Urban slope stability characteristic analysis method and system based on block sliding risk

Abstract

The present application belongs to the technical field of geological disasters, and discloses a kind of urban slope stability characteristic analysis method and system based on block sliding risk, the stability characteristics of each station are calculated based on plane sliding method by measuring its slope size, soil and vegetation characteristics and other data, and the relationship between stability coefficient and each sensitive factor is analyzed, the research results show that: the slope stability coefficient of each sampling point is basically above 1.0, and the landslide risk is extremely small;Soil cohesion is the largest in maintaining the contribution of slope stability, and it is also the most sensitive to slope stability coefficient;Soil moisture content can reduce the slope stability coefficient from increasing soil weight, reducing soil cohesion and other aspects;Soil root density can enhance the overall stability of slope body from enhancing the shear strength of soil, reducing soil erosion and other aspects. Using vegetation concrete and other technologies to reinforce soil, while increasing the vegetation coverage of slope, regularly monitoring the risk of slope state is a good way to reduce the landslide risk.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of geological disasters, and particularly relates to a city slope stability feature analysis method and system based on block sliding risk. BACKGROUND

[0002] With the acceleration of global urbanization and the increasing of human engineering activities, if the left-over slope after land excavation in urban construction is not properly handled, slope instability will occur from time to time, causing economic losses and casualties of different degrees. There are many factors that cause slope instability, mainly including natural factors such as rainfall, earthquakes, weathering, and human activities such as mining and road construction. Under the background of global climate change, extreme climate events such as rainstorms and droughts will have a complex impact on slope stability, increasing the occurrence of secondary disasters such as landslides and mudslides. Through the research and evaluation of slope stability characteristics, various disasters caused by slope instability can be effectively prevented and mitigated, the safety of human activities and the sustainability of economic development can be ensured, and scientific basis can be provided for mining planning, engineering design in urban construction, etc., which has important research significance.

[0003] Slope stability is affected by many natural and human factors, among which vegetation and rainfall are two key natural factors. The root structure of vegetation plays an important stabilizing role in slope by increasing the shear strength of soil and reducing surface erosion. Studies have found that different types of vegetation have different effects on improving soil stability, and the deep root system of trees is more effective than the shallow root system of herbaceous plants in enhancing soil cohesion. In addition, vegetation cover can effectively reduce surface runoff and rainfall infiltration, reducing the risk of slope landslide. Rainfall is one of the main natural factors that induce slope instability, and some studies have found that rainfall intensity and duration have an impact on soil pore water pressure and slope stability through field observation and numerical simulation. During the rainfall process, the saturation of soil increases, leading to an increase in pore water pressure and a decrease in effective stress of soil, thereby reducing the stability of the slope. Some researchers have developed a variety of rainfall-induced landslide warning systems that monitor rainfall, soil moisture, and other parameters to assess the risk of slope instability in real time. The calculation and evaluation methods of slope stability mainly include the limit equilibrium method based on theoretical analysis and the finite element method based on numerical simulation. The limit equilibrium method calculates the safety factor of the slope by analyzing the mechanical equilibrium state of the potential sliding surface, while the finite element method uses numerical simulation technology to more accurately simulate the slope stability under complex geological conditions. In addition, emerging three-dimensional numerical simulation technology and machine learning-based prediction models have been widely applied in slope stability evaluation.

[0004] Through the above analysis, the problems and defects of the prior art are:

[0005] The existing technology cannot analyze in time, leading to landslide disasters. SUMMARY

[0006] In view of the problems in the prior art, the present application provides a city slope stability characteristic analysis method based on block sliding risk.

[0007] The present application is implemented in a city slope stability characteristic analysis method based on block sliding risk, which comprises:

[0008] Step 1, by measuring the size of the slope, soil and vegetation characteristic data, the stability characteristics of each station are calculated based on the plane sliding method;

[0009] Step 2, analyze the relationship between the stability coefficient and each sensitive factor.

[0010] Further, the method of measuring the size of the slope, soil and vegetation characteristic data is as follows:

[0011] For each slope, the main sampling or measurement indexes include: the geometric size of the slope body, soil characteristics and vegetation characteristics data;

[0012] The geometric size of the slope body is directly measured on site; the soil moisture content is measured by the tensiometer method, and the measured pore water pressure is converted to the mass moisture content of the soil by a theoretical formula;

[0013] The soil type ratio and the volume ratio of the vegetation root in the soil are estimated by the method of field sampling and laboratory screening; the dominant vegetation ratio is estimated by the field quadrat investigation method, that is, a representative 1m 2 square is selected, and then the growth area ratio of different types of vegetation is measured.

[0014] Further, the method of calculating the stability characteristics of each station based on the plane sliding method is as follows:

[0015] The plane sliding method is mainly used to analyze the stability characteristics of different types of soil or sand along the approximate plane sliding surface; its stability coefficient Fs can be expressed as the ratio between the shear strength R of the potential landslide body and the sliding force T under the action of gravity, that is,

[0016]

[0017] In the formula, c represents the effective cohesion coefficient of soil, with the unit of kPa, which is estimated in the model according to the effective cohesion of different types of soil and the proportion of soil types at the survey point; L represents the length of the sliding surface, with the unit of m; W represents the gravity of the landslide body, with the unit of kN, which is calculated by the length L and the height H of the potential landslide body, including the soil and interstitial water of the landslide body; alpha represents the angle between the sliding surface L and the horizontal plane, with the unit of radian; Pwp represents the pore water pressure on the sliding surface, with the unit of kPa, which is related to the water content m of the soil; gamma represents the effective internal friction angle of the soil, with the unit of radian, which is estimated according to the effective internal friction angle of different types of soil and the proportion of soil types at the survey point; cr represents the reinforcement coefficient of the root system, that is, the contribution of the vegetation root system to the stability of the slope body, and the calculation method thereof is as follows,

