameter early warning model logic expression is mainly connected with each monitoring early warning parameter through 'and', 'or' and '()', when the multi-parameter early warning model is constructed, the weight relation of each parameter is fully considered, if the formation of landslide disasters in the flood season has obvious correlation with rainfall, a multi-parameter model with rainfall as a main control factor can be designed;
(3) the setting of the multi-parameter early warning model is to avoid the condition setting from being severe to cause the report missing, and also to reduce the condition that the condition setting is too loose to cause the frequent false report.
S5, setting an abnormal strategy according to the early warning error report condition, reducing the false alarm rate of the monitoring early warning system and finding abnormal equipment in time
And the monitoring and early warning system operates, acquires monitoring data of the landslide disaster hidden danger area in real time through monitoring and early warning equipment, and carries out emergency response on monitoring points for effective early warning according to geological disaster management regulations.
Specifically, step S5 includes:
(1) the monitoring and early warning system runs online, monitoring data of the landslide hidden danger points are obtained in real time, monitoring parameters reach a set threshold value, and after multi-parameter early warning is triggered, the monitoring and early warning system is sent to relevant responsible persons through short messages;
(2) for the hidden danger points with dangerous cases after verification, surrounding threatened people are prompted through an audible and visual alarm, and emergency response is carried out according to geological disaster management regulations;
(3) and analyzing and summarizing the false alarm reason for the early warning information which belongs to the false alarm after verification.
S6, analyzing the monitoring data, comprehensively considering equipment errors, hidden danger point deformation characteristics, equipment layout positions and the like caused by different environments, and respectively optimizing and adjusting the early warning criterion thresholds of different monitoring points and different monitoring equipment of the same monitoring point
After the monitoring and early warning system gives false alarms, the monitoring curve is analyzed, and the early warning criterion threshold value and the multi-parameter early warning model are adjusted according to the aspects of equipment errors, deformation characteristics, layout positions and the like.
Specifically, step S6 includes:
(1) adjusting the early warning criterion threshold value by false alarm caused by equipment error, deformation characteristics and layout position;
(2) and readjusting the model logic relation by the error caused by the problem of setting the multi-parameter early warning model.
S7, dynamically adjusting the multi-parameter early warning model of each monitoring point according to the change of the main induction factors of the hidden danger points and the feedback condition of the monitoring data
And analyzing the monitoring data of the monitoring area, and setting an abnormal strategy for each monitoring device as shown in fig. 5, so as to reduce the false alarm condition and timely find out the problem devices.
Specifically, step S7 includes:
(1) setting an abnormal strategy for monitoring equipment according to the monitoring curve feedback condition and a disaster evolution mechanism, wherein rainfall monitoring abnormity mainly comprises no rainfall data for multiple days and overlarge or undersize rainfall data for single day, surface displacement monitoring abnormity mainly comprises no monitoring data for a long time and displacement curve tangent angle overrun, crack meter monitoring abnormity mainly comprises monitoring curve tangent angle overrun, and inclinometer monitoring abnormity mainly comprises triaxial inclination angle change rate overrun, continuous change rate frequency overrun and the like;
(2) the setting of the exception policy mainly comprises two aspects: the false alarm rate of the instrument and equipment is reduced, and abnormal equipment is found in time;
s8, when the monitoring value of each device reaches the optimized early warning criterion threshold value, triggering a multi-parameter early warning model, sending early warning information to related responsible persons and departments in charge, realizing effective early warning, and achieving the purpose of accurate early warning
And dynamically adjusting the multi-parameter early warning model according to the adjusted early warning criterion and the abnormal condition of the equipment, such as figure 6, so as to achieve the purpose of monitoring and early warning.
Further, the step S8 includes:
(1) adjusting the monitoring parameter weight according to the stability of the instrument and equipment fed back by the monitoring condition, and optimizing the logic relation of the multi-parameter early warning model;
(2) based on a landslide disaster development mechanism, adjusting the weight of monitoring parameters, if the rainfall is obviously reduced after a flood season, and the rainfall parameters are prevented from playing a decisive role in an early warning model;
(3) and eliminating equipment with unnecessary monitoring parameters dropped due to unsmooth data transmission, reconstructing the multi-parameter early warning model, and timely adjusting the early warning model after maintenance and replacement are completed.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A multi-parameter model dynamic early warning method based on landslide three-dimensional monitoring is characterized by comprising the following steps:
primarily evaluating the stability of the current situation of the main monitored object according to the deformation characteristics of the landslide monitoring area to obtain a primary evaluation result;
setting an early warning criterion threshold according to the primary evaluation result, the landslide disaster development history and the development mechanism;
according to the type selection of monitoring equipment of a main monitoring object, a multi-parameter early warning model is constructed in combination with main inducing factors of landslide disasters;
dynamically adjusting the early warning criterion threshold value and the multi-parameter early warning model based on the monitoring result, and setting an abnormal strategy to reduce the false alarm rate;
and when the monitoring value reaches the early warning criterion threshold range after dynamic adjustment, triggering the multi-parameter early warning model and sending landslide early warning information.
