Landslide disaster-causing effect analysis method considering three-dimensional stability and finite difference

Abstract

The invention relates to a landslide disaster-causing effect analysis method considering three-dimensional stability and finite difference, which comprises the following steps: calculating underground water level change under event rainfall in real time through FSLAM, interacting with a stability analysis module, and realizing closed-loop feedback of rainfall infiltration-stability coefficient-motion simulation; and the stability coefficient serves as a strength reduction factor input by Massflow to dynamically adjust material parameters, and full-chain analysis from instability judgment to motion simulation is achieved. By using high-resolution DEM data, the search range of the sliding surface can be dynamically defined, and the sliding surface is a three-dimensional sliding surface, so that modeling of a non-circular surface is supported, and irregular geometrical shapes can be accurately captured. The method overcomes the limitation of simplification of landslide geometry and soil mass mechanical characteristics in traditional two-dimensional analysis, more accurately captures complex mechanical behaviors in the landslide instability process, and improves the reliability of stability calculation.

Description

Technical Field

[0001] The present invention belongs to the field of engineering geology research, and particularly relates to a landslide disaster-causing effect analysis method and system considering three-dimensional stability and finite difference. Background Technique

[0002] Landslide disasters are common and serious geological disasters, widely distributed in various terrains and landforms globally, especially prominent in mountainous areas, hilly areas, and coastal steep slopes. The occurrence of landslides is often affected by both natural factors and human activities, such as heavy rainfall, earthquakes, volcanic activities, river erosion, and unreasonable engineering construction. As a geological phenomenon with strong suddenness and great destructiveness, landslides not only pose a threat to human life and property safety but may also trigger secondary disasters, such as debris flows and barrier lakes, thus exacerbating the chain effect of disasters. Due to the often concealed, sudden, and complex characteristics of landslides, their prediction and prevention face huge challenges. Therefore, scientifically understanding the mechanism of landslide occurrence, accurately assessing landslide risks, and formulating reasonable prevention and control measures are important tasks for reducing the impact of landslide disasters and ensuring the sustainable development of social economy.

[0003] However, most traditional landslide analysis methods are based on two-dimensional models and cannot accurately consider the three-dimensional spatial characteristics and geological structures of the landslide body. In actual situations, the shape and geological conditions of the landslide body are often complex, and two-dimensional analysis methods are difficult to accurately simulate the deformation and failure process of the landslide body, resulting in low accuracy and reliability of the analysis results. Existing three-dimensional landslide stability analysis methods, such as the "A Method for Hazard Assessment and Prediction of Reservoir Landslides under Rainfall Conditions" by Sun Benbo et al., use the spherical surface cutting method to simplify the sliding surface. However, the actual landslide slope terrain is complex, with irregular geometric features (such as multi-level landslides and steep terrain changes), resulting in large errors in moment balance analysis and Bishop's method under complex geological conditions. For example, spherical surface cutting cannot accurately reflect the spatial distribution of the actual sliding surface and is insufficiently sensitive to the mechanical parameters of heterogeneous rock and soil masses. In the "Landslide Stability Analysis Method Based on the Morgenstern-Price Method" by Zhou Lin et al., a steady-state or transient seepage model is used to calculate pore water pressure, ignoring the cumulative effect of rainfall infiltration, such as the influence of previous rainfall on the groundwater level.

[0004] In summary, aiming at the limitations of current two-dimensional landslide analysis and the deficiencies of stability analysis methods, the present invention provides a landslide disaster-causing effect analysis method and system considering three-dimensional stability and finite difference. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the technical problem to be solved by the present invention is to provide a landslide disaster-causing effect analysis method and system considering three-dimensional stability and finite difference. This system aims to solve the limitations of current two-dimensional landslide analysis and the deficiencies of stability analysis methods, and is of great significance for effectively carrying out landslide risk assessment and reasonable early warning.

[0006] To solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0007] In the first aspect, the present invention provides a landslide disaster-causing effect analysis method considering three-dimensional stability and finite difference. The analysis method includes the following steps:

[0008] S1. Obtain relevant information of the landslide by using satellite remote sensing technology, ground sensor network, or public meteorological database. The relevant information of the landslide includes the landslide basin range, landslide soil information, landslide rainfall data, digital elevation model (DEM), and soil property parameters. The soil property parameters include density, porosity, cohesion, friction angle, unit weight, basal friction coefficient, pore water pressure, runoff curve number, and average saturation.