[0018]

[0019] In the formula, RAR represents the root volume ratio, which is dimensionless; Root growth angle represents the angle of the root growth angle relative to the sliding surface, with the unit of radian, and in the present application, the average growth angle of the root is assumed to be perpendicular to the downward direction, so that T r Root destruction strength represents the root destruction strength, with the unit of kPa, and the calculation method thereof is as follows: first, the proportion of the first three dominant vegetation at the sampling point is determined RV; then, the root destruction strength TrV of each dominant vegetation is measured by a tensile test, that is, the ratio of the maximum tensile force that the root can bear to the root diameter; finally, the area proportion coefficient AR of the vegetation is considered, that is,

[0020] T r = AR·∑RV·TrV#(3)

[0021] According to the above calculation method, the stability coefficient can be actually divided into three parts, that is,

[0022] Fs = Fs c + Fs w + Fs t #(4)

[0023] Among them, Fs represents the contribution of the soil cohesion to the stability, Fs represents the contribution of the self-weight of the slope body to the stability, Fs represents the contribution of the vegetation coverage and the root system to the stability.

[0024] Another object of the present application is to provide a city slope stability feature analysis system based on block sliding risk, which comprises:

[0025] A measurement module is used for measuring the size of the slope, the soil and vegetation characteristic data, and calculating the stability features of each station based on the plane sliding method.

[0026] An analysis module is configured to analyze the relationship between the stability coefficient and each sensitive factor.

[0027] Another object of the present application is to provide a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to enable the processor to perform the steps of the urban slope stability feature analysis method based on block sliding risk.

[0028] Another object of the present application is to provide a computer readable storage medium storing a computer program, and the computer program is executed by a processor to enable the processor to perform the steps of the urban slope stability feature analysis method based on block sliding risk.

[0029] Another object of the present application is to provide an information data processing terminal for implementing the urban slope stability feature analysis system based on block sliding risk.

[0030] Another object of the present application is to provide an urban slope stability analysis system based on block sliding risk, characterized in that the system comprises:

[0031] A data acquisition module is configured to acquire geometric size, soil property and vegetation property data of the slope, including soil water content, soil type, vegetation root volume ratio and dominant vegetation ratio, etc.

[0032] A calculation module is configured to calculate the stability coefficient of the slope based on the plane sliding method, and determine the contribution of soil cohesion, slope self-weight, vegetation root system, etc. to stability.

[0033] An analysis module is configured to analyze the relationship between the slope stability coefficient and each sensitive factor, and predict the potential landslide risk of the slope.

[0034] Another object of the present application is to provide an urban slope stability measurement device, characterized in that it comprises:

[0035] A tensiometer sensor is configured to measure the pore water pressure in the slope soil and convert the soil mass water content through a theoretical formula.

[0036] A sampling device is configured to collect soil samples and vegetation root system samples, and determine the soil type ratio and vegetation root volume ratio.

[0037] A data processing module is configured to perform real-time analysis on the measurement data, and provide real-time evaluation of the slope stability and sliding risk.

[0038] Another object of the present application is to provide a device for predicting the risk of landslides in urban slopes, characterized in that it comprises:

[0039] a slope geometry measurement module for determining the length, height and slope of the slope;

[0040] a soil and vegetation characteristics detection module for analyzing the cohesion coefficient, internal friction angle of the soil and the reinforcement coefficient of the vegetation roots;

[0041] a landslide stability calculation module for calculating the stability coefficient of the slope according to the measurement data using the plane sliding method and outputting the stability analysis result for predicting the risk of landslides.

[0042] In combination with the above technical solutions and the technical problems solved, the technical solution to be protected by the present application has the following advantages and positive effects:

[0043] Firstly, the present application calculates the stability characteristics of each slope using the plane sliding method and analyzes the relationship between the slope stability and sensitive factors such as soil cohesion, soil moisture content and vegetation root characteristics. The following conclusions are obtained.

[0044] (1) The slope stability coefficient of each sampling point is basically above 1.0, indicating that the risk of landslides is extremely small;

[0045] (2) The contribution of soil cohesion to maintaining slope stability is the largest, and after the soil cohesion coefficient is improved by 20%, the stability coefficient can be improved by 31.2% at most;

[0046] (3) Soil moisture content increases the self-weight of the soil and reduces the soil cohesion, thus being basically negatively correlated with the slope stability coefficient;

[0047] (4) The soil root density can improve the overall stability of the slope by enhancing the shear strength of the soil and reducing soil erosion.

[0048] Secondly, the urban slope stability characteristic analysis method based on block sliding risk provided by the present application solves a plurality of key problems in the prior art and achieves significant technical progress in industrial application.

[0049] Problems in the prior art:

[0050] 1. The data collection is not comprehensive: traditional slope stability analysis methods usually rely on limited geological survey data, ignoring factors such as vegetation coverage, soil moisture content, which have an important influence on slope stability, resulting in lack of comprehensiveness and accuracy of the analysis results.

[0051] 2. Analysis method is single and lacks accuracy: Most existing slope stability analysis methods use simplified models and ignore in-depth analysis of sensitive factors, making it difficult to accurately reflect the actual stability of the slope, especially in complex urban environments, leading to ineffective prediction and prevention of potential landslide risks.

[0052] 3. Lack of comprehensive evaluation of influencing factors: Traditional methods often fail to systematically analyze and quantify the factors affecting slope stability, making it difficult to provide targeted recommendations for slope management and affecting the scientificity and effectiveness of slope protection measures.

[0053] Technical progress of the present invention:

[0054] 1. Comprehensive data collection and processing: The present invention measures various factors such as slope size, soil properties, and vegetation coverage to form a comprehensive data set, providing rich basic data for slope stability analysis. Through comprehensive processing of these data, the accuracy of slope stability analysis is significantly improved.

