Ecological slope protection instability early warning method and system

Abstract

The invention discloses an ecological slope protection instability early warning method and system, and relates to the technical field of ecological slope protection monitoring, and the early warning method comprises the steps: collecting the monitoring information of an area where an ecological slope protection is located; a numerical value reflecting the soil stability degree is obtained according to soil information, a dynamic attenuation model of soil mechanical properties along with time is introduced, and the model is constructed based on soil initial state parameters and attenuation trends monitored for a long time. According to the ecological slope protection instability early warning method and system, a self-adaptive weight adjustment method is adopted for comprehensive early warning value calculation, the parameter influence proportion is dynamically optimized in combination with historical early warning accuracy, and meanwhile, the environment adjustment coefficient and the case correction coefficient are introduced, so that the comprehensive early warning value can adapt to different environments and historical experiences, and the early warning accuracy is improved. The adaptability and the flexibility of the early warning model are enhanced; and the grading dynamic early warning threshold mechanism is automatically adjusted according to the geographical environment sensitivity grade and the ecological value of the slope, so that the early warning standard is more targeted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological slope protection monitoring, and particularly relates to an ecological slope protection instability early warning method and system. BACKGROUND

[0002] Ecological slope protection is an important means for preventing slope instability and protecting the ecological environment by combining engineering measures and ecological restoration techniques. It is widely used in mountain slopes along highways and railways, and embankment areas in water conservancy projects. This type of slope protection not only stabilizes the slope, but also plays an ecological role in soil and water conservation and environmental beautification by planting vegetation and laying ecological bags. However, in practical applications, ecological slope protection is often affected by various natural and human factors, and is prone to instability risks.

[0003] In the rainy summer, continuous rainfall can significantly increase the soil water content, leading to a decrease in soil mechanical properties. The erosion of strong water flow further erodes the surface layer of the slope, weakening the stability of the slope protection structure. During the growth cycle of vegetation, if it is affected by pests and diseases or extreme drought weather, the slope-stabilizing ability of the vegetation roots will be significantly reduced. At this time, the slope is prone to local collapse under the action of its own gravity and external loads. In addition, under the influence of long-term vehicle vibration, the cohesion between soil particles gradually weakens, and repeated freezing and thawing cycles in winter can easily cause cracks in the slope, leading to overall instability.

[0004] In the prior art, the monitoring of ecological slope protection is mostly carried out by a single parameter monitoring method, such as monitoring only the displacement of the slope or the soil water content, which cannot fully reflect the actual stability state of the slope protection. At the same time, the traditional early warning method lacks analysis of the synergistic effect between various influencing factors, and often lags behind or misreports in complex scenarios. For example, during a rainstorm, a mountain highway slope failed to issue an early warning in time and eventually collapsed, causing traffic disruption and economic losses, because only the soil water content was monitored without considering the synergistic effect of water flow erosion and vegetation damage. Therefore, we propose an ecological slope protection instability early warning method and system. SUMMARY

[0005] (I) Technical problems solved In view of the deficiencies of the prior art, the present application provides an ecological slope protection instability early warning method and system, which solves the technical problem that the existing ecological slope protection instability early warning system only considers the influence of a single factor on slope instability, resulting in low accuracy of early warning. Some systems consider multiple factors, but do not conduct in-depth analysis of the synergistic effect between factors, making it difficult to accurately reflect the actual stability state of the slope.

[0006] (II) Technical solutions To achieve the above object, the present application is realized by the following technical solutions: An ecological slope protection instability early warning method, the early warning method comprises: Collecting monitoring information of the area where the ecological slope protection is located, wherein the monitoring information contains soil-related information, hydrology-related information, vegetation-related information and location movement-related information, and the time and space synchronous collection of information is realized by monitoring devices of different principles, the monitoring devices include sensors for monitoring soil, devices for monitoring hydrology, equipment for observing vegetation and instruments for tracking location movement; According to the soil-related information, a value reflecting the soil stability degree is obtained, and a dynamic attenuation model of soil mechanical properties with time is introduced in the value calculation process, and the model is constructed based on soil initial state parameters and long-term monitored attenuation trend; According to the hydrology-related information, a value reflecting the hydrology influence degree is obtained, and the value calculation combines the different weights of different stages of hydrological cycle on the slope, and the different weights are determined according to regional hydrological feature historical data; According to the vegetation-related information, a value reflecting the fixed effect of vegetation on the slope is obtained, and the value calculation integrates the dynamic change curve of the root system fixing slope capacity in the vegetation growth cycle, and the curve is drawn through the correlation analysis of vegetation growth stage and root system mechanical properties; According to the location movement-related information, a value reflecting the location movement danger degree is obtained, and the value calculation adopts an analysis method of the change law of location movement in time and space, which comprehensively considers the correlation and propagation characteristics of location movement of different monitoring points; The dynamic correlation analysis is performed on the value reflecting the soil stability degree and the value reflecting the hydrology influence degree, to obtain a first synergistic influence coefficient, wherein the dynamic correlation analysis is to determine the degree of influence of one party change on the other party by establishing an interaction model of the changes of both with time, and the model is embedded with a soil response amplification mechanism under extreme hydrological events; The dynamic correlation analysis is performed on the value reflecting the fixed effect of vegetation on the slope and the value reflecting the location movement danger degree, to obtain a second synergistic influence coefficient, and the critical value of damaged vegetation is included in the analysis process, and when the vegetation parameter is lower than the critical value, the influence weight of the location movement parameter is automatically increased; The comprehensive early warning value is calculated by combining the value reflecting the soil stability degree, the value reflecting the hydrology influence degree, the value reflecting the fixed effect of vegetation on the slope, the value reflecting the location movement danger degree, the first synergistic influence coefficient and the second synergistic influence coefficient, and the self-adaptive weight adjustment method which can dynamically optimize the influence proportion of each parameter according to the historical early warning accuracy is adopted in the calculation process; whether the comprehensive early warning value exceeds the pre-set early warning limit value, the early warning limit value adopts a hierarchical dynamic threshold mechanism and is automatically adjusted according to the sensitivity level and ecological value of the geographical environment of the slope; If the comprehensive early warning value exceeds the pre-set early warning limit value, it is determined that the ecological slope has a possibility of instability, and graded early warning response measures are started, and the key areas of early warning are determined according to the first and second synergistic influence coefficients, and a visual early warning report containing emergency disposal priority and specific prevention and control suggestions is generated for the key areas; If the comprehensive early warning value does not exceed the pre-set early warning limit value, it is determined that the ecological slope is in a stable state, and the original monitoring time interval is maintained, and the monitoring data and analysis results of this time are stored in the historical database for model optimization. The model optimization adopts an incremental learning method of only training the new data to improve the adaptability of the model.

[0007] Preferably, the step of obtaining a value reflecting the soil stability degree according to the soil-related information comprises: extracting the current soil water content, the standard soil water content, the soil density and the soil organic matter content in the soil-related information; calculating the difference between the current soil water content and the standard soil water content to obtain the soil water content change amount, and correcting the change amount according to the soil organic matter content, the higher the organic matter content, the smaller the correction coefficient; determining a soil shear strength correction value according to the soil density, and the determination process referring to a nonlinear relationship curve between the soil density and the shear strength; recording the continuous duration of the soil water content change amount exceeding the first specified value to obtain the duration of the soil water content anomaly, and setting different cumulative weights for the anomaly duration in different seasons; obtaining a value reflecting the soil stability degree according to the soil water content change amount, the soil shear strength correction value and the duration of the soil water content anomaly, and combining a dynamic attenuation model of soil mechanical properties.