[0009] S2. Import the DEM into GIS software and calculate the initial groundwater level height h under cumulative rainfall for each grid a and the groundwater level height h after event rainfall a +=h e ; where

[0010]

[0011] In the formula, h e is the change height of the groundwater level after event rainfall; CN is the runoff curve number; P e is the event rainfall; n f is the fillable porosity, n f =n·(1 - S r ), n is the porosity, and S r is the average saturation of the entire depth before event rainfall.

[0012] S3. Take (h a , h a +h e ) as the elevation range, and based on the DEM data of the study area and the landslide boundary, delimit the spatial range where the slip surface may be distributed. Set the slip surface search range for each grid according to the elevation range of each grid and the spatial range where the slip surface may be distributed. Take the distance from h a to the slope surface as the maximum depth, and take h a +h eThe distance to the slope surface is taken as the minimum depth, and then the depth range of the sliding surface is set for each grid; each sliding surface search range is considered as a sliding mass. After that, the stability coefficients are calculated for all the sliding masses within the landslide to be analyzed, and a landslide stability coefficient distribution map, a sliding mass volume file, and a ratio file of the sliding mass volume to the area are obtained.

[0013] S4. Import the digital elevation model (DEM) into the Massflow software. Within the sliding surface search range, use the sliding mass volume output in step S3 as the volume of the sliding source area, and use the ratio of the sliding mass volume to the area output in step S3 as the average depth of the sliding mass to construct a three-dimensional landslide model. Then, dynamically reduce the strength of the mechanical parameters of the sliding mass using the landslide stability coefficient obtained in S3, and directly use the mechanical parameters of the sliding mass after strength reduction for numerical simulation of landslide movement to obtain the landslide influence range, speed, and flow depth for evaluating various disaster effects that the landslide may trigger.

[0014] Furthermore, the calculation formula for the stability coefficient Fs is:

[0015]

[0016] where, e i，j is the horizontal seismic force arm of the grid column, and its value is the vertical distance from the centroid of the grid column to the elevation of the rotation axis. G i，j is the gravity of the grid column, k i，j is the horizontal seismic coefficient; a i,j is the force arm of the grid column in the gravity direction, and its value is the horizontal distance from the rotation axis to the centroid of the grid column; A i，j is the potential sliding surface area of the grid column located in the i-th row and j-th column; S i，j is the distance from the bottom surface of the grid column to the rotation axis; α i,j is the apparent dip angle of the bottom surface of the grid column in the sliding direction; σ i，j is the normal stress of the grid column in the i-th row and j-th column; c i，j and are the shear strength parameters of the sliding surface of the grid column in the i-th row and j-th column, and u i，j is the pore water pressure.

[0017] Furthermore, the calculation formula for the stability coefficient Fs is simplified using the Fellenius method and the Bishop simplified method respectively, and any one of the simplified formulas is used as the basis for determining the landslide stability coefficient distribution map.

[0018] Furthermore, when delimiting the spatial range where the slip surface may be distributed based on the DEM data of the study area and the landslide boundary, if the terrain feature within the landslide boundary is a steep area with a slope greater than 30°, the spatial search range is narrowed; if the terrain feature is a gentle area with a slope not greater than 30°, the search range is expanded, thereby determining the spatial range where the slip surface may be distributed.

[0019] In a second aspect, the present invention provides a landslide disaster-causing effect analysis system considering three-dimensional stability and finite difference. The system includes:

[0020] A database module for storing relevant information of the landslide, including the landslide basin range, landslide soil information, landslide rainfall data, digital elevation model DEM, and soil property parameters;

[0021] A groundwater level calculation module for calculating the initial groundwater level height under cumulative rainfall using the Fast Shallow Landslide Assessment Model (FSLAM) based on steady-state recharge and catchment contributing area, and then calculating the change in groundwater level height after event rainfall through event rainfall and runoff curve, thereby obtaining the groundwater level height h a +h e ;

[0022] A stability analysis module for simplifying the stability coefficient formula based on the Bishop simplification method or the Fellenius method, calculating the stability coefficient using the simplified formula, and conducting landslide stability analysis to determine the landslide body volume and the ratio of the landslide body volume to the area;

[0023] A three-dimensional numerical simulation module for numerically simulating the landslide movement using Massflow software;

[0024] A result analysis module for conducting landslide disaster-causing effect analysis based on the landslide movement range, speed, and depth diagrams under different working conditions obtained by the three-dimensional numerical simulation module;