[0055] 2. Application of multi-factor analysis model: The present invention uses the plane sliding method combined with multi-sensitive factor analysis to conduct detailed calculation and evaluation of slope stability. By quantitatively analyzing the relationship between stability coefficient and sensitive factors, the influence of each factor on slope stability is clarified, enabling more accurate identification of high-risk areas.

[0056] 3. Strongly instructive slope management measures: Based on the analysis results of sensitive factors, the present invention can provide targeted slope management recommendations such as improving drainage systems and increasing vegetation coverage, greatly enhancing the scientificity and effectiveness of slope management and reducing the probability of landslide and other geological disasters.

[0057] 4. Efficient and practical urban application: This method is particularly suitable for complex urban environments, enabling rapid and efficient analysis of urban slope stability and providing decision support for urban planning and construction engineering. Compared with traditional methods, the accuracy and reliability of slope stability analysis are significantly improved, helping to ensure the safety and sustainability of urban infrastructure.

[0058] In summary, the present invention has made significant progress in solving the problems of incomplete data collection, single analysis method, and lack of comprehensive evaluation of influencing factors in existing technology, providing a more scientific, comprehensive, and effective solution for urban slope stability analysis.

[0059] Third, the expected benefits and commercial value of the technical solution of the present invention after transformation are:

[0060] The present application calculates the stability of the slope by using the block sliding risk, and the expected revenue and commercial value of the converted technical solution mainly reflect in civil engineering and geological disaster prevention, which provides a fast calculation and judgment evaluation method for slope stability. Firstly, in the aspect of civil engineering, the present application can be applied to the slope stability evaluation in highway, railway, water conservancy and other engineering construction, and provides reliable data support for engineering design and construction. Secondly, in the aspect of low-quality disaster, the present application can be used for monitoring and early warning to reduce personnel and property losses when disasters occur.

[0061] The technical solution of the present application fills the technical blank in the industry at home and abroad:

[0062] Compared with the traditional slope stability evaluation method, the present application considers more comprehensive factors by combining the effective cohesion, the self-weight of the slope and the vegetation root reinforcement. Compared with the current popular finite element numerical simulation method, although the calculation accuracy of the present application is not as good as the former, the calculation efficiency is higher, and the present application is suitable for predictive evaluation of a large range of multiple slopes.

[0063] (3) The technical solution of the present application overcomes technical bias:

[0064] The technical solution of the present application overcomes the limitations and bias of the traditional slope stability evaluation method. The traditional method usually focuses on analyzing a single factor, such as the mechanical properties of soil, the geometric shape of the slope or the groundwater conditions, and lacks comprehensive consideration of other important influencing factors. These methods often cannot fully reflect the true stability of the slope and are prone to bias. The present application comprehensively considers the effective cohesion, the self-weight of the slope and the vegetation root reinforcement, and provides a more comprehensive evaluation perspective.

[0065] At the same time, the present application also overcomes the high threshold problem of the modern finite element numerical simulation method. Although the finite element method can provide accurate slope stability analysis, it requires high professional knowledge and modeling skills of the user, and non-professionals are difficult to master. The method of the present application is simple and easy to use, and the evaluation process does not require complex numerical modeling and high-level software support, which reduces the application difficulty, so that non-professional users can also effectively evaluate the slope stability, thereby expanding the application range of the technology.

[0066] Fourthly, the technical solution of the present application solves many problems in the existing city slope stability analysis technology in industrial application, and has made significant technical progress, mainly reflected in the following aspects:

[0067] 1. Precision and comprehensiveness of data collection: Traditional slope stability evaluation methods usually rely on simple geometric measurements and soil analysis, which may overlook the impact of slope vegetation on stability. The invention uses systematic measurement devices to accurately collect slope geometric dimensions, soil properties, and vegetation characteristics data, especially considering the strengthening effect of vegetation roots on slope stability, enhancing the accuracy and completeness of the evaluation.

[0068] 2. Stability calculation based on plane sliding method: The invention uses the plane sliding method, combining soil cohesion, internal friction angle, pore water pressure, and other factors to comprehensively calculate the slope stability coefficient. Compared with traditional methods, the calculation model of the invention refines the contribution of each factor, accurately evaluates the sliding risk of slopes under different conditions, and is especially suitable for urban slope stability analysis under complex geological conditions.

[0069] 3. Real-time monitoring and dynamic adjustment: By introducing a sensor network, slope data can be collected in real time, and real-time analysis and risk prediction of slope stability can be performed through an online calculation module. This real-time monitoring and dynamic adjustment function enables the invention to quickly reflect changes in slope environment, effectively improving the accuracy and emergency handling capability of slope monitoring.

[0070] 4. Multi-factor comprehensive analysis and risk assessment: The invention not only considers the physical properties of the slope, but also includes vegetation roots and hydrological factors in the stability analysis model, greatly enriching the elements of slope sliding risk assessment. Through comprehensive analysis of sensitive factors such as soil moisture content and vegetation roots, high-risk areas can be accurately identified, improving the reliability and scientificity of urban slope protection.

[0071] In summary, the invention significantly improves the precision of data collection, the comprehensiveness and real-time nature of stability evaluation in slope stability analysis, providing more reliable and intelligent technical support for urban construction and slope protection. BRIEF DESCRIPTION OF DRAWINGS

[0072] Figure 1 is the flow chart of the urban slope stability feature analysis method based on block sliding risk provided by the embodiment of the invention.

[0073] Figure 2 is the structural block diagram of the urban slope stability feature analysis system based on block sliding risk provided by the embodiment of the invention.

[0074] Figure 3 is the sampling location distribution map provided by the embodiment of the invention.

[0075] Figure 4 is the potential landslide body schematic diagram considering the strengthening effect of vegetation roots provided by the embodiment of the invention.