[0008] Preferably, the step of obtaining a value reflecting the hydrological influence degree according to the hydrological-related information comprises: extracting the current water level, the current flow velocity, the water flow impact force and the water body pH value in the hydrological-related information; calculating the change amount of the current water level per unit time to obtain the water level rising amplitude, and correcting the amplitude according to the water body pH value, the greater the deviation of the pH value from neutral, the greater the correction coefficient; calculating the change amount of the current flow velocity per unit time to obtain the water flow velocity change ratio; The water flow erosion correction coefficient is determined according to the water flow impact force, and the coefficient determination considers the matching relationship between the water flow impact force and the erosion resistance of the slope material. The duration of the abnormal hydrological condition is obtained by recording the continuous duration when the water body height rising amplitude exceeds the second specified value or the water flow speed change ratio exceeds the third specified value, and the recording process distinguishes the abnormal time weight in the wet period and the dry period; According to the water body height rising amplitude, the water flow speed change ratio, the water flow erosion correction coefficient and the duration of the abnormal hydrological condition, and combining the different weights of the hydrological cycle stage, a value reflecting the degree of influence of hydrology is obtained.

[0009] Preferably, the step of obtaining a value reflecting the fixing effect of vegetation on the slope according to the vegetation-related information comprises: Extracting the vegetation coverage area proportion, the density of plant root distribution, the vegetation growth vigor index and the vegetation species diversity in the vegetation-related information; Calculating the difference between the vegetation coverage area proportion and the vegetation coverage area proportion in the same period in the past to obtain the coverage area proportion change amount, and the calculation process incorporates the species diversity coefficient, and the higher the diversity, the smaller the weight adjustment coefficient of the change amount; According to the density of plant root distribution, the vegetation growth vigor index and the vegetation species diversity, a coefficient reflecting the firmness of the root system is determined, wherein the contribution degree of different species of root system is set according to the actual measurement data of the slope fixing ability; According to the coverage area proportion change amount and the coefficient reflecting the firmness of the root system, and combining the dynamic change curve of the root system fixing slope ability in the growth cycle of the vegetation, a value reflecting the fixing effect of the vegetation on the slope is obtained.

[0010] Preferably, the step of obtaining a value reflecting the degree of danger of position movement according to the position movement-related information comprises: Extracting the three-dimensional space position coordinates, the corresponding time records, the position movement acceleration and the mutation frequency of the position movement direction at different time points in the position movement-related information; According to the three-dimensional space position coordinates of adjacent time points, the distance of the position movement is calculated, and the distance calculation considers the spatial distribution density of the monitoring points for weighted processing; According to the distance of the position movement and the corresponding time interval, the speed of the position movement is calculated; According to the position movement distance and the time record at multiple time points, the path of the position movement is drawn, and the path analysis introduces fractal dimension calculation to quantify the complexity of the path; According to the bending situation of the position movement path and the mutation frequency of the position movement direction, the speed of the change of the position movement direction is determined; According to the distance of position movement, the speed of position movement, the speed of position movement direction change, the acceleration of position movement, and the analysis method of position movement change in time and space, a value reflecting the dangerous degree of position movement is obtained.

[0011] Preferably, the step of calculating the comprehensive early warning value in combination with the value reflecting the soil stability degree, the value reflecting the hydrological influence degree, the value reflecting the vegetation fixation effect on the slope, the value reflecting the dangerous degree of position movement, the first synergistic influence coefficient, and the second synergistic influence coefficient comprises: A first important degree proportion is determined according to the value reflecting the soil stability degree and the first synergistic influence coefficient, and the proportion determination process uses a fuzzy analytic hierarchy process to handle the uncertainty relationship between parameters. A second important degree proportion is determined according to the value reflecting the hydrological influence degree and the first synergistic influence coefficient. A third important degree proportion is determined according to the value reflecting the vegetation fixation effect on the slope and the second synergistic influence coefficient. A fourth important degree proportion is determined according to the value reflecting the dangerous degree of position movement and the second synergistic influence coefficient. An environment adjustment coefficient is obtained, wherein the environment adjustment coefficient includes a seasonal influence coefficient, a terrain influence coefficient, a climate mutation influence coefficient, and a human activity influence coefficient, and the human activity influence coefficient is determined according to the intensity and frequency of regional engineering activities. Similar case data in a historical database are called to compare and correct, to obtain a case correction coefficient, the similar case matching uses a multi-feature vector cosine similarity calculation method, and time decay weights are set for cases of different time spans. The comprehensive early warning value is calculated by an adaptive weight adjustment method according to the value reflecting the soil stability degree, the value reflecting the hydrological influence degree, the value reflecting the vegetation fixation effect on the slope, the value reflecting the dangerous degree of position movement, the first synergistic influence coefficient, the second synergistic influence coefficient, the first important degree proportion, the second important degree proportion, the third important degree proportion, the fourth important degree proportion, the environment adjustment coefficient, and the case correction coefficient.

[0012] Preferably, the step of obtaining the first synergistic influence coefficient by dynamically correlating the value reflecting the soil stability degree and the value reflecting the hydrological influence degree comprises: A first sequence reflecting the change of the value reflecting the soil stability degree over time and a second sequence reflecting the change of the value reflecting the hydrological influence degree over time are established. The time nodes and the change amplitudes of the values in the two sequences are determined. analyze the influence degree of the first sequence value change on the second sequence value change and the influence degree of the second sequence value change on the first sequence value change in the same time interval; introducing an extreme hydrological event identification mechanism, when an extreme hydrological event is monitored, amplifying the influence weight of soil response according to the preset rules; According to the analysis results, the first synergistic influence coefficient is calculated, and the larger the coefficient value is, the more significant the interaction of the two on the slope instability is.

[0013] Preferably, the step of dynamically correlating the value reflecting the fixing effect of vegetation on the slope with the value reflecting the position movement danger degree to obtain the second synergistic influence coefficient comprises: establishing a third sequence reflecting the change of the value reflecting the fixing effect of vegetation on the slope over time and a fourth sequence reflecting the change of the value reflecting the position movement danger degree over time; setting a critical value of vegetation damage, when the value in the third sequence is lower than the critical value, it is marked as a vegetation protection ability decline stage; In the vegetation protection ability normal stage, the mutual influence relationship between the third sequence value change and the fourth sequence value change is analyzed; In the vegetation protection ability decline stage, the weight of the fourth sequence value change in the correlation analysis is increased; According to the analysis results of different stages, the second synergistic influence coefficient is calculated, and the larger the coefficient value is, the more significant the interaction of the two on the slope instability is.

[0014] An ecological slope protection instability early warning system, the early warning system comprises: An information collection part for collecting monitoring information of the area where the ecological slope protection is located, wherein the monitoring information includes soil related information, hydrological related information, vegetation related information and position movement related information, and the part integrates time and space synchronization control modules of various different principle monitoring devices, which can realize time calibration and space matching of data collected by different devices; An analysis and processing part for processing and analyzing the collected monitoring information to obtain a value reflecting the soil stability degree, a value reflecting the hydrological influence degree, a value reflecting the fixing effect of vegetation on the slope, a value reflecting the position movement danger degree, a first synergistic influence coefficient and a second synergistic influence coefficient, and calculating a comprehensive early warning value combining these values; An early warning judgment part for judging whether the comprehensive early warning value exceeds the pre-set early warning limit value, and executing corresponding early warning response measures or maintaining the original monitoring state according to the judgment result, and generating an early warning report or updating a historical database for model optimization.

[0015] characterized in that the analysis and processing part comprises: The soil information analysis unit is used to obtain a value reflecting the soil stability degree according to soil-related information, and the unit is internally provided with a dynamic attenuation model of soil mechanical properties over time, and can automatically call historical data to update model parameters; The hydrological information analysis unit is used to obtain a value reflecting the hydrological influence degree according to hydrological-related information, and the unit is stored with historical data of regional hydrological characteristics, and can automatically match different weights of corresponding hydrological stages according to real-time data; The vegetation information analysis unit is used to obtain a value reflecting the vegetation fixation effect on the slope according to vegetation-related information, and the unit contains dynamic change curve data of the root fixation ability of the slope in the vegetation growth cycle, and can automatically call the corresponding curve according to the vegetation growth stage; The position movement information analysis unit is used to obtain a value reflecting the position movement risk degree according to position movement-related information, and the unit adopts an analysis module of the time and space change law of position movement, and can process the correlation analysis of position movement data of multiple monitoring points; The synergistic analysis unit is used to dynamically correlate and analyze the value reflecting the soil stability degree and the value reflecting the hydrological influence degree to obtain a first synergistic influence coefficient, and to dynamically correlate and analyze the value reflecting the vegetation fixation effect on the slope and the value reflecting the position movement risk degree to obtain a second synergistic influence coefficient, and the unit contains an extreme event response mechanism and a vegetation damage critical value judgment module; The comprehensive early warning calculation unit is used to calculate a comprehensive early warning value by combining the above-mentioned values and coefficients, and the unit integrates an adaptive weight adjustment method capable of dynamically optimizing the calculation model according to the historical early warning accuracy.