[0025] By calculating the change in groundwater level under event rainfall in real time through FSLAM and interacting with the stability analysis module, a closed-loop feedback of rainfall infiltration - stability coefficient - movement simulation is realized; the stability coefficient is used as the strength reduction factor input to Massflow to dynamically adjust the material parameters, achieving a full-chain analysis from instability judgment to movement simulation.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] (1) By using high-resolution DEM data, the present invention can dynamically define the search range of the slip surface, which is a three-dimensional slip surface, thus supporting the modeling of non-circular surfaces (such as polyline-shaped or multi-stage slip surfaces) and being able to accurately capture irregular geometries (such as multi-stage landslides or steep terrain changes). It overcomes the limitations of the simplification of landslide geometry and soil mechanics properties in traditional two-dimensional analysis, more precisely captures the complex mechanical behavior during landslide instability, and improves the reliability of stability calculation. Moreover, it supports the accurate modeling and dynamic analysis of various types of landslides, including landslide bodies with a high width / depth ratio or landslides in heterogeneous strata, and has strong adaptability.

[0028] (2) The present invention uses the finite difference method (such as Massflow software) to model the three-dimensional dynamics of slopes, simulating the dynamic evolution process of stress and displacement fields within the landslide body, which can effectively capture the whole process of landslide from initial instability to large-scale movement, thereby improving the accuracy of stress and displacement analysis, having high numerical stability and flexibility, and being applicable to the study of landslide dynamics under multi-field coupling conditions (such as rainfall infiltration, seismic action). By combining the strength reduction method to dynamically adjust geotechnical parameters, it reduces the errors caused by simplification and improves the prediction of slope stability.

[0029] (3) The present invention uses high-resolution digital elevation model (DEM) data and combines terrain parameters to dynamically adjust the search range of the slip surface. For example, within the landslide boundary, if the terrain feature is a steep area with a slope greater than 30°, the spatial search range is narrowed; if the terrain feature is a gentle area with a slope not greater than 30°, the search range is expanded, thereby determining the possible spatial range of the distribution of the slip surface. This flexibility is crucial for accurately modeling various types of landslides, especially those with irregular geometries (such as multi-stage landslides or steep terrain), ensuring that the model can adapt to the unique characteristics of each slope. At the same time, using the finite difference method of Massflow software can conduct a detailed three-dimensional simulation of landslide dynamics, including stress distribution and displacement fields. This is crucial for capturing the behavior of landslides with complex soil layers, heterogeneous materials, or different boundary conditions (such as steep slopes, etc.). Finally, through strength reduction, geotechnical parameters such as cohesion and friction angle can be dynamically adjusted during the simulation process. This dynamic adjustment makes the model more adaptable and accurate when dealing with landslides with different geotechnical conditions and can meet the analysis needs of various types of landslides.

[0030] (4) The present invention realizes the dynamic real-time simulation of the entire landslide process from instability to large-scale movement. It directly couples external factors such as rainfall and seismic activities with landslide dynamics, realizing a complete feedback loop of stress, displacement, and external influences, thereby ensuring a more comprehensive understanding of the disaster process and being able to completely simulate the movement of the landslide from start to end.

[0031] (5) By combining topography, soil mechanics parameters, and hydrological conditions, considering the dynamic cumulative effect of rainfall infiltration, the present invention calculates the change in the groundwater level before and after rainfall in real time through the FSLAM model. The pore water pressure changes dynamically with event rainfall. Each time, the stability coefficient is dynamically calculated based on the water level change, and its value is dynamically updated. It can accurately evaluate various disaster effects that may be caused by landslides, such as landslide volume, movement path, influence range, etc., providing a scientific basis for landslide disaster risk management and emergency decision-making. The output results include three-dimensional landslide distribution maps, stability coefficient distributions, landslide volume, and downstream impact predictions, etc., with intuitiveness and practicality. The total rainfall is updated in real time according to rainfall events, that is, the event rainfall P e , dynamically calculate h e , through S r reflecting the influence of previous rainfall on soil saturation. For example, previous rainfall causes S r to increase and n f to decrease, thereby amplifying the correction amplitude of h e on the change height of the groundwater level.

[0032] (6) The present invention dynamically defines the search range of the sliding surface through high-resolution DEM data, and combines the finite difference method (Massflow software) to perform grid-by-grid mechanical analysis on the three-dimensional sliding surface, fully considering the dynamic cumulative effect of rainfall infiltration (such as the influence of previous rainfall on the groundwater level), realizing the real-time interaction between hydrological conditions and mechanical analysis, and dynamically adjusting geotechnical parameters through the strength reduction method to simulate the gradual process of the landslide from stable to unstable.

[0033] In summary, the method and system of the present invention integrate advanced three-dimensional stability analysis and finite difference calculation technologies, make up for the deficiencies of traditional landslide analysis methods, significantly improve the accuracy and efficiency of landslide disaster effect analysis, and provide strong technical support for landslide prevention and disaster management. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is the flow depth map of the Gouhe North landslide under the 50-year return period in Embodiment 1 of the present invention.