[0076] Figure 5 is a slope stability coefficient and contribution ratio chart of each site provided by the embodiment of the present application.

[0077] Figure 6 is a soil cohesion impact on slope stability chart provided by the embodiment of the present application.

[0078] Figure 7 is a soil water content impact on slope stability calculation result chart provided by the embodiment of the present application.

[0079] Figure 8 is a slope stability coefficient of each part of the slope response contribution ratio chart of soil water content provided by the embodiment of the present application.

[0080] Figure 9 is a vegetation root impact on slope stability chart provided by the embodiment of the present application. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the embodiment. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0082] As shown in Figure 1 , the city slope stability feature analysis method based on block sliding risk provided by the embodiment of the present application includes the following steps:

[0083] S101, the stability features of each site are calculated based on the plane sliding method by measuring the size of the slope, soil and vegetation characteristic data;

[0084] S102, the relationship between the stability coefficient and each sensitive factor is analyzed.

[0085] The city slope stability feature analysis method based on block sliding risk provided by the embodiment of the present application first measures the size of the slope, soil and vegetation characteristic data. The measurement process includes accurately collecting factors such as the height, slope, soil type, density, water content and vegetation coverage of the slope. These data provide a basis for subsequent stability calculation, making the calculation result more accurate and reliable.

[0086] Then, the stability features of each site are calculated based on the plane sliding method. The plane sliding method is a classic slope stability analysis method, which calculates the stability coefficient by assuming that the potential sliding surface is a plane and considering the forces acting on the sliding body, including gravity, shear force and water pressure, etc. The coefficient is used to judge the safety of the slope. If the coefficient is lower than a certain critical value, it indicates that the slope has a sliding risk.

[0087] After obtaining the stability characteristics of each site, further analyze the relationship between the stability coefficient and each sensitive factor. The sensitive factors usually include soil type, water content, vegetation coverage, etc. Through statistical analysis and regression analysis, explore the influence degree of each sensitive factor on the stability coefficient, determine which factors have the greatest impact on slope stability, and provide guidance for the management and maintenance of the slope.

[0088] Finally, according to the above analysis results, specific slope management measures are proposed. For example, for the slope with high water content and low vegetation coverage, it is recommended to increase drainage facilities and vegetation restoration to improve the stability of the slope. Through this analysis method, the stability of urban slopes can be effectively evaluated, potential landslide disasters can be prevented, and the safety of urban infrastructure can be ensured.

[0089] The method for measuring the size of the slope, soil and vegetation characteristics data provided by the embodiment of the present application is as follows:

[0090] For each slope, the main sampling or measurement indicators include: the geometric size of the slope body, soil characteristics and vegetation characteristics data;

[0091] Among them, the geometric size of the slope body is directly measured on site; the soil water content is measured by the tensiometer method, and the measured pore water pressure is converted to the mass water content of the soil through a theoretical formula;

[0092] The soil type ratio and the volume ratio of the vegetation roots in the soil are estimated by the method of field sampling and laboratory screening; the dominant vegetation ratio is estimated by the method of field quadrat investigation, that is, a representative 1m 2 square is selected, and then the growth area proportion of different types of vegetation is measured.

[0093] The method for calculating the stability characteristics of each site based on the plane sliding method provided by the embodiment of the present application is as follows:

[0094] The plane sliding method is mainly used to analyze the stability characteristics of different types of soil or sand along the approximate plane sliding surface; its stability coefficient Fs can be expressed as the ratio between the shear strength R of the potential landslide body and the sliding force T under the action of gravity, that is,

[0095]

[0096] In the formula, c represents the effective cohesion coefficient of the soil, in kPa, which is estimated in the model based on the effective cohesion of different soil types and the proportion of soil types at the field survey points; L represents the length of the sliding surface, in meters; W represents the weight of the landslide, in kN, calculated using the length L and height H of the potential landslide body, including both the soil and pore water; α represents the angle between the sliding surface L and the horizontal plane, in radians; Pwp represents the pore water pressure on the sliding surface, in kPa, which is related to the soil moisture content m; γ represents the effective internal friction angle of the soil, in radians, calculated similarly to the effective cohesion, i.e., estimated based on the effective internal friction angle of different soil types and the proportion of soil types at the field survey points; cr represents the root enhancement coefficient, i.e., considering the contribution of vegetation roots to slope stability, and its calculation method is referenced from Stokes as follows.

[0097]

[0098] In the formula, RAR represents the root volume ratio, which is dimensionless; This represents the angle of root growth relative to the sliding surface, in radians. The text assumes the average root growth angle is vertically downwards, so we take... T r The root damage intensity, expressed in kPa, is calculated as follows: First, determine the proportion (RV) of the top three dominant vegetation types at the sampling point. Then, use a tensile test to measure the root damage intensity (TrV) of each dominant vegetation type, which is the ratio of the maximum tensile force the root system can withstand to the root diameter. Finally, consider the vegetation area proportion coefficient (AR).

[0099] T r =AR·∑RV·TrV#(3)

[0100] Based on the calculation method described above, the stability coefficient can actually be divided into three parts, namely...

[0101] Fs = Fs c +Fs w +Fs t #(4)

[0102] in This indicates the contribution of soil cohesion to stability. This indicates the contribution of the slope's own weight to its stability. This indicates the contribution of vegetation cover and root system to stability.

[0103] like Figure 2 As shown in the figure, an urban slope stability characteristic analysis system based on block slippage risk provided by an embodiment of the present invention includes:

[0104] A measuring module is configured to measure the size of the slope, soil and vegetation characteristics data, and calculate the stability characteristics of each station based on the plane sliding method;

[0105] An analyzing module is configured to analyze the relationship between the stability coefficient and each sensitive factor.