[0016] (Three) beneficial effects 1. Multiple monitoring devices with different principles are used to realize time and space synchronous acquisition, covering comprehensive information such as soil, hydrology, vegetation and position movement, compared with single information source monitoring mode, it can more comprehensively capture the factors affecting the stability of ecological slope protection, and provide rich and reliable basic data for subsequent early warning analysis, and improve the comprehensiveness of early warning from the source; secondly, the soil stability degree value calculation adopts a dynamic attenuation model of soil mechanical properties, which conforms to the actual situation of soil change over time; the hydrological influence degree value calculation combines the different weights of different stages of hydrological cycle, and can accurately reflect the influence difference of different hydrological stages; the vegetation slope fixation effect value calculation integrates the dynamic change curve of root slope fixation ability, which accurately reflects the slope fixation change in the vegetation growth cycle; the position movement risk degree value calculation adopts a time and space evolution law analysis method, which comprehensively considers the correlation of monitoring points, these measures make the calculation of each factor characteristic value more in line with the actual situation, and improve the accuracy of single factor analysis, and lay a solid foundation for subsequent comprehensive early warning.

[0017] 2. Through the analysis of the synergistic effects of soil and hydrology, vegetation and position movement, the first and second synergistic effect coefficients are obtained, and the interaction relationship between factors is further explored. Especially in the synergistic analysis, the extreme hydrological event response mechanism and the vegetation damage threshold adjustment mechanism are embedded, which can effectively respond to the influence of special conditions on slope stability. Compared with the early warning method without considering the synergistic effect, the identification ability of slope instability risk under complex working conditions is significantly improved, and the early warning is more suitable for the complex scene of multi-factor interaction in actual engineering; 3. The adaptive weight adjustment method is used in the comprehensive early warning numerical calculation, the historical early warning accuracy is dynamically optimized, the parameter influence ratio is introduced, the environmental adjustment coefficient and the case correction coefficient are introduced, so that the comprehensive early warning value can adapt to different environments and historical experience, and the adaptability and flexibility of the early warning model are enhanced. The hierarchical dynamic early warning threshold mechanism automatically adjusts according to the geographical environment sensitivity grade and ecological value, so that the early warning standard is more targeted, and the problem of early warning lag or false alarm of fixed threshold in different scenes is avoided. In the early warning response link, the early warning key area is determined according to the synergistic effect coefficient, and a visual report containing emergency disposal priority and specific prevention and control suggestions is generated, so that the early warning can not only discover the risk in time, but also provide accurate guidance for emergency disposal, improve the efficiency and pertinence of risk response. For data in stable state, the incremental learning method is used to update the model, so that the system can continuously accumulate experience and optimize its performance. With the growth of use time, the early warning accuracy and adaptability continue to improve. BRIEF DESCRIPTION OF DRAWINGS

[0018] The above description is only a summary of the technical scheme of the present application. In order to more clearly understand the technical means of the present application and can be implemented according to the content of the specification, the following will be described in detail with the preferred embodiments of the present application and with the help of the accompanying drawings.

[0019] Figure 1 The above description is only a summary of the technical scheme of the present application. In order to more clearly understand the technical means of the present application and can be implemented according to the content of the specification, the following will be described in detail with the preferred embodiments of the present application and with the help of the accompanying drawings. Figure 2 The above description is only a summary of the technical scheme of the present application. In order to more clearly understand the technical means of the present application and can be implemented according to the content of the specification, the following will be described in detail with the preferred embodiments of the present application and with the help of the accompanying drawings. Figure 3 The above description is only a summary of the technical scheme of the present application. In order to more clearly understand the technical means of the present application and can be implemented according to the content of the specification, the following will be described in detail with the preferred embodiments of the present application and with the help of the accompanying drawings. DETAILED DESCRIPTION

[0020] The embodiment of the application provides an ecological slope protection instability early warning method and system, solves the technical problem that the existing ecological slope protection instability early warning system only considers the influence of a single factor on slope instability in use, and the early warning accuracy is low; some systems consider multiple factors, but do not deeply analyze the synergistic effect between factors, and it is difficult to accurately reflect the actual stability state of the slope; the soil stability degree numerical calculation adopts a soil mechanical property dynamic attenuation model, which is consistent with the actual situation of soil change over time; the hydrological influence degree numerical calculation combines the differentiating weights of different stages of hydrological cycle, and can accurately reflect the influence difference of different hydrological stages; the vegetation slope fixation effect numerical calculation integrates the root system slope fixation capacity dynamic change curve, and accurately reflects the slope fixation change in the vegetation growth period; the position movement danger degree numerical calculation adopts a space-time evolution rule analysis method, and comprehensively considers the correlation of monitoring points, these measures make the calculation of the characteristic value of each factor more consistent with the actual situation, improve the accuracy of single factor analysis, and lay a solid foundation for subsequent comprehensive early warning.

[0021] Embodiment: as shown in the Figure 1 Figure 3 The technical scheme in the embodiment of the application is to solve the technical problem that the existing ecological slope protection instability early warning system only considers the influence of a single factor on slope instability in use, and the early warning accuracy is low; some systems consider multiple factors, but do not deeply analyze the synergistic effect between factors, and it is difficult to accurately reflect the actual stability state of the slope; the overall idea is as follows: As an important means combining engineering measures and ecological restoration technology, ecological slope protection has significant advantages in soil and water conservation, slope stability and ecological protection; however, in the long-term use process, the ecological slope protection is easily affected by the comprehensive influence of many factors such as soil property change, hydrological condition fluctuation, vegetation growth condition change and slope position movement, and has instability hidden danger; once instability occurs, not only the local ecological environment will be destroyed, but also geological disasters such as landslide and debris flow may be caused, which seriously threatens the life and property safety of the surrounding residents; for example, in a certain area, the ecological slope protection is unstable due to heavy rain, which causes landslide disaster and causes road interruption and partial house damage.

[0022] In view of the problems in the prior art, the application provides an ecological slope protection instability early warning method, and the specific content of the early warning method is as follows: (1) Information collection: Collect monitoring information of the area where the ecological slope protection is located, including soil related information, hydrological related information, vegetation related information and position movement related information; in order to ensure the comprehensiveness and accuracy of the information, the information is collected synchronously in time and space through monitoring equipment of different principles.

[0023] ​The sensor for monitoring the soil can be selected from a resistance type soil moisture sensor, a soil compactness meter, etc., to obtain information such as the water content ratio of the soil and the soil compactness, wherein the resistance type soil moisture sensor converts the water content ratio of the soil by measuring the resistance value of the soil, and the soil compactness meter measures the soil compactness data accurately by using the impact method. The device for monitoring the hydrology can be selected from a water level gauge, a flow velocity meter, a pressure sensor, etc., to obtain data such as the water height, the water flow velocity, and the water flow impact force; the water level gauge uses the ultrasonic principle, and the measurement range is 0-10 m; the flow velocity meter is an electromagnetic flow velocity meter, and the measurement range is 0.05-10 m / s; and the pressure sensor is installed on the water-facing surface of the slope to directly measure the water flow impact force, and the measurement range is 0-100 N / m. 2 ; The device for observing the vegetation can use a drone remote sensing device and a vegetation coverage measuring instrument to record the vegetation coverage area ratio and the vegetation growth vigor index; the drone remote sensing device is equipped with a high-definition camera and a multi-spectral sensor to obtain high-resolution vegetation images, and the vegetation coverage area ratio is obtained through image analysis; and the vegetation coverage measuring instrument calculates the growth vigor index by measuring the specific wavelength light reflected by the vegetation, and the measurement range is 0-100. The instrument for tracking the position movement can use a total station and a GPS positioning device to capture three-dimensional space position coordinates; the total station has a measurement accuracy of ±2 mm+2 ppm, and the GPS positioning device uses differential positioning technology.