[0035] Figure 2 is the velocity map of the Gouhe North landslide under the 50-year return period in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0036] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Of course, the specific embodiments described here are only used to explain the present invention and are not used to limit the present invention.

[0037] A method for analyzing landslide disaster effects considering three-dimensional stability and finite difference of the present invention includes the following steps:

[0038] S1. Obtain relevant information of the landslide by using satellite remote sensing technology, ground sensor network, or public meteorological databases, etc. The relevant information of the landslide includes the landslide basin scope, landslide soil information, landslide rainfall data, digital elevation model (DEM), soil property parameters (such as density, porosity, cohesion, friction angle, unit weight, basal friction coefficient, pore water pressure, runoff curve number, average saturation).

[0039] S2. Import the DEM into GIS software and calculate the groundwater level height after rainfall for each grid cell of the landslide event to be analyzed.

[0040] The groundwater level module calculates the initial groundwater level height before rainfall based on the Fast Shallow Landslide Assessment Model (FSLAM) according to the steady-state recharge and contributing area of catchment, and then calculates the change in groundwater level height h after event rainfall through the event rainfall and runoff curve e , and finally obtains the groundwater level height h after rainfall for the landslide event to be analyzed. a h += e .

[0041] The Fast Shallow Landslide Assessment Model (FSLAM) is based on the infinite slope theory and determines the pore water pressure distribution in the soil by combining the lateral (previous conditions) and longitudinal (event rainfall) flow characteristics. FSLAM uses the steady-state recharge q a and the contributing area of catchment ( a ) As an input parameter to calculate the initial groundwater level height h under the cumulative rainfall for each grid cell a , that is, the water level height starting from the bottom of the soil column due to the influence of previous conditions. This process reflects the combined effect of previous cumulative rainfall, topographic features, and soil permeability on the groundwater dynamic process, providing important initial hydrogeological conditions for landslide stability analysis. The calculation formula for the initial groundwater level height h a under the cumulative rainfall for each grid cell is as follows:

[0042]

[0043] where K s is the saturated hydraulic conductivity, b is the grid cell size, and θ is the slope.

[0044] During event rainfall, surface runoff is determined by using the Curve Number (CN), which is a simple hydrological model that takes into account land use and land cover (LULC) and soil type. The change in the groundwater level height after event rainfall is calculated based on the event rainfall amount and the Curve Number according to the following formula:

[0045]

[0046] In the formula, h e is the rise value of the groundwater level during rainfall, that is, the change in the groundwater level height after rainfall; CN is the Curve Number, which is only related to the vegetation type, and different vegetation types have different CN values; P e is the event rainfall amount, n f is the fillable porosity,

[0047] The expression of the fillable porosity n f is:

[0048] n f = n·(1 - S r )

[0049] where n is the porosity, and S r is the average saturation of the entire depth before event rainfall, that is, the average saturation during previous cumulative rainfall, which reflects the influence of previous cumulative rainfall on soil saturation through S r and is obtained by monitoring a certain number of soil temperature and humidity sensors arranged along the cross-section of the landslide, and Sr changes dynamically during the event rainfall process.

[0050] Furthermore, h a + h e is the groundwater level height after the landslide event rainfall.

[0051] S3. Calculate the stability coefficient of all sliding masses within the landslide in the GIS software:

[0052] Taking (h a , h a + h e ) as the elevation range, and based on the DEM data of the study area and the landslide boundary, delimit the spatial range where the slip surface may be distributed. Set the slip surface search range for each grid according to the elevation range of each grid and the spatial range where the slip surface may be distributed. Take the distance from h a to the slope surface as the maximum depth, and take h a + h eThe distance to the slope surface is taken as the minimum depth, and then the depth range of the sliding surface is set for each grid; each sliding surface search range is considered as a sliding mass. After that, the stability coefficients of all sliding masses within the landslide to be analyzed are calculated separately to obtain the landslide stability coefficient distribution map, the sliding mass volume file, and the ratio file of the sliding mass volume to the area. The specific process is as follows:

[0053] (1) Prepare the high-resolution DEM file of the study area, and preprocess the DEM in GIS software (such as ArcGIS or QGIS), fill in the invalid data in the DEM, repair possible boundary anomalies, ensure data integrity, and clip the DEM to the study area range to reduce the calculation amount.