[0106] Another object of the present application is to provide a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to enable the processor to perform the steps of the urban slope stability characteristic analysis method based on block sliding risk.

[0107] Another object of the present application is to provide a computer readable storage medium storing a computer program, and the computer program is executed by a processor to enable the processor to perform the steps of the urban slope stability characteristic analysis method based on block sliding risk.

[0108] Another object of the present application is to provide an information data processing terminal for implementing the urban slope stability characteristic analysis system based on block sliding risk.

[0109] The present application is specifically implemented as follows:

[0110] 1. The present application selects a plurality of slopes after land excavation in Chongqing urban construction as the research object, adopts the plane sliding method considering the self-weight of the landslide body and the root reinforcement coefficient, analyzes and calculates the stability of each slope, evaluates the stability of each slope, and discusses the potential influence of soil characteristics, rainfall, vegetation and other influencing factors on the stability of the landslide body. The research results of the paper can provide technical support for the geological safety, ecological protection and other problems of the slope after urban construction excavation.

[0111] 2. Research area overview

[0112] Chongqing is located in the transition zone between the Qinghai-Tibet Plateau and the eastern plain of the Yangtze River in China, specifically in the hilly area on the eastern edge of the Sichuan Basin. The main urban area of Chongqing is a typical mountain city, mainly located on the southern edge of the Dabashan, connected to the Zhongliangshan in the west and the Nanshan in the east, with the main stream of the Yangtze River and the tributaries of the Jialing River passing through. The strata of Chongqing are mainly sandstone and mudstone, and under the influence of the rainy summer of the tropical monsoon climate, geological disasters such as landslides and bank collapses frequently occur in Chongqing.

[0113] 2.1 Data source The present application takes the main urban area of Chongqing as an example, selects 11 typical slopes in Yuzhong District, Jiangbei District and other 8 main urban areas according to the actual situation during the sampling period to evaluate their stability characteristics. The positions of each slope are shown in Figure 3As shown, for each slope, the main sampling or measurement indicators include: the geometric size of the slope body, soil properties and vegetation characteristics, and the position and main measurement data of each measurement point are shown in Table 1. The geometric size of the slope body is directly measured on site; the soil moisture content is measured by the tensiometer method (TEROS21), and the measured pore water pressure is converted to the mass moisture content of the soil through a theoretical formula

[23] ; the soil type ratio and the root volume ratio in the soil are estimated by the field sampling and laboratory screening method; the dominant vegetation ratio is determined by the field quadrat investigation method, that is, a representative 1m2quadrat is selected, and then the growth area ratio of different types of vegetation is measured.

[0114] Table 1 Basic information and main measurement data of each sampling point

[0115]

[0116]

[0117] 2.2 Research method The high and steep slope formed by soil and gravel accumulated after urban construction excavation often has safety risks due to the existence of sliding planes. The plane sliding method is mainly used to analyze the stability characteristics of different types of soil or gravel along the approximate plane sliding surface. Its stability coefficient (Fs) can be expressed as the ratio between the shear strength (R) of the potential landslide body and the sliding force (T) under the action of gravity, that is,

[0118]

[0119] In the formula, c represents the effective cohesion coefficient of the soil, with the unit of kPa, which is estimated in the model according to the effective cohesion of different types of soil and the soil type ratio of the field survey point; L represents the length of the sliding surface, with the unit of m; W represents the gravity of the landslide body, with the unit of kN, which is calculated by the length (L) and height (H) of the potential landslide body, including the soil and interstitial water of the landslide body; α represents the angle between the sliding surface L and the horizontal plane, with the unit of radian; Pwp represents the pore water pressure on the sliding surface, with the unit of kPa, which is related to the soil moisture content m, and its calculation method is determined according to the research results of Sasahara Katsuo; γ represents the effective internal friction angle of the soil, with the unit of radian, and the calculation method is similar to the effective cohesion, that is, it is estimated according to the effective internal friction angle of different types of soil and the soil type ratio of the field survey point; cr represents the root reinforcement coefficient, that is, the contribution of vegetation roots to the stability of the slope body, and its calculation method is referred to by Stokes et al. as follows,

[0120] cr=T r ·RAR·cos 2 φ#(2)

[0121] where RAR represents the root volume ratio, dimensionless; and φ represents the root growth angle relative to the sliding surface, unit, radian. In this paper, the average root growth angle is assumed to be perpendicular to the downward direction, so φ = 0. T r where Tr represents the root damage strength, unit kPa. The calculation method is as follows: first, determine the proportion of the top three dominant vegetation (RV) at the sampling point; then, measure the root damage strength (TrV) of each dominant vegetation by tensile test, i.e., the ratio of the maximum tensile force that the root can withstand to the root diameter; finally, consider the area ratio coefficient (AR) of the vegetation, i.e., the ratio of the area of the dominant vegetation to the total area of the sampling point.

[0122] T r = AR·∑RV·TrV#(3)

[0123] According to the above calculation method, the stability coefficient can be actually divided into three parts, i.e.,

[0124] Fs = Fs c + Fs w + Fs t #(4)

[0125] where Fs represents the contribution of soil cohesion to stability, represents the contribution of the self-weight of the slope body to stability, represents the contribution of vegetation coverage and roots to stability. The calculation results of the stability coefficients of various slope bodies and the sensitivity factor analysis are as follows. Figure 4