[0024] The synchronous acquisition is achieved by implanting a time synchronization module, also known as a synchronous clock, in each monitoring device, which can be any module with the same function, not limited to the time synchronization module given above; the time synchronization module is used to ensure that the time references of all devices are consistent, with an error of less than 1 second; at the same time, the spatial coordinates of each monitoring point are pre-set to realize spatial matching of the data, so that the data collected by different devices can correspond to the same spatial position; the layout density of the monitoring devices is determined according to the length and complexity of the slope, and generally one monitoring point is arranged every 5-10 meters, and the installation point is generally a street lamp beside the slope protection.

[0025] Taking an ecological slope protection beside a mountainous road as an example, the length of the ecological slope protection is about 200 meters, the slope is 30°, the main soil type is loam, the vegetation is mainly composed of local common herbaceous plants and shrubs, and there is a seasonal small stream at the bottom of the slope; one monitoring point is arranged every 8 meters in the ecological slope protection area, and a total of 25 monitoring points are arranged; each monitoring point is equipped with the above-mentioned monitoring devices, the time references of the devices are ensured to be consistent through the time synchronization module, and the spatial matching is realized by pre-entering the longitude, latitude, and altitude information of each monitoring point; it is assumed that the ecological slope protection is monitored in July, the summer, and the wet season, and some key data obtained are as follows: Soil-related information: the current soil water content is 28%, the standard soil water content is 22%, which is the historical average value, and the soil density is 1.4 g / cm 3 , and the soil organic matter content is 4%; Hydrological-related information: the current water height is 1.2 m, the water height 1 hour ago was 0.8 m, the current water flow speed is 1.5 m / s, the water flow speed 1 hour ago was 1.2 m / s, the water flow impact force is 6 N / m 2 , and the water pH value is 6; Vegetation-related information: the vegetation coverage area accounts for 65%, the vegetation coverage area in the same period in the past accounts for 58%, the plant root system distribution density is 0.7, the vegetation growth vigor index is 75, and the number of vegetation species is 6; Location movement-related information: the location movement distance calculated by the three-dimensional spatial position coordinates of the adjacent time points is 0.6 m, the interval is 1 hour, the spatial distribution density of the monitoring points is high, the location movement acceleration is 0.08 m / s 2 , and the location movement direction mutation frequency is 1 / h.

[0026] (II) Numerical calculation of soil stability degree: According to the collected soil-related information, the numerical value reflecting the soil stability degree is obtained; in the calculation of the numerical value, a dynamic attenuation model of soil mechanical properties with time is introduced, which is based on soil initial state parameters and long-term monitored attenuation trend, wherein the soil initial state parameters include initial density, initial organic matter content, etc., and the long-term monitored attenuation trend is obtained by fitting the soil parameter monitoring data for many years, which can better fit the actual situation of soil change with time.

[0027] The specific calculation steps are as follows: Extract the current soil water content, standard soil water content, soil density and soil organic matter content from the soil-related information, the standard soil water content is determined by the average value of the historical soil water data of the same period in this area, and the soil-related information is obtained by sampling; Calculate the difference between the current soil water content and the standard soil water content to obtain the soil water content change, and at the same time, correct the change according to the soil organic matter content, the higher the organic matter content, the smaller the correction coefficient; the correction coefficient is obtained by fitting the experimental results, and the correction coefficient decreases by 0.05 for every 1% increase in organic matter content; for the above example of ecological slope protection beside the mountain road, the current soil water content is 28%, the standard soil water content is 22%, the soil water content change = 28%-22%=6%, if the soil organic matter content is 4%, the correction coefficient = 1-4x0.05 = 0.8, the corrected soil water content change = 6% x 0.8 = 4.8%, take 4.8 as the soil water content change; According to the soil density, the soil shear strength correction value is determined by referring to the nonlinear relationship curve between soil density and shear strength; the curve is drawn after indoor test, such as when the density is 1.2 g / cm 3 , the shear strength is 15 kPa, when the density is 1.5 g / cm 3 , the shear strength is 25 kPa, etc.; when the soil density is 1.3 g / cm 3 , the shear strength is 18 kPa, and the corresponding correction value is 0.8; in this example, according to the nonlinear relationship curve between soil density and shear strength, when the soil density is 1.4 g / cm 3 , the corresponding shear strength correction value is 0.85; The continuous duration of the soil water content change exceeding the first specified value is recorded to obtain the duration of the soil water content anomaly, and different cumulative weights are set for the anomaly duration in different seasons; the first specified value is determined according to the soil characteristics and historical instability cases in the region, such as 15% for sandy soil; the weight in the rainy season is 1.2, and the weight in the dry season is 0.8; if the sandy soil has a soil water content change exceeding 15% for 3 days in the rainy season, the weighted anomaly duration is 3 x 1.2 = 3.6 days; in this example, the soil water content change of 6% does not exceed the first specified value of 15% for sandy soil, and the duration of the soil water content anomaly is 0; Finally, the soil water content change, soil shear strength correction value and duration of soil water content anomaly obtained above are substituted into the model formula to obtain a value reflecting the soil stability; the model formula is: soil stability value = (1-soil water content change x 0.02) x soil shear strength correction value ÷ (1+soil water content anomaly duration x 0.1); the value calculated by the formula ranges from 0 to 1, and the closer the value is to 1, the more stable the soil is; using the data obtained in the above example, the soil stability value = (1-4.8 x 0.02) x 0.85 ÷ (1+0 x 0.1) ≈ (1-0.096) x 0.85 ≈ 0.904 x 0.85 ≈ 0.77.

[0028] The soil mechanical property dynamic attenuation model is a core analysis tool for soil stability, mainly used to quantify the change law of soil mechanical properties over time and environmental factors; that is, the shear strength, density, and stability of the soil; it is not a fixed value and will gradually decrease due to external influences, such as increased moisture content due to continuous rainfall, degraded vegetation roots, and long-term load effects; this process of decreasing ability is called attenuation, and dynamic emphasizes its real-time updating characteristics over time and environmental conditions, such as rainfall intensity, temperature, and vegetation coverage changes; The core logic of the model is: Input: soil initial density, real-time moisture content, environmental disturbance intensity, vegetation root support capacity and other parameters; Output: A soil stability value that changes dynamically over time. The lower the value, the higher the risk of instability.

[0029] Its function is to provide a quantitative basis for single factor analysis, so that the system can grasp the changes in the soil's own anti-instability ability in real time, and lay the foundation for subsequent multi-factor collaborative analysis. (III) Numerical calculation of hydrological impact degree: A numerical value reflecting the degree of hydrological influence is obtained based on hydrological related information; the different weights of the effects of different stages of the hydrological cycle on the slope are combined in the calculation process. These weights are determined based on the historical data of regional hydrological characteristics. Among them, the stages include precipitation period, confluence period, dry season, etc. The historical data of hydrological characteristics can be set as needed. Taking the hydrological monitoring data of the past 30 years as an example, the differences in the impact of different hydrological stages on the slope can be reflected.

[0030] The specific steps are as follows: Extract the current water height, current water velocity, water flow impact force, and water pH from the hydrological information; the water flow impact force is directly measured by a pressure sensor or calculated based on the flow velocity and water cross-sectional area, and the water pH is measured using a pH meter; The change in the current water height per unit time is calculated to obtain the amplitude of the water height rise. At the same time, the amplitude is corrected according to the pH value of the water. The greater the pH value deviates from neutral, the greater the correction coefficient is. The correction coefficient corresponding to alkalinity is greater than the correction coefficient of acidity with the same degree of deviation. It can be pre-set. Among them, the pH value deviates from neutral pH=7; for example, when pH=5, the correction coefficient is 1.3, and when pH=9, the correction coefficient is 1.4; the pH value of the water body is 6, which deviates from neutral by 1 unit, and the correction coefficient is 1.1. The corrected rise amplitude = 0.4×1.1=0.44m / h; Calculate the change in the current water flow velocity per unit time to get the water flow velocity change ratio. For example, if the current water flow velocity is 2 m / s and changes to 2.25 m / s after 1 hour, the water flow velocity change ratio is (2.25-2) ÷ 1 × 100% = 25% / h. The water erosion correction coefficient is determined based on the impact force of the water flow and its matching relationship with the erosion resistance of the slope material. The erosion resistance of the slope material is determined by the indoor anti-scour test of the slope material. For example, the erosion resistance of the slope material is determined to be 9N / m 2 , the water flow impact force is 6N / m 2 , water erosion correction coefficient = 6÷9≈0.67.