[0054] (2) Import the DEM file as the basic terrain data, check whether the DEM data is loaded correctly, and ensure that the displayed terrain range is consistent with the study area. Secondly, set the DEM cell size, which is usually consistent with the DEM file resolution. Finally, define the analysis area range (such as the landslide boundary). In these two steps, filling is to repair the defects in the data content to ensure the accuracy of the analysis results; checking is to verify whether the data is correctly presented in the GIS software to avoid calculation simulation errors.

[0055] (3) Define the material model, set the soil property parameters of the landslide, including cohesion, friction angle, unit weight, etc. And if there are significant soil layers in the area, define the properties of each layer of material, make the soil property parameters of each layer of material into a layered material file, and input through the layered material file.

[0056] (4) Input the initial groundwater level height h a and the groundwater level height h a +h e after rainfall in the landslide. Take (h a , =h a +h e ) as the elevation range, and based on the DEM data of the study area and the landslide boundary, delimit the spatial range where the sliding surface may be distributed. Set the sliding surface search range for each grid according to the elevation range of each grid and the spatial range where the sliding surface may be distributed. Take the distance from h a to the slope surface as the maximum depth, and take h a +h eThe distance to the slope surface is taken as the minimum depth, and then the depth range of the sliding surface is set for each grid. By setting the maximum and minimum depths, the system only conducts mechanical analysis on the soil mass within the selected depth range, avoiding ineffective calculations. Each search range of the sliding surface is considered as a landslide body. The volume and average depth of the landslide source area input into the Massflow software directly depend on the depth range of the sliding surface set in this step. The calculation of the landslide body volume only covers the soil mass within this depth. Generally, the volume range of the sliding surface can also be set to about 0.01 to 10,000 cubic meters to limit the possible scale of the landslide within the calculation area.

[0057] (5) Conduct a stability analysis on the landslide to be analyzed:

[0058] When calculating the stability coefficient, the moment balance method is used for calculation, mainly the ordinary Fellenius method and the simplified Bishop method. Generally speaking, all limit equilibrium methods (including the moment balance method) define F S as the ratio of the average shear strength τ f to the shear stress τ in the sliding direction along the slip surface:

[0059]

[0060] When the landslide body is in the limit equilibrium state, assuming that F of each grid column in the disaster reduction landslide body S is the same, then its average downslope force T is the sum of the downslope forces of all grid columns with row number i and column number j corresponding to the x and y directions inside it, that is:

[0061]

[0062] In the formula, A is the total surface area of the potential slip surface; A i，j is the potential slip surface area of the grid column located in row i and column j.

[0063] The moment arm a of each grid column in the direction of gravity i,j is the horizontal distance from the rotation axis to the centroid of the column (approximately the geometric center of the column). From the geometric relationship, it can be obtained that:

[0064] a i,j = S i,j sinα i,j

[0065] In the formula, S i，j is the distance from the bottom surface of the grid column to the rotation axis, which varies with the column. In two dimensions, this value is the radius of the circle; αi,j is the apparent dip angle of the bottom surface of the column in the sliding direction.

[0066] Therefore, the rotational moments M dG and M dEQThey are respectively:

[0067] M dG = ∑S i,j G i,j sinα i,j

[0068] M dEQ = ∑G i,j k i,j e i,j

[0069] Wherein, e i，j is the horizontal seismic force arm of the grid column, and its value is the vertical distance from the centroid of the grid column to the elevation where the rotation axis is located, G i，j is the gravity of the grid column, and k i，j is the horizontal seismic coefficient.

[0070] The anti-rotation moment is the sum of the products of the shear strength at the bottom of all grid columns and their anti-rotation force arms. Then, the total anti-rotation moment M of all grid columns r is:

[0071]

[0072] Wherein, σ i，j is the normal stress of the grid column in the i-th row and j-th column; c i，j and are the shear strength parameters of the sliding surface of the grid column in the i-th row and j-th column, and u i，j is the pore water pressure.

[0073] Therefore, the stability coefficient F of the potential sliding mass S is:

[0074]

[0075] The Fellenius method and the Bishop simplified method use different normal pressure calculation methods to evaluate the landslide stability. Their stability calculation formulas are simplified using the Fellenius method and the Bishop simplified method respectively, and after simplification, they are respectively:

[0076]

[0077] Wherein, β i，j is the inclination angle of the potential sliding surface of the grid column in the i-th row and j-th column, and k eq is the equivalent seismic coefficient.

[0078] (6) Output the landslide stability coefficient distribution map, the landslide body volume file, and the ratio file of the landslide body volume to the area. In the landslide stability coefficient distribution map, it can show a block-by-block distribution state. Each block can be considered as a landslide body. The above stability coefficient is calculated as the stability coefficient of a landslide body.