[0126] 3 Research Results

[0127] 3.1 Analysis of the stability characteristics of each sampling point According to the sampling results of the typical slopes in the main urban areas of Chongqing, the stability coefficients (Fs) of each slope were calculated based on the above-mentioned plane sliding method. When Fs>1.0, it indicates that the slope has no landslide risk; when 0.75<Fs<1.0, it indicates that it is in a low-risk state; when 0.50<Fs<0.75, it indicates that it is in a medium-risk state; and when Fs<0.5, it indicates that it is in a high-risk state. According to the calculation results of the stability coefficients of the typical slopes in Chongqing, Figure 5 ​Of the sampling points, only the slope stability coefficient (Fs = 0.95) at point 1 in Banan District was slightly less than 1, indicating a low-risk condition. The stability coefficients of the remaining slopes were all greater than 1, indicating no risk of landslide. The reasons for the lower slope stability coefficient at point 1 in Banan District are mainly as follows: First and foremost, the slope is relatively high, resulting in a steep slope. Among all sampling points, this site has the largest angle between the sliding surface and the horizontal plane, thus posing a greater risk of landslide under its own weight. Secondly, the vegetation coverage and root volume ratio on the slope are relatively low, only better than the sampling point in Yuzhong District. However, the slope angle in Yuzhong District is gentler, and the stability coefficient is still higher (Fs = 2.09). Overall, the risk of landslide at point 1 in Banan District remains relatively low.

[0128] Further analysis of the contribution ratios of three factors—soil cohesion (Fs_c), slope self-weight (Fs_w), and vegetation root system (Fs_t)—to the stability coefficient at each site yielded the following results: Figure 5 As shown in b, at most sites, soil cohesion and slope self-weight have the most significant impact on slope stability, with the contribution reaching 99.8% at the Yuzhong District site. However, at the Yubei 2, Nan'an, Shapingba, Jiulongpo, and Dadukou sites, where vegetation is more lush, the high vegetation coverage and root system weight contribute significantly to the slope stability coefficient, and the slope stability coefficients at these sites are also relatively high.

[0129] 3.2 The Influence of Soil Cohesion on Slope Stability Soil cohesion is the internal cohesive force between soil particles, originating from chemical bonds, adsorption forces, and electromagnetic forces between soil particles. Soils with high cohesion have stronger shear strength, which helps prevent soil sliding and improves slope stability. Soil cohesion is mainly affected by soil type and moisture content. (From the previous section...) Figure 5 As the previous content shows, soil cohesion has a crucial impact on slope stability. In this model, even a 10% to 20% increase or decrease in soil cohesion significantly alters the slope's stability coefficient. The model calculation results are as follows: Figure 6 As shown, a 20% increase in soil cohesion coefficient can lead to a maximum increase of 31.2% and a minimum increase of 13.5% in its stability coefficient compared to a 20% decrease. The key influencing factor is the contribution of soil cohesion to the overall stability coefficient (Fs_c / Fs). According to... Figure 5 The Fs_c / Fs value at the Yuzhong site can reach about 68%, indicating a relatively high improvement. In contrast, the Fs_c / Fs value at the Yubei 2 site is only about 29%. Furthermore, at the Banan 1 site, if the soil cohesion can be increased by 10%, the overall stability coefficient Fs value can reach 1.05, which crosses the landslide risk line.

[0130] As to how to improve the soil cohesion, it can be considered from two aspects of soil water content and soil itself. Studies have shown that maintaining the soil water content in a certain appropriate range (the specific value is related to the soil type) can enhance its cohesive characteristics. In addition, from the engineering point of view, the soil properties can be improved by physical and chemical methods, such as increasing the wire mesh or directly concreting it. The vegetation concrete technology is more suitable, which can improve the soil properties and grow vegetation to maintain the landscape and ecological needs.

[0131] 3.3 Influence of soil water content on the stability of slope The soil water content directly affects the physical properties of the soil, such as density, pore water pressure and shear strength, thus having an important influence on the stability of the slope. Generally, the field soil water content varies between 5% and 60%, so the present invention selects this range to discuss the influence of soil water content on the stability of the slope. The diamond solid points in the figure represent the actual water content of the measuring point and its corresponding stability coefficient, and the results are shown in Figure 7 Generally speaking, higher soil water content usually shows lower shear strength, which is prone to soil sliding, thereby reducing the stability of the slope, which can also be reflected from the model calculation results of the present paper. From the calculation results of the calculation model used in this paper, the stability coefficient of each slope decreases with the increase of soil water content, mainly due to the following reasons. First, in the soil with high water content, the soil voids will be filled with water, which will increase the weight of the soil itself, and on the other hand, it will increase the weight of the soil itself, both of which will lead to the decrease of the stability coefficient of the slope. In addition, the increase of soil water content will also affect the soil cohesion, but the influence on the stability of the slope is nonlinear, and both lower and higher soil water content will reduce the stability of the slope.

[0132] From the contribution of the stability coefficient of each part to the later change characteristics of the increase of soil water content, the contribution of water content to the decrease of the stability coefficient of the slope by reducing the soil cohesion (Fs_c) is the largest, which accounts for more than 72% in all influencing factors Figure 8 a), and the range of the decrease of Fs_c value itself with the increase of water content is also the largest, which can reach about 60%. The influence of water content on the weight of soil is relatively small, with a total proportion of about 3.5%, and the range of its own change is only about 4%. The water content cannot affect the stability of the slope through the soil root system, but from the model formula (1), the increase of water content leads to the increase of the weight of the soil itself, which leads to the decrease of its stability coefficient.

[0133] From the above analysis, the influence of soil water content on the slope stability coefficient is more significant. In the case of Banan No. 1 test point, in the case of very low water content, the slope stability coefficient can be increased to 1.0 or more, reaching a risk-free state, and when the water content is more than 57%, the stability coefficient will decrease to 0.75 or less, reaching a medium risk state, and safety protection measures need to be taken. The natural factor affecting soil water content is rainfall. Chongqing is located in the subtropical monsoon climate zone, with annual rainfall of about 1002-1666mm, of which the rainfall in the flood season from May to October accounts for more than 70%. This is one of the important reasons for the occurrence of a large number of landslide and other geological disaster events in this mountainous city during the flood season. According to statistics by Xie Yangyi et al., about 97.2% of the total landslide events in Chongqing are directly caused by heavy rainfall.

