A landslide hazard risk assessment method and system based on spatial analysis model

Abstract

This invention belongs to the field of landslide risk assessment technology. It discloses a landslide disaster risk assessment method and system based on a spatial analysis model. The method includes dividing the landslide disaster study area into a spatial cell network according to slope aspect and geomorphological characteristics, acquiring and storing the geological spatial information of each cell; based on the spatial cell network, uniformly representing disaster triggering events under different disaster scenarios, establishing a time-varying pore water pressure response, mapping the rainfall infiltration effect and the additional impact of earthquakes to equivalent pore pressure increments, performing disaster factor isomorphism processing, and outputting the pore pressure response results of each cell; based on the pore pressure response results and combined with the soil strength degradation law, using a dual-threshold criterion based on the safety factor and the degree of deterioration to determine the unstable cells; this invention achieves operability and systematization of landslide disaster risk analysis, providing a reliable technical means for landslide prevention and control in complex terrain areas.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of landslide risk assessment, more particularly, the present application relates to a landslide disaster risk assessment method and system based on a spatial analysis model. BACKGROUND

[0002] The existing landslide disaster risk assessment method and system mainly have the following problems:

[0003] As a common geological disaster, landslides are often affected by multiple disaster-causing factors, including rainfall, earthquakes, terrain slope, and soil properties. The existing landslide disaster risk assessment method and system has many shortcomings in practical application.

[0004] Traditional landslide risk assessment methods usually deal with the seepage effect induced by rainfall and the transient pore water pressure effect induced by earthquakes separately, lacking a unified time-varying pore water pressure description. This leads to difficulties in accurately quantifying unit stability in multi-disaster factor coupling analysis, affecting the accuracy of landslide instability determination. Existing methods mostly use Richards equation or physical seepage models to simulate rainfall infiltration, with complex calculation process and time-consuming numerical solution, making it difficult to efficiently apply in large-area, multi-unit spatial analysis models. At the same time, existing methods lack a simplified means to directly convert seismic action into pore water pressure increment, making it difficult to consider seismic effects uniformly with rainfall effects, further reducing the accuracy of landslide stability determination. Existing technologies usually fail to incorporate spatial heterogeneity characteristics such as terrain, slope direction, and soil thickness into pore pressure response calculations, resulting in inaccurate unit-scale landslide risk determination.

[0005] Existing methods have limitations in landslide evolution to secondary disasters. Traditional methods fail to scientifically determine the transformation initiation conditions of landslide bodies at slope toes, valleys, or river areas based on actual terrain conditions and hydrodynamic factors, resulting in insufficient secondary disaster prediction. When landslide material slides along the slope surface to the valley or river, its accumulation space distribution is affected by slope, terrain, and material source remobilization capacity, while traditional methods often use fixed or empirical ranges, making it difficult to reflect the actual accumulation situation and reducing the spatial accuracy of risk assessment.

[0006] Traditional landslide assessment methods mostly use single landslide safety factor or landslide volume as an indicator, failing to consider landslide and debris flow risks simultaneously, lacking integrated landslide and secondary disaster assessment capability, and limiting scientific judgment and prevention management of landslide disaster chain and comprehensive risk.

[0007] In view of the above, the present application proposes a landslide disaster risk assessment method based on a spatial analysis model to solve the above problems. SUMMARY

[0008] In order to overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purpose, the present application provides the following technical scheme: a landslide disaster risk assessment method based on a spatial analysis model, comprising:

[0009] S1, the landslide disaster research area is divided into a spatial cell grid according to the slope direction and the landform characteristics, and the geological spatial information of each unit is obtained and stored;

[0010] S2, based on the spatial cell grid, the disaster triggering events under different disaster scenarios are uniformly represented, the time-varying pore water pressure response is established, the rainfall infiltration effect and the earthquake additional influence are mapped into equivalent pore pressure increment, the disaster factor is isomorphic, and the pore pressure response result of each unit is output;

[0011] S3, according to the pore pressure response result, combining the soil strength degradation law, adopting the double threshold criterion based on the safety factor and the deterioration degree, the unstable unit is determined;

[0012] S4, the spatial connectivity of the unstable unit is analyzed, the potential sliding body is identified, and the movement trend of the sliding body is evaluated based on the energy balance method, the ground roughness and the vegetation resistance are introduced to modify the movement process, and the potential sliding path and the accumulation area are deduced;

[0013] S5, after the potential sliding path and the accumulation area are deduced, the evolution of the sliding body in the valley and the river area is determined, when the erosion shear stress reaches the preset determination rule, the landslide to debris flow conversion process is identified, and the corresponding risk level is output, and the landslide and secondary disaster integrated risk assessment is carried out.