[0079] S4. Import the digital elevation model DEM into the Massflow software to generate a Massflow landslide model. Within the sliding surface search range, and use the landslide stability coefficient obtained in S3 to perform dynamic strength reduction on the mechanical parameters of the landslide body. The mechanical parameters of the landslide body after strength reduction are directly used for the numerical simulation of landslide movement to obtain the landslide influence range, speed, and flow depth, which are used to evaluate various disaster effects that the landslide may trigger. The specific steps are as follows:

[0080] (1) Obtain and process the digital elevation model DEM data: In step S3, use the ArcGIS software to clip the DEM data, remove irrelevant or unimportant areas, and optimize the data to ensure the accuracy and calculation efficiency of the model. In this step, based on step S3, convert the DEM data into the projection coordinate format acceptable by AutoCAD, convert these data into ASCII format files, and name the basic terrain data required for landslide modeling and the spatial distribution information of the landslide source area as m.txt and s.txt respectively, so that the processed data can be effectively recognized by modeling software such as Massflow. Then, import these ASCII format files into the Massflow software for further processing.

[0081] (2) In the Massflow software, input the volume of the landslide source area (i.e., the total amount of landslide material) and the average depth of the landslide. The volume is the landslide body volume output in step S3, and the average depth is the ratio of the landslide body volume to the area output in step S3. After completing these preliminary settings, run the Landslide Volume.exe program. The Massflow software will generate the final required terrain elevation z and fluid height h files according to the input landslide area data (volume and average depth).

[0082] (3) Conduct three-dimensional modeling of the landslide. Directly generate a complete three-dimensional landslide model based on the z and h files. The z file is assigned as the terrain data, and the h file represents the height of the fluid during the landslide process.

[0083] (4) Set model material parameters. Select the Coulomb model in the Massflow software and set the material parameters, including density, cohesion, and basal friction coefficient, etc. When setting these parameters, the stability coefficient output in step S3 needs to be used for strength reduction. The mechanical parameters of the landslide body after strength reduction are directly used for the numerical simulation of landslide movement, and static-dynamic coupling analysis is realized. Through the parameter reduction mechanism, the stability analysis and movement simulation are integrated into a unified process, improving the accuracy and efficiency of the analysis of landslide disaster-causing effects.

[0084] (5) Conduct dynamic numerical simulation of the landslide movement and output the landslide influence range, as well as velocity and flow depth files. Finally, based on the output files, various disaster effects that the landslide may trigger can be accurately evaluated, providing a scientific basis for landslide disaster risk management and emergency decision-making.

[0085] Example 1

[0086] The research example in this study is the Gouhebei landslide. The Gouhebei landslide is located in Gouhebei Village, Guanzhuang Town, Jizhou District, Tianjin City, in the north of China. For the Gouhebei landslide, rainfall is the most important factor triggering landslide instability. Therefore, it is necessary to analyze extreme rainfall scenarios and predict the potential stability and danger of the landslide in advance.

[0087] Step S1: Obtain the digital elevation model (DEM), soil property parameters, landslide rainfall data, etc. of the landslide from the system database module, such as geomechanical parameters like saturated permeability coefficient, porosity, cohesion, and friction angle. Among them, the rainfall amounts are rainfall with a 50-year return period and rainfall with a 100-year return period, and their values are 130 mm / day and 150 mm / day respectively.

[0088] In the groundwater level calculation module, use the steady-state recharge q a , catchment contribution area ( a ), Saturated permeability coefficient K s , grid size b, and slope θ to calculate the change height of the groundwater level of the landslide under different event rainfall conditions.

[0089] Step S2: Process the topographic data obtained in step S1 using ArcGIS. Import the digital elevation model (DEM) into the stability analysis module to ensure that the displayed topographic range is consistent with the research area. Set the DEM cell size to 0.5 m, define the landslide boundary, and define the material model.

[0090] Step S3: The groundwater level change heights under two working conditions calculated by the groundwater level module under the conditions of rainfall with a 50-year return period and rainfall with a 100-year return period are set to the stability analysis module. The stability analysis is carried out in the stability analysis module. Finally, the stability coefficient of the landslide under the rainfall condition with a 50-year return period is output as 0.957, and the stability coefficient of the landslide under the rainfall condition with a 100-year return period is 0.939.

[0091] Step S4: Process the topographic data obtained in Step S1 using ArcGIS to determine the scope of the landslide source area in the landslide occurrence area, and generate corresponding topographic files according to the topographic characteristics of this area. Convert these data into ASCII format files, and name them m.txt and s.txt respectively. These files contain the basic topographic data required for landslide modeling and the spatial distribution information of the landslide source area. Then, import these ASCII format files into the Massflow software of the three-dimensional numerical simulation module for further processing to generate a three-dimensional landslide model of the Gouhebei landslide.