[0134] 3.4 Influence of vegetation roots on slope stability The vegetation roots mainly improve the stability of the slope by enhancing the shear strength of the soil and reducing soil erosion. Through physical action, roots directly reinforce the soil structure, increase the friction between soil particles, and thus improve the overall stability of the soil body. In this sampling site, the soil root volume ratio is basically between 0.01% and 10%, and the sensitivity analysis results of the slope stability to the roots show that as the soil root density increases, the slope stability also increases, but the relationship between the two is not significant. Taking the Yuzhong District site as an example, when the root volume density increases from 0.03% to 10%, the stability coefficient only increases from 2.1 to 4.7. However, only the influence of roots on improving the tensile capacity of soil is considered in this model, and in fact, roots can also affect the slope stability in other ways, which are not considered in this model. For example, roots can increase the porosity of soil, improve the infiltration and drainage conditions of water, thereby reducing the saturation of the soil body and reducing the probability of landslide occurrence. The transpiration of vegetation helps to reduce the soil water content, further improving the stability of the slope. In addition, high root density can also reflect high vegetation coverage, which can reduce the permeability of water during heavy rain and prevent landslide events Figure 9 .

[0135] 3.5 Thinking about improving slope stability Based on the above research conclusions of the invention, although the slope stability coefficients of each sampling point are relatively high, and only one test point has a stability coefficient slightly less than 1, but landslide phenomena still occur in Chongqing and even in China. Based on the calculation results of the invention and the sensitivity analysis results of each parameter, we propose some thoughts on improving the slope stability coefficient.

[0136] 3.5.1 First, engineering measures can be used to reinforce the soil through supporting structures and drainage systems. For example, retaining walls, anchor rods, and soil nail walls can be used to provide additional resistance to sliding and prevent soil movement. Effective drainage systems can lower the groundwater level and reduce soil saturation, thereby improving the stability of the slope. Common drainage measures include installing drainage pipes, blind trenches, and infiltration wells. In recent years, the technology of vegetation concrete has emerged, which can significantly enhance the cohesion of the soil while causing minimal disturbance to the growth of vegetation. It is one of the important ways to improve the stability coefficient of the slope.

[0137] 3.5.2 Second, increasing vegetation coverage can effectively reduce the speed of surface water flow and reduce erosion. The root system of plants can enhance the shear strength of the soil, especially deep-rooted plants. For different regions of the slope, appropriate plant species should be selected to ensure that the plants can grow well in the slope environment.

[0138] 3.5.3 For important slopes, regular monitoring and maintenance should be implemented, including the installation of inclinometers, rain gauges, and groundwater level meters to monitor the deformation of the slope, rainfall, and groundwater level on a regular basis to detect potential stability problems in a timely manner. At the same time, development and construction activities near the slope should be limited to reduce excavation, filling, and building activities above or near the slope to avoid increasing the load on the slope or damaging the original geological structure.

[0139] 4 Conclusion

[0140] Based on the slope characteristics data of multiple stations in the main urban area of Chongqing, the invention uses the plane sliding method to calculate the stability characteristics of each slope, and analyzes the relationship between the slope stability and sensitive factors such as soil cohesion, soil moisture content, and vegetation root characteristics. The paper obtains the following conclusions.

[0141] (1) The stability coefficient of each sampling point is basically above 1.0, indicating that the landslide risk is extremely small;

[0142] (2) The contribution of soil cohesion to maintaining the stability of the slope is the largest, and the stability coefficient can be increased by 31.2% after the soil cohesion coefficient is increased by 20%;

[0143] (3) Soil moisture content increases the weight of the soil and reduces the soil cohesion, so it is basically negatively correlated with the stability coefficient of the slope;

[0144] (4) Soil root density can enhance the shear strength of the soil and reduce soil erosion, thereby improving the overall stability of the slope.

[0145] The specific application fields of the invention mainly include:

[0146] (1) Civil engineering: In civil engineering projects such as highways, railways, bridges, and tunnels, the present application can be used for stability evaluation during the design and construction stages of slopes, helping engineers develop safer and more reliable design schemes.

[0147] (2) Geological disaster prevention: The present application can be applied in areas prone to landslides, debris flows, and other geological disasters to monitor and warn of slope stability, improving disaster prevention and emergency response capabilities and reducing casualties and property losses.

[0148] (3) Water conservancy engineering: In water conservancy projects such as reservoirs, dams, and river embankments, the present application can be used to evaluate the stability of slopes and dam bodies to ensure the long-term safety and stability of engineering structures.

[0149] (4) Urban planning and construction: In the planning of urban expansion and new areas, the present application can be used to evaluate the stability of different plots to provide scientific basis for building site selection and foundation design, reducing safety hazards caused by geological instability.

[0150] (5) Mining and reclamation: In mining activities, the present application can be used to evaluate the stability of slopes during mining and ensure slope safety during land reclamation and environmental restoration after mine closure.

[0151] (6) Agricultural and forestry management: In agricultural terrace, orchard, and forest land management, the present application can be used to evaluate the risk of soil erosion and slope instability, helping to develop reasonable soil conservation and vegetation management strategies.

[0152] It should be noted that the embodiments of the present application can be realized by hardware, software or a combination of software and hardware. The hardware part can be realized by special logic; the software part can be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or a specially designed hardware. Those skilled in the art can understand that the above devices and methods can be realized by computer executable instructions and / or included in processor control code, such as provided on carrier media, such as magnetic disk, CD or DVD-ROM, programmable memory, such as read-only memory (firmware), or data carrier, such as optical or electronic signal carrier. The devices of the present application and their modules can be realized by hardware circuit, such as ultra-large-scale integrated circuit or gate array, semiconductor, such as logic chip, transistor, or programmable hardware device, such as field programmable gate array, programmable logic device, etc., or by software executed by various types of processors, or by a combination of the above hardware circuit and software, such as firmware.