[0014] Specifically, the division method of the spatial cell grid comprises:

[0015] The digital elevation model of the landslide disaster research area is obtained, the digital elevation model is preprocessed, the slope, the slope direction, the curvature and the flow accumulation of the preprocessed digital elevation model are extracted, and the valley line and the ridge line are identified to form a landform skeleton;

[0016] The landslide disaster research area is preliminarily divided into different units with the ridge line and the valley line as the boundary, and each unit is divided according to the slope direction consistency criterion; under the premise of meeting the slope direction consistency, the long axis along the slope direction and the short axis along the contour direction are generated to form a strip-shaped cell grid, and the grid scale is adaptively controlled through the preset unit length-width ratio and the preset minimum area threshold;

[0017] The unit that does not meet the preset unit length-width ratio and the preset minimum area threshold is preferentially merged with the adjacent unit with similar slope direction, and the generated strip-shaped cell grid is topologically checked and coded to form a spatial cell grid.

[0018] Specifically, the method for obtaining the geological space information comprises:

[0019] Based on the generated space cell grid, the geological space information of each cell is obtained and stored from the digital elevation model, remote sensing image and geological survey data by indexing the space position through cell coding, and the geological space information includes slope, slope direction, curvature, convergence area, slope length and landform position.

[0020] Specifically, the method for establishing the time-varying pore water pressure response comprises:

[0021] The defined disaster scenarios include rainfall scenarios and earthquake scenarios. For the rainfall scenario, the historical rainfall and rainfall duration within the space cell grid are collected, and the total rainfall is evenly distributed to each time step within the rainfall duration, the rainfall intensity of each time step is calculated, and the rainfall duration curve is obtained.

[0022] The rainfall duration curve is processed by using the convergence memory kernel convolution method to obtain the transient equivalent water level rise of each unit, and the time-varying pore water pressure is converted by the unit weight of water to obtain the pore pressure time sequence under the action of rainfall.

[0023] For the earthquake scenario, the peak ground acceleration within the space cell grid is calculated by using the seismic record observed by the regional seismic station; and the effective overburden stress of the unit is calculated based on the soil thickness and soil bulk density within the space cell grid.

[0024] The peak ground acceleration and the effective overburden stress of the unit are combined to calculate the equivalent pore water pressure increment under the action of earthquake, and the equivalent pore water pressure increment under the action of earthquake is mapped into the equivalent pore pressure sequence which can be superimposed on the time sequence.

[0025] Specifically, the method for outputting the pore pressure response results of each unit comprises:

[0026] The pore pressure time sequence under the action of rainfall and the equivalent pore pressure sequence mapped by earthquake are superimposed to form the unified time-varying pore water pressure response sequence of each space unit, the isomorphic processing of disaster factors is realized, and the unified pore pressure response results of each space unit are outputted.

[0027] Specifically, the method for determining the unstable unit comprises:

[0028] Based on the unified time-varying pore water pressure response sequence of each space unit, the safety factor of each unit is calculated with time according to the strength degradation law of the unit soil body, and the safety factor is obtained according to the ratio of the unit shear strength to the effective shear stress affected by the pore water pressure.

[0029] The system sets a critical threshold for the safety factor and a threshold for the degree of soil strength deterioration. It then compares the safety factor with the critical threshold for the safety factor and the degree of soil strength deterioration with the threshold for the degree of soil strength deterioration.

[0030] When the unit safety factor is less than the preset safety factor threshold and the soil strength deterioration degree is greater than the preset soil strength deterioration degree threshold, the unit is determined to be an unstable unit; the spatial location, instability time, corresponding safety factor and soil strength deterioration degree of the unstable unit are output.

[0031] Specifically, the method for assessing the motion trend of the sliding body includes:

[0032] The unstable cells are identified in the spatial cell grid to form a set of unstable cells; for each unstable cell, the spatial adjacency relationship with the adjacent cells is checked, and the adjacency relationship can be determined by the cells sharing edges or sharing vertices; and according to the adjacency relationship between cells, the interconnected unstable cells are merged into different connected domains, and each connected domain is a candidate region of a potential sliding body.