[0092] The stability coefficient of the landslide under the rainfall condition with a 50-year return period is 0.957. Therefore, its strength reduction coefficient is 0.957. Multiply the strength parameter values of the rock and soil mass under the natural scenario by 0.957, which is the strength parameter value of the rock and soil mass under the rainfall return period of 50 years. Similarly, under the rainfall condition with a 100-year return period, assign these parameter values to determine the parameters in the Massflow software to obtain the three-dimensional landslide model under the current scenario.

[0093] Step S5: Based on the three-dimensional landslide models under different scenarios obtained in Step S4, conduct numerical simulation of the landslide movement in the Massflow software, output the movement range, speed, and flow depth diagrams under different working conditions, and analyze the three-dimensional movement characteristics of the landslide under different scenarios.

[0094] To better display the three-dimensional movement process of the Gouhebei landslide, select 4 time period nodes of T = 5s, 20s, 30s, and 60s to analyze its movement characteristics, such as Figure 1 、 2 shown, which are the flow depth diagram and the speed diagram respectively.

[0095] Finally, analyze the movement range, speed, and flow depth diagrams under the rainfall conditions with a 50-year return period and a 100-year return period in the system result analysis module, and it is concluded that the speed, flow depth, and disaster-causing effect of the landslide under the 100-year return period are greater than those under the 50-year return period.

[0096] Example 2

[0097] This example is a landslide disaster-causing effect analysis system considering three-dimensional stability and finite difference, including:

[0098] A database module for storing high - resolution terrain data of landslides, such as high - resolution remote sensing of landslides, digital elevation models, rainfall, etc.

[0099] A groundwater level calculation module for calculating the initial groundwater level height under cumulative rainfall based on steady - state recharge and catchment contributing area using the Fast Shallow Landslide Assessment Model (FSLAM), and then calculating the change in groundwater level height after event rainfall through event rainfall and runoff curve, so as to obtain the groundwater level height h after event rainfall of the landslide to be analyzed. a += h e 。

[0100] A stability analysis module for simplifying the landslide stability coefficient formula based on the Bishop simplification method or the Fellenius method, calculating the stability coefficient with the simplified formula, and conducting landslide stability analysis to determine the landslide body volume and the ratio of landslide body volume to area.

[0101] In the simplification of the present invention, the two - dimensional radius is extended to the apparent dip angle in the three - dimensional sliding direction, the lever arm is dynamically calculated through the geometric center of the grid cylinder, and the pore water pressure term is introduced. Finally, the cohesion and internal friction angle of the rock and soil mass are dynamically reduced using the stability coefficient to reduce the error caused by simplification assumptions.

[0102] A three - dimensional numerical simulation module for conducting numerical simulation of landslide movement based on the Massflow software using finite differences.

[0103] A result analysis module for conducting disaster - causing effect analysis of the landslide based on the landslide movement range, speed, and depth maps output by the three - dimensional numerical simulation module under different working conditions, and obtaining the disaster - causing effects of the landslide under different working conditions. It can also output three - dimensional landslide distribution maps, stability coefficient distribution maps, landslide body volume and downstream impact predictions, etc.

[0104] The present invention defines the sliding surface search range grid - by - grid based on DEM data, supports the modeling of non - circular arc sliding surfaces (such as broken - line - shaped and multi - level sliding surfaces); calculates the change in groundwater level in real - time through FSLAM, interacts with the stability analysis module, and realizes the closed - loop feedback of rainfall infiltration - stability coefficient - movement simulation; uses the stability coefficient as the strength reduction factor for input to the Massflow to dynamically adjust the material parameters, and realizes the full - chain analysis from instability judgment to movement simulation. It realizes the linkage analysis of dynamically feeding back the stability coefficient to the Massflow software to adjust the material parameters to achieve the instability threshold (when the instability threshold is reached, the landslide begins to slide) and movement simulation.

[0105] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

[0106] Matters not described in the present invention apply to the prior art.