2. The warning method according to claim 1, wherein:
based on the characteristics of wide development distribution, complex deformation characteristics and multiple induction factors of geological disasters in mountainous and hilly areas, the landslide hidden danger point is selected as a main monitoring object.
3. The warning method according to claim 1, wherein:
collecting basic information of landslide hazard points and current landslide hidden danger points which occur in a monitoring area, wherein the basic information of the landslide hazard points comprises geological conditions, landslide occurrence backgrounds, deformation characteristics, early rainfall, formation mechanism and loss conditions, and the basic information of the landslide hidden danger points comprises the geological conditions, the rainfall, deformation signs, landslide body scale and threat range;
and selecting rainfall, surface displacement, cracks, dip angles and water content as main monitoring parameters according to the scale, the influence range, the development characteristics and the engineering environmental conditions of the landslide hidden danger points, so as to realize the landslide three-dimensional monitoring.
4. The warning method according to claim 2, wherein:
primarily evaluating the current stability of a main monitoring object according to deformation characteristics of a landslide monitoring area to obtain a primary evaluation result, wherein the deformation characteristics mainly comprise deformation conditions of a front edge, a middle part, a rear edge and a side edge of a slope of the monitoring area and deformation signs of houses and trees on the surface of the slope;
according to the deformation characteristics of the landslide monitoring area, scoring the current stability of the landslide hidden danger points;
and dividing the monitoring area according to a drainage basin or an administrative division, and summarizing and forming a database by combining the current stability score condition of the landslide hidden danger points.
5. The early warning method as claimed in claim 4, wherein setting an early warning criterion threshold value according to the preliminary evaluation result, the landslide disaster development history and the development mechanism comprises:
dividing monitoring areas according to drainage basins or administrative divisions, analyzing background and early rainfall at landslide disaster points of each area, and setting rainfall monitoring and early warning thresholds at monitoring points with the same current situation and stability scores in each area;
and setting monitoring and early warning thresholds of earth surface displacement, cracks and dip angles according to the slope deformation characteristics, the development mechanism and the equipment installation position.
6. The warning method according to claim 1, wherein: and comprehensively considering the difference of the induction factors of different landslide hidden danger points and the difference of the development mechanism, analyzing the weight relation of different monitoring equipment parameters, and constructing a multi-parameter early warning model.
7. The warning method according to claim 1, wherein: and the monitoring and early warning system operates, acquires monitoring data of a monitoring area in real time through monitoring and early warning equipment, and carries out emergency response on monitoring points which effectively early warn according to geological disaster management regulations.
8. The warning method according to claim 7, wherein: and after the monitoring and early warning system gives false alarms, analyzing a monitoring curve, and adjusting an early warning criterion threshold value and a multi-parameter early warning model in consideration of equipment errors, deformation characteristics and layout positions.
9. The warning method according to claim 8, wherein:
adjusting the early warning criterion threshold value according to the error of the equipment, the deformation characteristics and the false alarm caused by the arrangement position;
and readjusting the model logic relation according to errors caused by problems of the multi-parameter early warning model.
10. The warning method of claim 1, further comprising:
and analyzing the monitoring data of the monitoring area, and setting an abnormal strategy for the monitoring equipment according to the monitoring curve feedback condition and the disaster evolution mechanism.
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| CN115273410A (en) * | 2022-09-09 | 2022-11-01 | 西北大学 | Sudden landslide monitoring and early warning system based on big data |
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| CN115325928A (en) * | 2022-10-17 | 2022-11-11 | 西北大学 | Landslide earth surface crack integrated monitoring system based on Beidou communication |
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| CN116205497A (en) * | 2023-04-24 | 2023-06-02 | 四川川核地质工程有限公司 | Landslide intelligent early warning method and system based on artificial intelligence |
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