[0033] Using graph theory, each unstable unit is treated as a graph node, and edges are established between adjacent units. A connected subgraph algorithm is used to identify each connected domain. For each connected domain, the spatial extent, area, and centroid location are statistically analyzed. Combined with topographic information such as slope, aspect, valley line, and ridge line, the unit with the steepest slope within the connected domain is identified, and the aspect of the unit with the steepest slope is taken as the main sliding direction of the potential sliding body.

[0034] Specifically, the method for extrapolating potential slip paths and accumulation zones includes:

[0035] An energy balance model was established to calculate the release of gravitational potential energy, the consumption of frictional resistance, and the surface resistance during the movement of the sliding body. In the energy balance model, the surface roughness was added as a friction correction factor to the consumption of frictional resistance. The vegetation cover type and density information of the sliding body were obtained, and the vegetation resistance coefficient was calculated through field surveys and converted into additional friction during the movement of the sliding body.

[0036] Based on the modified energy balance model, the path is deduced along the main sliding direction of each potential sliding body, and the energy surplus of the sliding body in each unit is calculated step by step. The movement trend of the sliding body is judged based on the energy surplus. If the energy surplus is positive, it means that the sliding body moves along the main slope direction. If the energy surplus is zero or negative, it means that the movement of the sliding body is hindered.

[0037] Based on the termination position of the sliding body and its spatial distribution along the path, the spatial range of the potential accumulation zone is formed. Combining the slope toe topography, valley width, and slope bottom resistance conditions, a spatial buffer algorithm is used to correct the boundary of the accumulation zone, outputting the sliding path of each potential sliding body and the corresponding spatial information of the accumulation zone.

[0038] Specifically, the method for conducting integrated risk assessment of landslides and secondary disasters includes:

[0039] After completing the simulation of potential slip paths and deposition zones, for each unit where the sliding body reaches the toe of the slope, gully, or river channel, the lowest unit is identified as the bottom unit of the gully; the erosion shear stress of the bottom unit of the gully is calculated and compared with the preset erosion shear stress threshold.

[0040] When the erosion shear stress exceeds the preset erosion shear stress threshold, it is determined that the landslide meets the initiation conditions for transformation into debris flow; the volume rate of landslide transformation into debris flow is calculated, and the risk level of landslide transformation into debris flow is determined based on the volume rate of landslide transformation into debris flow, and an integrated risk assessment of landslide and secondary disasters is carried out.

[0041] A landslide hazard risk assessment system based on a spatial analysis model includes:

[0042] The spatial unit division module divides the landslide disaster research area into a spatial cell grid according to slope aspect and geomorphological characteristics, and acquires and stores the geological spatial information of each cell;

[0043] The disaster factor characterization module, based on spatial cell grid, uniformly characterizes disaster triggering events under different disaster scenarios, establishes time-varying pore water pressure response, maps rainfall infiltration effect and earthquake additional impact as equivalent pore pressure increment, performs disaster factor isomorphism processing, and outputs the pore pressure response results of each cell.

[0044] The dual-threshold instability criterion module determines the unstable unit based on the pore pressure response results and the soil strength degradation law, using a dual-threshold criterion based on the safety factor and the degree of deterioration.

[0045] The sliding body identification module performs spatial connectivity analysis on unstable units, identifies potential sliding bodies, evaluates the movement trend of sliding bodies based on the energy balance method, introduces surface roughness and vegetation resistance to correct the movement process, and deduces potential sliding paths and deposition areas.

[0046] The secondary disaster assessment module, after completing the simulation of potential sliding paths and deposition areas, determines the evolution of sliding bodies located in gullies and river channels. When the erosion shear stress reaches the preset judgment rules, it identifies the transformation process of landslides into debris flows and outputs the corresponding risk level, thus conducting an integrated risk assessment of landslides and secondary disasters.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] This invention maps rainfall infiltration and seismic action into superimposed pore water pressure time series, achieving isomorphic processing of different disaster-causing factors and solving the problem of unified characterization of multi-source disaster factors at the unit scale. It employs a confluence memory kernel convolution approximation, simulating the unit transient response through an exponential decay kernel, while simultaneously considering the permeability limit and upstream water supply. This approximates the transient response of the Richards equations and facilitates analytical and numerical calculations, significantly improving computational efficiency. By combining peak ground acceleration with effective overburden stress, it calculates the equivalent pore pressure increment using empirical or semi-analytical mapping, which can be converted into a time series and superimposed with rainfall pore pressure, achieving quantification and temporal processing of seismic impact. Based on spatial cell grids, combined with digital elevation models, soil layer thickness, and soil unit weight, it precisely calculates the permeability characteristics, time delay parameters, and effective overburden stress of each unit, enabling accurate responses to rainfall and seismic action at the unit scale, improving spatial judgment accuracy, and allowing landslide instability assessment to more accurately reflect spatial heterogeneity and the dynamic characteristics of disaster triggering.