Claims

1. A landslide disaster effect analysis method considering three-dimensional stability and finite difference, characterized in that: The analytical method comprises the following steps: S1. Obtaining relevant information of the landslide by using satellite remote sensing technology, ground sensor networks, or public meteorological databases, wherein the relevant information of the landslide includes the landslide basin range, landslide soil information, landslide rainfall data, digital elevation model (DEM), and soil attribute parameters; the soil attribute parameters include density, porosity, cohesion, friction angle, unit weight, base friction coefficient, pore water pressure, runoff curve number, and average saturation; S2. Import DEM into GIS software and calculate the initial groundwater level h under the cumulative rainfall of each grid. a and the groundwater level after the rainfall event h a + = h e ;in, In the formula, h e is the height of groundwater level change after the event rainfall; CN is the runoff curve number; P e is the event rainfall; n f is the fillable porosity, n f =n·(1-S r ), n is the porosity, S r is the average saturation over the entire depth before the rainfall event; S3, with (h a ,h a +h e ) as the elevation range, and based on the DEM data of the study area and the landslide boundary, the possible spatial range of the sliding surface is delineated. The sliding surface search range is set grid by grid according to the elevation range of each grid and the possible spatial range of the sliding surface. a The distance to the slope surface is taken as the maximum depth, expressed as h a +h e The distance to the slope surface is taken as the minimum depth, and then the depth range of the sliding surface is set grid by grid; each sliding surface search range is considered to be a sliding body, and then the stability coefficients of all sliding bodies in the landslide to be analyzed are calculated respectively to obtain the landslide stability coefficient distribution map and sliding body volume file, and the sliding body volume and area ratio file; S4. Import the digital elevation model DEM into Massflow software. Within the sliding surface search range, take the sliding body volume output in step S3 as the volume of the sliding source area, take the ratio of the sliding body volume to the area output in step S3 as the average depth of the sliding body, and construct a three-dimensional landslide model. Use the landslide stability coefficient obtained in S3 to perform dynamic strength reduction on the mechanical parameters of the sliding body. The mechanical parameters of the sliding body after strength reduction are directly used in the numerical simulation of landslide movement to obtain the landslide impact range, velocity and flow depth, which are used to evaluate the various disaster effects that may be caused by the landslide.

2. The method according to claim 1, characterized in that The calculation formula of the stability coefficient Fs is: Among them, e i，j is the horizontal seismic arm of the grid column, which is the vertical distance from the center of mass of the grid column to the elevation of the rotation axis, G i，j is the weight of the grid column, k i，j is the horizontal seismic coefficient; a i,j A is the lever arm of the grid column in the direction of gravity, and its value is the horizontal distance from the rotation axis to the center of mass of the grid column; i，j is the potential sliding surface area of ​​the grid column located in row i and column j; S i，j is the distance from the bottom of the grid column to the axis of rotation; αi,j is the apparent inclination angle of the bottom of the grid column in the sliding direction; σ i，j is the normal stress of the grid column in row i and column j; c i，j and is the shear strength parameter of the sliding surface of the grid column in the i-th row and j-th column, u i，j is the pore water pressure.

3. The method according to claim 2, characterized in that The calculation formula of the stability coefficient Fs is simplified by using the Fellenius method and the Bishop simplification method respectively, and any one of the simplified formulas is used as the basis for determining the landslide stability coefficient distribution map.

4. The method according to claim 2, characterized in that: When delineating the possible spatial range of the sliding surface distribution based on the DEM data of the study area and the landslide boundary, if the terrain feature within the landslide boundary is a steep area with a slope greater than 30°, the spatial search range is narrowed; if the terrain feature is a gentle area with a slope not greater than 30°, the search range is expanded to further determine the possible spatial range of the sliding surface distribution.

5. A landslide disaster effect analysis system considering three-dimensional stability and finite difference, characterized in that: The system comprises: Database module, used to store relevant information of landslide, including landslide basin range, landslide soil information, landslide rainfall data, digital elevation model DEM, and soil attribute parameters; The groundwater level calculation module is used to calculate the initial groundwater level under cumulative rainfall based on steady-state recharge and catchment contribution area using the rapid shallow landslide assessment model FSLAM, and then calculate the groundwater level change height after the event rainfall through the event rainfall and runoff curve, so as to obtain the groundwater level height h after the landslide event to be analyzed a +h e ; The stability analysis module is used to simplify the stability coefficient formula based on the Bishop simplification method or the Fellenius method, calculate the stability coefficient with the simplified formula, and perform landslide stability analysis to determine the sliding body volume and the ratio of the sliding body volume to the area; Three-dimensional numerical simulation module, used to simulate the landslide movement numerically using Massflow software; The result analysis module is used to analyze the disaster-causing effect of landslides based on the landslide movement range, speed, and depth maps under different working conditions obtained by the three-dimensional numerical simulation module; FSLAM is used to calculate the groundwater level changes under event rainfall in real time, and interact with the stability analysis module to achieve a closed-loop feedback of rainfall infiltration-stability coefficient-motion simulation. The stability coefficient is used as the strength reduction factor input by Massflow to dynamically adjust the material parameters, realizing a full-chain analysis from instability judgment to motion simulation.

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