[0031] The duration of the hydrological condition anomaly is recorded by recording the continuous duration when the water body height rising amplitude exceeds a second specified value or the water flow speed change ratio exceeds a third specified value, the second specified value is 0.5 m / h, and the third specified value is 20% / h; the abnormal time weight in the wet period is 1.3, and the abnormal time weight in the dry period is 0.7; the water body height rising amplitude 0.4 m / h does not exceed the second specified value 0.5 m / h, the water flow speed change ratio 25% / h exceeds the third specified value 20% / h, the abnormal time weight in the wet period is 1.3, and the duration of the hydrological condition anomaly = 1 x 1.3 = 1.3 hours; In combination with different weights of the hydrological cycle stage, for example, the weight of the precipitation period is 0.3, the weight of the confluence period is 0.5, and the weight of the dry period is 0.2, the above data is substituted into the calculation model to obtain the value reflecting the degree of influence of hydrology; the calculation model is: the value of the influence of hydrology = (water body height rising amplitude x 0.4 + water flow speed change ratio x 0.3 + water flow erosion correction coefficient x 0.2 + duration of hydrological condition anomaly x 0.1) x weight of hydrological cycle stage, the value range is 0-1, and the closer the value is to 1, the greater the influence of hydrology on the slope; in July, the hydrological cycle stage weight is 0.4, which is the average of the weights of the precipitation period 0.3 and the confluence period 0.5, and the value of the influence of hydrology = (0.44 x 0.4 + 25% x 0.3 + 0.67 x 0.2 + 1.3 x 0.1) x 0.4 ≈ (0.176 + 0.075 + 0.134 + 0.13) x 0.4 ≈ 0.515 x 0.4 ≈ 0.21.

[0032] (Four) Calculation of the value of the slope fixing effect of vegetation: The value reflecting the fixing effect of vegetation on the slope is obtained according to the vegetation-related information; the dynamic change curve of the fixing ability of the root system of the vegetation in the growth cycle of the vegetation is integrated into the calculation, the curve is drawn by analyzing the correlation between the growth stage of the vegetation and the mechanical properties of the root system, the growth stage of the vegetation includes the seedling stage, the growth stage, the mature stage and the decline stage, and the mechanical properties of the root system are measured by the root system tension test, which can accurately reflect the change of the fixing effect of the root system of the vegetation on the slope in different growth stages.

[0033] Specifically, the following steps are included: The vegetation coverage area proportion, the density of plant root system distribution, the vegetation growth vigor index and the vegetation species diversity in the vegetation-related information are extracted; the vegetation coverage area proportion is obtained by analyzing the unmanned aerial vehicle remote sensing image, the density of plant root system distribution is measured by soil drilling sampling, the vegetation growth vigor index is determined by measuring the chlorophyll content of the vegetation leaves, and the vegetation species diversity is determined by the quadrat method investigation; The difference between the vegetation coverage area ratio and the vegetation coverage area ratio in the same period in the past is the coverage area ratio change amount, and the calculation process takes into account the species diversity coefficient. The higher the diversity, the smaller the weight adjustment coefficient of the change amount. For example, when the number of species is 5, the adjustment coefficient is 0.9, when the number of species is 6, the adjustment coefficient is 0.85, and when the number of species is 9, the adjustment coefficient is 0.7. The specific adjustment coefficient can be preset. If the current vegetation coverage area ratio is 65%, the same period in the past is 58%, the coverage area ratio change amount is 10%, and the number of species is 5, then the adjusted coverage area ratio change amount = 65%-58%=7%. If the number of species is 6 and the adjustment coefficient is 0.85, the adjusted coverage area ratio change amount = 7% x 0.85 = 5.95%, and the value 5.95 is taken as the coverage area ratio change amount. The root system firmness coefficient is determined according to the density of plant root system distribution, vegetation growth vigor index and vegetation species diversity. The contribution of different species of root system is preset according to the actual measurement data of the fixed slope ability. Root system firmness coefficient = (plant root system distribution density x 0.3 + vegetation growth vigor index ÷ 100 x 0.4 + vegetation species diversity x 0.3). For example, the plant root system distribution density is 0.7, the vegetation growth vigor index is 75, and the vegetation species diversity is set to 0.6 when the number of species is 6. The root system firmness coefficient = 0.7 x 0.3 + 75 ÷ 100 x 0.4 + 0.6 x 0.3 = 0.21 + 0.3 + 0.18 = 0.69, wherein 0.3, 0.4 and 0.3 are the weights of plant root system distribution density, vegetation growth vigor index and vegetation species diversity respectively. Combined with the dynamic change curve of root system fixed slope ability in the growth cycle of vegetation, the value reflecting the slope fixation of vegetation is obtained according to the coverage area ratio change amount and the root system firmness coefficient. Vegetation slope fixation value = (1-vegetation coverage area ratio ÷ 100) x root system firmness coefficient x dynamic change curve coefficient. The dynamic change curve coefficient is 0.3 in seedling stage, 0.6 in growth period, 0.9 in mature period and 0.4 in decline period. In July, the vegetation is in growth period, the dynamic change curve coefficient is 0.6, and the vegetation slope fixation value = (1-5.95 ÷ 100) x 0.69 x 0.6 ≈ 0.94 x 0.69 x 0.6 ≈ 0.39.

[0034] (Five) Position movement risk degree value calculation: The value reflecting the position movement risk degree is obtained according to the position movement related information. The analysis method of position movement change rule in time and space is adopted, and the correlation and propagation characteristics of different monitoring point position movement are considered comprehensively, so that the value can better reflect the risk situation of position movement.

[0035] The specific steps are as follows: Extracting the three-dimensional spatial position coordinates of different time points in the position movement related information, the corresponding time records, the position movement acceleration and the mutation frequency of the position movement direction; the position movement acceleration is calculated by the change of the speed of adjacent time points, and the mutation frequency of the position movement direction is the number of times of direction change in a unit time; Calculating the distance of the position movement according to the three-dimensional spatial position coordinates of adjacent time points, and the distance calculation considers the weighted processing of the spatial distribution density of the monitoring points; the weight of the region with high density is 1.1, and the weight of the region with low density is 0.9; if the distance calculated according to the three-dimensional spatial position coordinates of adjacent time points is 0.6 m, the spatial distribution density of the monitoring points is high, and the weighted distance is 0.6*1.1=0.66 m; Calculating the speed of the position movement according to the distance of the position movement and the corresponding time interval; if the distance of the position movement is 0.66 m and the time interval is 1 hour, then the speed of the position movement is 0.66÷1=0.66 m / h; Drawing the path of the position movement according to the distance of the position movement and the time record of multiple time points, and introducing the fractal dimension calculation for the path analysis to quantify the complexity of the path; the greater the fractal dimension, the more complex the path, and the fractal dimension of the position movement path is calculated to be 1.1; Determining the speed of the change of the direction of the position movement according to the bending condition of the position movement path and the mutation frequency of the direction of the position movement; if the mutation frequency of the direction of the position movement is 1 times / h, the bending degree coefficient is taken as 0.2, wherein the greater the bending, the greater the bending degree coefficient, and then the speed of the change of the direction is 1*0.5+0.2=0.7; Combining the analysis method of the change law of the position movement in time and space, substituting the above data into the calculation model to obtain the numerical value reflecting the risk degree of the position movement; the calculation model is: the numerical value of the risk degree of the position movement=(the distance of the position movement*0.3+the fractal dimension*0.2+the speed of the change of the direction of the position movement*0.3+the position movement acceleration*0.2), if the position movement acceleration is 0.08 m / s 2 , then the numerical value of the risk degree of the position movement=(0.66*0.3+1.1*0.2+0.7*0.3+0.08*0.2)=0.198+0.22+0.21+0.016=0.644≈0.64, the numerical value ranges from 0 to 1, and the closer the numerical value to 1, the higher the risk degree of the position movement.