[0153] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any modification, equivalent replacement and improvement within the technical range disclosed by the present application and within the spirit and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for analyzing the stability characteristics of urban slopes based on the risk of block sliding, characterized by, The method comprises the following steps: Step 1, calculating the stability characteristics of each station based on the plane sliding method by measuring the slope size, soil and vegetation characteristic data; Step 2, analyzing the relationship between the stability coefficient and each sensitive factor; The method for measuring the slope size, soil and vegetation characteristic data is as follows: For each slope, the main sampling or measurement indexes include the geometric size of the slope body, soil characteristics and vegetation characteristic data; The geometric size of the slope body is directly measured on site; the soil water content is measured by the tensiometer method, and the pore water pressure measured is converted into the mass water content of the soil through a theoretical formula; The soil type ratio and the root volume ratio of the vegetation in the soil are estimated by the field sampling and laboratory screening method; the dominant vegetation ratio is estimated by the field quadrat investigation method, that is, a representative 1m2 quadrat is selected, and then the growth area proportion of different types of vegetation is measured; The method for calculating the stability characteristics of each station based on the plane sliding method is as follows: The plane sliding method is mainly used for analyzing the stability characteristics of different types of soil or sand along an approximate plane sliding surface; the stability coefficient Fs can be represented as the ratio between the shear strength R of the potential landslide body and the sliding force T under the action of gravity, that is, In the formula, c represents the effective cohesion coefficient of the soil, with the unit of kPa; in the model, the effective cohesion of different types of soil and the soil type ratio of the surveyed point on site are estimated; L represents the length of the sliding surface, with the unit of m; W represents the gravity of the landslide body, with the unit of kN, which is calculated by the length L and the height H of the potential landslide body, including the soil and the interstitial water of the landslide body; a represents the included angle between the sliding surface L and the horizontal plane, with the unit of radian; Pwp represents the pore water pressure on the sliding surface, with the unit of kPa, which is related to the water content m of the soil; γ represents the effective internal friction angle of the soil, with the unit of radian, and the calculation method is similar to that of the effective cohesion, that is, the effective internal friction angle of different types of soil and the soil type ratio of the surveyed point on site are estimated; cr represents the root reinforcement coefficient, that is, the contribution of the vegetation root to the stability of the slope body, and the calculation method is as follows, In the formula, RAR represents the root volume ratio, which is dimensionless; Tr represents the root growth angle relative to the sliding surface, with the unit of radian; in this paper, it is assumed that the average growth angle of the root is perpendicular to the downward direction, so Tr is taken as 0; and the root failure strength is calculated as follows: first, the proportion of the first three dominant vegetation RV of the sampling point is determined; then, the root failure strength TrV of each dominant vegetation is measured by the tensile test, that is, the ratio of the maximum tensile force that the root can bear to the root diameter; finally, the area proportion coefficient AR of the vegetation is considered, that is, Tr = AR·∑RV·TrV#(3) According to the above calculation method, the stability coefficient can be actually divided into three parts, that is, Fs = Fs c + Fs w + Fs t #(4) wherein represents the contribution of soil cohesion to stability, represents the contribution of the self-weight of the slope body to stability, represents the contribution of vegetation cover and root system to stability.

2. A block-based urban slope stability analysis system based on the risk of block sliding according to claim 1, characterized in that, The system comprises: a data acquisition module, which is used for acquiring the geometric size, soil characteristics and vegetation characteristic data of the slope, including the soil water content, soil type, root volume ratio of the vegetation and dominant vegetation ratio, etc. The computing module calculates the stability coefficient of the slope based on the plane sliding method, and determines the contribution of soil cohesion, slope self-weight, and vegetation roots to stability. The analysis module is used to analyze the relationship between the stability coefficient and each sensitive factor, and to predict the potential landslide risk of the slope.

3. A city side slope stability measuring device based on the method of claim 1, characterized by, It includes: A tensiometer sensor is used to measure the pore water pressure in the slope soil and convert it to soil mass water content through theoretical formula; A sampling device is used to collect soil samples and vegetation root samples, and to determine the soil type ratio and vegetation root volume ratio; A data processing module is used to analyze the measurement data in real time and provide real-time evaluation of slope stability and sliding risk.

4. A device for predicting the risk of sliding of urban slopes based on the method according to claim 1, characterized by the fact that it comprises: The device includes: A slope geometry measurement module is used to measure the length, height, and slope of the slope; A soil and vegetation property detection module is used to analyze the cohesion coefficient, internal friction angle of the soil, and the reinforcement coefficient of the vegetation roots; A landslide stability calculation module is used to calculate the stability coefficient of the slope based on the plane sliding method according to the measurement data, and to output the stability analysis results for sliding risk prediction.

5. A block sliding risk-based urban slope stability feature analysis system implementing the block sliding risk-based urban slope stability feature analysis method of claim 1, characterized by, The urban slope stability feature analysis system based on block sliding risk includes: A measurement module is used to measure the slope size, soil and vegetation property data, and to calculate the stability features of each station based on the plane sliding method; An analysis module is used to analyze the relationship between the stability coefficient and each sensitive factor.

6. A computer device, comprising: The computer device includes a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the urban slope stability feature analysis method based on block sliding risk as claimed in claim 1.

7. A computer readable storage medium storing a computer program, the computer program being executed by a processor to make the processor execute the steps of the urban slope stability feature analysis method based on block sliding risk as claimed in claim 1.

8. An information data processing terminal, characterized by The information data processing terminal is used to implement the urban slope stability feature analysis system based on block sliding risk as claimed in claim 5.

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