[0036] (Six) Synergistic influence coefficient calculation: The numerical value reflecting the degree of soil stability and the numerical value reflecting the degree of hydrological influence are dynamically correlated to obtain a first synergistic influence coefficient; specifically, an interaction model of the changes of the two over time is established to determine the degree of influence of the change of one on the other, and the model embeds a soil response amplification mechanism under extreme hydrological events to cope with extreme situations; extreme hydrological events such as heavy rain, floods, etc. are identified by setting thresholds such as daily rainfall exceeding 50 mm or water level rise exceeding 1 m; when extreme events occur, the influence weight of soil response is amplified by 1.5 times; for example, the numerical value reflecting the degree of soil stability is 0.77, the numerical value reflecting the degree of hydrological influence is 0.21, and the interaction coefficient is 0.3 in non-extreme hydrological events, then the first synergistic influence coefficient = 0.77 x 0.21 x 0.3 ≈ 0.048; if an extreme hydrological event occurs, the amplified coefficient = 0.77 x 0.21 x 0.3 x 1.5 ≈ 0.073, the larger the coefficient, the more significant the interaction of the two on slope instability.

[0037] The numerical value reflecting the fixing effect of vegetation on the slope and the numerical value reflecting the degree of position movement danger are dynamically correlated to obtain a second synergistic influence coefficient; during the analysis, the critical value of damaged vegetation is included, when the vegetation parameter is lower than the critical value, the influence weight of the position movement parameter is automatically increased to more accurately reflect the influence of the synergistic action of the two on slope instability; the critical value of damaged vegetation is, for example, the vegetation coverage area ratio is less than 30%; it is increased to 1.2 times of the original; for example, the numerical value reflecting the fixing effect of vegetation on the slope is 0.39, the numerical value reflecting the degree of position movement danger is 0.64, when the vegetation parameter is normal and the coverage area ratio is 65%> 30%, the interaction coefficient is 0.2, then the second synergistic influence coefficient = 0.39 x 0.64 x 0.2 ≈ 0.05; if the vegetation parameter is lower than the critical value, the amplified coefficient = 0.39 x 0.64 x 0.2 x 1.2 ≈ 0.06, the larger the coefficient, the more significant the interaction of the two on slope instability.

[0038] (Seven) Comprehensive early warning value calculation: Based on the above obtained various values and synergistic influence coefficients, an adaptive weight adjustment method that can dynamically optimize the influence proportion of each parameter according to the historical early warning accuracy is used to calculate the comprehensive early warning value.

[0039] Specifically, the following steps are included: The first important degree proportion is determined according to the numerical value reflecting the soil stability degree and the first synergistic influence coefficient, and the proportion determination process adopts the fuzzy analytic hierarchy process to process the uncertain relationship between parameters; the fuzzy analytic hierarchy process converts the qualitative parameter relationship into a quantitative weight proportion by constructing a judgment matrix, effectively dealing with the complex interaction between parameters; similarly, the second important degree proportion is determined in combination with the numerical value reflecting the hydrological influence degree and the first synergistic influence coefficient, the third important degree proportion is determined in combination with the numerical value reflecting the vegetation fixation effect on the slope and the second synergistic influence coefficient, and the fourth important degree proportion is determined in combination with the numerical value reflecting the position movement danger degree and the second synergistic influence coefficient; for the above example, the first important degree proportion is 0.2, the second is 0.25, the third is 0.3, and the fourth is 0.25 by the fuzzy analytic hierarchy process in combination with the above numerical values and synergistic influence coefficients. The important degree proportion determination method is based on the fuzzy analytic hierarchy process: The fuzzy analytic hierarchy process (FAHP) converts the qualitative relationship between parameters into quantitative weights to process the uncertain relationship between the four types of parameters (soil, hydrology, vegetation, and position movement) and the synergistic influence coefficient, and the core steps include constructing a hierarchical structure, establishing a fuzzy judgment matrix, calculating a weight vector, and consistency checking.

[0040] In the hierarchical structure setting, the target layer is the ecological slope protection instability risk contribution degree, the criterion layer is the four types of parameters, the soil stability degree A, the hydrological influence degree B, the vegetation slope fixation effect C, and the position movement danger degree D, the correlation factor is the synergistic influence coefficient, the first synergistic coefficient K1 is related to A and B, and the second synergistic coefficient K2 is related to C and D; the relative importance between parameters is represented by a triangular fuzzy number (l, m, u), where l is the minimum value, m is the most likely value, and u is the maximum value; the importance scale reference is (1, 1, 1) for equal importance, (1 / 2, 1, 3 / 2) for slightly important, and (1, 3 / 2, 2) for obviously important; in combination with the example data, A=0.77, B=0.21, C=0.39, and D=0.64; K1=0.048 and K2=0.052, and the judgment matrix is constructed as follows:

[0041] Note: The matrix elements are based on the comprehensive judgment of parameter values and synergistic coefficients, such as the soil stability degree of A being higher and K1 being smaller, and A having weaker influence on B, so A is obviously more important than B.

[0042] The weight calculation steps are as follows: first, perform fuzzy synthesis to calculate the fuzzy weight vector of each parameter, and the formula is: ; in the formula, M iThe fuzzy weight vector of the i-th criterion layer parameter (A, B, C, D) is a triangular fuzzy number (l, m, u), which is used to represent the fuzzy proportion of the parameter in the risk contribution degree; The sum operation is performed on the four triangular fuzzy numbers (l, m, u) in the i-th row of the judgment matrix; wherein, l ij , m ij , and u ij are the minimum value, the most likely value, and the maximum value of the triangular fuzzy number in the j-th column of the i-th row, for example, (3 / 2, 2, 5 / 2) in the B column of the A row, l AB = 3 / 2, m AB = 2, and u AB = 5 / 2; The multiplication operation of the fuzzy number is used to multiply the sum result of the numerator and the inverse operation result of the denominator to obtain the fuzzy weight vector; The double summation is first performed on all 16 triangular fuzzy numbers (l, m, u) in the judgment matrix, and then the inverse operation of the fuzzy number is performed, that is, the reciprocal is taken, as the denominator of the normalization processing, to ensure that the weight sum meets the logical range; wherein, i in the subscripts i, j, and k represents the criterion layer parameter, A = 1, B = 2, C = 3, and D = 4, j and k are matrix row indexes, and the value range is 1-4, which is used to traverse the elements in the judgment matrix; the fuzzy weight of A is (0.28, 0.35, 0.42), the fuzzy weight of B is (0.12, 0.18, 0.24), the fuzzy weight of C is (0.25, 0.32, 0.39), and the fuzzy weight of D is (0.15, 0.21, 0.27); then the centroid method is used to defuzzify, and the formula is: w i = (l i + 2m i + u i ) / 4; wherein, w i is the accurate weight value of the i-th criterion layer parameter, which is the result of the defuzzification processing of the fuzzy weight vector (l, m, u), and is a specific numerical value, which is used for subsequent weight correction; l i , m i , and u i are the minimum value, the most likely value, and the maximum value in the fuzzy weight vector of the i-th parameter, for example, in the fuzzy weight (0.28, 0.35, 0.42) of A, l A = 0.28, m A = 0.35, and u A = 0.42; the coefficients 2 and 4 are because the most likely value m i has higher representativeness in the fuzzy number, so it is given a weight of 2, the total sum of the numerator is divided by 4 to obtain the average value, which is the calculation result of the accurate weight, and the calculation result is w A = 0.35, w B = 0.18, and w C= 0.32, w D = 0.21; finally, the synergy coefficient is introduced to fine-tune the weight, and the formula is: ; in the formula, is the corrected importance proportion of the i-th parameter, which is finally used for comprehensive early warning calculation; w i is the accurate weight value obtained by deblurring formula; K 关联 is the correlation synergy influence coefficient; (1+K 关联 ) is the synergy adjustment term, which amplifies or reduces the weight to reflect the interaction between parameters; is the sum of the correlation parameters (weight x adjustment term), which is used for normalization processing to ensure + + + = 1, wherein A and B are associated with K1 = 0.048, and after correction = 0.20, = 0.25; C and D are associated with K2 = 0.052, and after correction = 0.30, = 0.25.

[0043] An environmental adjustment coefficient is obtained, which includes a seasonal influence coefficient, a terrain influence coefficient, a climate mutation influence coefficient, and a human activity influence coefficient; the seasonal influence coefficient is set according to the difference in the influence of different seasons on the stability of the slope, such as 0.9 in winter and 1.1 in summer; the terrain influence coefficient is determined according to the slope and the complexity of the terrain, and the steep slope is 1.2 and the gentle slope is 0.8; the climate mutation influence coefficient is set for extreme climate events, including cold wave, typhoon, etc., and the coefficient is 1.3 when cold wave occurs; the human activity influence coefficient is determined according to the intensity and frequency of regional engineering activities, such as 1.2 when there are more than 3 engineering activities per day; the environmental adjustment coefficient = seasonal influence coefficient x terrain influence coefficient x climate mutation influence coefficient x human activity influence coefficient: current summer 1.1, slope 30°, steep slope 1.2, no extreme climate event 1.0, engineering activity 1 time per day 1.0, then environmental adjustment coefficient = 1.1 x 1.2 x 1.0 x 1.0 = 1.32; The similar case data in the call history database is compared and corrected to obtain a case correction coefficient; the similar case matching adopts a multi-feature vector cosine similarity calculation method, the cosine similarity of the current monitoring data feature vector and the historical case feature vector is calculated, the cases with higher similarity are screened out, and the case correction coefficient = (cosine similarity in the past 1 year x case weight in the past 1 year + cosine similarity in the past 3 years x case weight in the past 3 years) ÷ (case weight in the past 1 year + case weight in the past 3 years); at the same time, time attenuation weights are set for cases of different time spans, two similar cases are screened out, one in the past 1 year with a similarity of 0.75, and one in the past 3 years with a similarity of 0.65, and the case correction coefficient = (0.75 x 1.0 + 0.65 x 0.8) ÷ (1.0 + 0.8) ≈ (0.75 + 0.52) ÷ 1.8 ≈ 0.706 ≈ 0.71, so as to highlight the reference value of the recent cases.

[0044] The adaptive weight adjustment method is used to calculate the comprehensive early warning value according to the above-mentioned various data; the adaptive weight adjustment method will regularly calculate the early warning accuracy according to the historical early warning data, and dynamically adjust the influence weight of each parameter according to the accuracy, wherein the historical early warning data is, for example, the number of successful early warnings, the number of false alarms, the number of missed alarms, etc.; for example, when it is found that the contribution of soil-related parameters in early warning is low, the weight is automatically reduced, and the weight of other more critical parameters is increased; the calculation formula of the comprehensive early warning value is: comprehensive early warning value = (first important degree proportion x value reflecting the stability of soil + second important degree proportion x value reflecting the influence of hydrology + third important degree proportion x value reflecting the fixing effect of vegetation on slope + fourth important degree proportion x value reflecting the degree of position movement danger) x environmental adjustment coefficient x case correction coefficient x ED, the value range is 0-100, the larger the value, the higher the risk of ecological slope protection instability, and ED is a correction factor, since the calculation result value is small, 100 is used here to correct the calculation result; in this example, the comprehensive early warning value = (0.2 x 0.77 + 0.25 x 0.21 + 0.3 x 0.39 + 0.25 x 0.64) x 1.32 x 0.71 ≈ (0.154 + 0.053 + 0.117 + 0.16) x 1.32 x 0.71 x 100 ≈ 0.49 x 1.32 x 0.71 x 100 ≈ 0.49 x 0.937 x 100 ≈ 0.46 x 100 ≈ 46.

[0045] (Eight) Early warning judgment and response: whether the comprehensive early warning value exceeds the pre-set early warning limit value, the early warning limit value adopts a hierarchical dynamic threshold mechanism and will automatically adjust according to the sensitive level and ecological value of the geographical environment where the slope is located; for example, the high sensitive level is close to the residential area, and the threshold value is set to 80; far away from the residential area is the low sensitive level, and the threshold value is set to 60; in terms of ecological value, the threshold value of the ecological protection area is set to 85, and the threshold value of the ordinary area is set to 70.

[0046] If the comprehensive early warning value exceeds the early warning limit value, it is determined that the ecological slope protection has the possibility of instability, and the graded early warning response measures are started; when the comprehensive early warning value is greater than or equal to 90, the first-level early warning starts the emergency evacuation plan, and organizes professional personnel to carry out on-site rescue; when 80 is less than the comprehensive early warning value and less than 90, the second-level early warning strengthens the monitoring frequency, monitors once an hour, and prepares emergency materials; when the early warning limit value is less than or equal to the comprehensive early warning value and less than 80, the third-level early warning increases the number of patrols, and closely observes the changes of the slope; at the same time, the first and second synergistic influence coefficients are used to determine the key areas of early warning, and the areas with high coefficients are the key areas, and a visual early warning report containing emergency disposal priority and specific prevention and control suggestions is generated for the key areas; the emergency disposal priority is sorted from high to low according to the synergistic influence coefficient, and the specific prevention and control suggestions are, for example, preferential reinforcement, setting drainage facilities, and re-planting vegetation.

[0047] If the comprehensive early warning value does not exceed the early warning limit value, it is determined that the ecological slope protection is in a stable state, the original monitoring time interval is maintained, the monitoring is carried out once a day, and the monitoring data and analysis results of this time are stored in the historical database; an incremental learning method of only training new data to improve the adaptability of the model is used for model optimization, and the incremental learning method can update the model parameters using new data without retraining the entire model, thereby improving the adaptability of the model to new environments and new situations.

[0048] For the above example of the ecological slope protection beside the mountainous highway, the ecological slope protection is located in an ordinary area and far away from the residential area, and the early warning limit value is 60; the comprehensive early warning value is 46, which does not exceed the early warning limit value, and it is determined that the ecological slope protection is in a stable state; the frequency of monitoring once a day is maintained, and the monitoring data and analysis results of this time are stored in the historical database, and the incremental learning method is used to optimize the model to improve the accuracy and adaptability of subsequent early warning.

[0049] All the above weights are model parameters obtained by multiple linear regression analysis on historical monitoring data or by training using machine learning algorithms such as gradient boosting trees, to reflect the contribution of each parameter to the stability of the soil, and can also be pre-set.

[0050] Finally, it should be noted that the above embodiments are merely intended for the purpose of illustration, and are not intended to limit the present application. Based on the above description, those skilled in the art can make other variations or modifications of the present application in different forms. Here, it is not necessary or possible to enumerate all the embodiments. The obvious variations or modifications derived therefrom are still within the scope of the present application.

Claims

1. An ecological slope protection instability early warning method, characterized in that, The early warning method comprises: Collecting monitoring information of the area where the ecological slope protection is located, wherein the monitoring information comprises soil information, hydrological information, vegetation information and location movement information; According to the soil information, a value reflecting the soil stability degree is obtained, and a dynamic attenuation model of soil mechanical properties with time is introduced to quantify the changes of soil mechanical properties with time and environmental factors, which is constructed based on the initial state parameters of the soil and the long-term monitored attenuation trend; According to the hydrological information, a value reflecting the hydrological influence degree is obtained; According to the vegetation information, a value reflecting the fixing effect of the vegetation on the slope is obtained; According to the location movement information, a value reflecting the location movement danger degree is obtained; The value reflecting the soil stability degree and the value reflecting the hydrological influence degree are dynamically correlated and analyzed to obtain a first synergistic influence coefficient; The value reflecting the fixing effect of the vegetation on the slope and the value reflecting the location movement danger degree are dynamically correlated and analyzed to obtain a second synergistic influence coefficient; The value reflecting the soil stability degree, the value reflecting the hydrological influence degree, the value reflecting the fixing effect of the vegetation on the slope, the value reflecting the location movement danger degree, the first and second synergistic influence coefficients are combined to calculate a comprehensive early warning value, and it is judged whether the comprehensive early warning value exceeds a warning limit value. 2.The ecological slope protection instability early warning method according to claim 1, characterized in that, The step of obtaining the value reflecting the soil stability degree according to the soil information comprises: Extracting the current soil water content ratio, the standard soil water content ratio, the soil density and the soil organic matter content in the soil information; Calculating the difference between the current soil water content ratio and the standard soil water content ratio to obtain a soil water content ratio change amount; determining a soil shear strength correction value according to the soil density; recording the continuous duration that the soil water content ratio change amount exceeds a first specified value to obtain the duration of soil water content ratio anomaly; and using the soil water content ratio change amount, the soil shear strength correction value and the duration of soil water content ratio anomaly, and combining the dynamic attenuation model of soil mechanical properties, the value reflecting the soil stability degree is obtained.

3. The ecological slope protection instability early warning method according to claim 1, characterized in that, The step of obtaining the value reflecting the hydrological influence degree according to the hydrological information comprises: Extracting the current water body height, the current water flow speed, the water flow impact force and the water body pH value in the hydrological information; Calculating the change amount of the current water body height per unit time to obtain a water body height rising amplitude; calculating the change amount of the current water flow speed per unit time to obtain a water flow speed change ratio; determining a water flow erosion correction coefficient according to the matching relationship between the water flow impact force and the erosion resistance of the slope material; recording the continuous duration that the water body height rising amplitude exceeds a second specified value or the water flow speed change ratio exceeds a third specified value to obtain the duration of hydrological anomaly, and recording the abnormal time weight of the process distinguishing between the wet period and the dry period; and using the water body height rising amplitude, the water flow speed change ratio, the water flow erosion correction coefficient and the duration of hydrological anomaly, and combining the different weights of the hydrological cycle stages, the value reflecting the hydrological influence degree is obtained.

4. The ecological slope protection instability early warning method according to claim 1, characterized in that, The step of obtaining the value reflecting the fixing effect of the vegetation on the slope according to the vegetation information comprises: Extracting the vegetation coverage area proportion, the plant root system distribution density, the vegetation growth vigor index and the vegetation species diversity in the vegetation information; The difference between the vegetation coverage area ratio and the vegetation coverage area ratio in the same period in the past is calculated to obtain the coverage area ratio change amount; the root system distribution density, vegetation growth vigor index, and vegetation species diversity are used to determine the root system firmness coefficient; and the coverage area ratio change amount and the root system firmness coefficient are combined with the vegetation growth cycle root system slope fixation ability dynamic change curve to obtain the value reflecting the slope fixation effect of the vegetation.

5. The ecological slope protection instability early warning method of claim 1, wherein, The step of obtaining the value reflecting the position movement danger degree according to the position movement information comprises: extracting the three-dimensional space position coordinates, corresponding time records, position movement acceleration, and position movement direction mutation frequency at different time points in the position movement information; calculating the position movement distance according to the three-dimensional space position coordinates at adjacent time points, and the distance calculation considers the spatial distribution density of the monitoring points for weighted processing; then, the position movement speed is calculated according to the position movement distance and the corresponding time interval; the position movement path is drawn by using the position movement distance and the time records at multiple time points; the position movement direction change speed is determined by the bending situation of the position movement path and the position movement direction mutation frequency; and the value reflecting the position movement danger degree is obtained according to the position movement distance, the position movement speed, the position movement direction change speed, and the position movement acceleration.

6. The ecological slope protection instability early warning method of claim 1, wherein, The step of synthesizing the early warning value comprises: determining a first importance degree proportion by using the value reflecting the soil firmness degree and the first synergistic influence coefficient; determining a second importance degree proportion by using the value reflecting the hydrological influence degree and the first synergistic influence coefficient; determining a third importance degree proportion by using the value reflecting the slope fixation effect of the vegetation and the second synergistic influence coefficient; and determining a fourth importance degree proportion by using the value reflecting the position movement danger degree and the second synergistic influence coefficient; obtaining an environmental adjustment coefficient; calling similar case data in a historical database for comparison and correction to obtain a case correction coefficient, and using a multi-feature vector cosine similarity calculation method for similar case matching, and setting time attenuation weights for cases of different time spans; synthesizing the early warning value by using the value reflecting the soil firmness degree, the value reflecting the hydrological influence degree, the value reflecting the slope fixation effect of the vegetation, the value reflecting the position movement danger degree, the first and second synergistic influence coefficients, the first to fourth importance degree proportions, the environmental adjustment coefficient, and the case correction coefficient after adaptive weight adjustment.

7. The ecological slope protection instability early warning method of claim 1, wherein, The step of obtaining the first synergistic influence coefficient by dynamically correlating the value reflecting the soil firmness degree and the value reflecting the hydrological influence degree comprises: establishing a first sequence of values reflecting the degree of soil stability over time and a second sequence of values reflecting the degree of hydrological influence over time; determining the time nodes and the amplitude of the changes in the values in the two sequences; analyzing the degree of influence of the changes in the values in the first sequence on the changes in the values in the second sequence and the degree of influence of the changes in the values in the second sequence on the changes in the values in the first sequence within the same time interval; introducing an extreme hydrological event identification mechanism, when an extreme hydrological event is monitored, amplifying the influence weight of the soil response according to a preset rule; and calculating the first synergistic influence coefficient according to the analysis results. 8.The ecological slope protection instability early warning method of claim 1, wherein, The steps of dynamically correlating the values reflecting the fixing effect of the vegetation on the slope and the values reflecting the degree of position movement danger to obtain the second synergistic influence coefficient include: establishing a third sequence of values reflecting the fixing effect of the vegetation on the slope over time and a fourth sequence of values reflecting the degree of position movement danger over time; setting a critical value of the vegetation damage, when the value in the third sequence is lower than the critical value, marking the vegetation protection capability as being in a decline stage; analyzing the mutual influence relationship between the changes in the values in the third sequence and the changes in the values in the fourth sequence in the vegetation protection capability normal stage; increasing the weight of the changes in the values in the fourth sequence in the correlation analysis in the vegetation protection capability decline stage; and comprehensively calculating the second synergistic influence coefficient according to the analysis results in different stages.

9. An ecological slope protection instability early warning system, characterized in that, The steps include: an information collection part for collecting monitoring information of the area where the ecological slope protection is located, wherein the monitoring information includes soil information, hydrological information, vegetation information and position movement information; an analysis and processing part for processing and analyzing the collected monitoring information to obtain values reflecting the degree of soil stability, values reflecting the degree of hydrological influence, values reflecting the fixing effect of the vegetation on the slope, values reflecting the degree of position movement danger, first and second synergistic influence coefficients, and calculating a comprehensive early warning value by combining the values; an early warning judgment part for judging whether the comprehensive early warning value exceeds a warning limit value, and executing corresponding early warning response measures or maintaining the original monitoring state according to the judgment result, and generating an early warning report or updating a historical database for model optimization.

10. The ecological slope protection instability early warning system of claim 9, wherein, The analysis and processing part includes: a soil information analysis unit for obtaining values reflecting the degree of soil stability according to the soil information, wherein the unit is internally provided with a dynamic attenuation model of soil mechanical properties over time, and can automatically call historical data to update model parameters; a hydrological information analysis unit for obtaining values reflecting the degree of hydrological influence according to the hydrological information; a vegetation information analysis unit for obtaining values reflecting the fixing effect of the vegetation on the slope according to the vegetation information; a position movement information analysis unit for obtaining values reflecting the degree of position movement danger according to the position movement information; a synergistic analysis unit for dynamically correlating the values reflecting the degree of soil stability and the values reflecting the degree of hydrological influence to obtain the first synergistic influence coefficient, and dynamically correlating the values reflecting the fixing effect of the vegetation on the slope and the values reflecting the degree of position movement danger to obtain the second synergistic influence coefficient. The comprehensive early warning calculation unit is used for calculating the comprehensive early warning value by combining the above-mentioned various values and coefficients, and the adaptive weight adjustment method of the integrated dynamic optimization calculation model can be adjusted according to the historical early warning accuracy.

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