[0049] By calculating the erosion shear stress of the bottom unit of the gully and comparing it with a preset threshold, the initiation conditions for the transformation of landslides into debris flows can be scientifically identified, improving the accuracy of secondary disaster prediction. Using the transformation volume and rate of the landslide, combined with gully geometry and source remobilization capacity, spatial corrections are made to the deposition area, avoiding the irrationality of fixing the deposition range in traditional methods, making downstream landslide deposition predictions closer to reality. Through the landslide volume transformation rate and downstream deposition area information, a landslide-to-debris flow risk level is established, achieving integrated risk assessment of landslides and debris flows, providing a more comprehensive and scientific basis for disaster prevention and mitigation. Based on a spatial analysis model, the movement, erosion, and transformation risk of the landslide along different cells are quantified, making the assessment results operable and spatially resolvable, suitable for application in complex terrain and multi-source data environments. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of a landslide disaster risk assessment method based on a spatial analysis model according to the present invention.

[0051] Figure 2 This is a schematic diagram of a landslide disaster risk assessment system based on a spatial analysis model according to the present invention.

[0052] Figure 3 This is a schematic diagram of the method for deriving potential slip paths and accumulation zones provided by the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Example 1

[0055] Please see Figure 1 and Figure 3 As shown in the figure, this embodiment provides a landslide hazard risk assessment method based on a spatial analysis model, which specifically includes the following steps:

[0056] S1. Divide the landslide disaster research area into spatial cell grids according to slope aspect and geomorphological characteristics, and obtain and store the geological spatial information of each cell;

[0057] S2. Based on spatial cell grids, disaster triggering events under different disaster scenarios are uniformly represented, time-varying pore water pressure response is established, rainfall infiltration effect and earthquake additional effect are mapped into equivalent pore pressure increment, disaster factor isomorphism processing is performed, and pore pressure response results of each cell are output.

[0058] S3. Based on the pore pressure response results and the soil strength degradation law, the unstable unit is determined by a dual threshold criterion based on the safety factor and the degree of deterioration.

[0059] S4. Conduct spatial connectivity analysis on the unstable units, identify potential sliding bodies, assess the movement trend of the sliding bodies based on the energy balance method, introduce surface roughness and vegetation resistance to correct the movement process, and deduce potential sliding paths and deposition areas.

[0060] S5. After completing the simulation of potential sliding paths and deposition areas, the evolution of sliding bodies located in gullies and river channels is determined. When the erosion shear stress reaches the preset judgment rule, the transformation process of landslide into debris flow is identified, and the corresponding risk level is output to conduct an integrated risk assessment of landslide and secondary disasters.

[0061] Methods for dividing spatial cell networks include:

[0062] A digital elevation model of the landslide disaster research area is obtained, the digital elevation model is preprocessed, and the slope, aspect, curvature and runoff accumulation are extracted based on the preprocessed digital elevation model. Valley lines and ridge lines are also identified to form a geomorphic framework.

[0063] The landslide disaster research area is initially divided into different units with ridge lines and valley lines as boundaries, and further subdivided within each unit according to the slope aspect consistency criterion. Under the premise of satisfying the slope aspect consistency, strip-shaped cell grids are generated along the main slope aspect with the long axis along the slope aspect and the short axis along the contour direction, and the grid scale is adaptively controlled by the preset cell aspect ratio and the preset minimum area threshold.

[0064] Units that do not meet the preset aspect ratio and preset minimum area threshold are preferentially merged with adjacent units with similar slope direction. The resulting strip-shaped cell network is then topologically checked and encoded to form a spatial cell network.

[0065] Methods for acquiring geological spatial information include:

[0066] Based on the generated spatial cell network, an index is established by cell coding and spatial location. Geological spatial information of each cell is obtained and stored from digital elevation model, remote sensing image and geological survey data. Geological spatial information includes slope, aspect, curvature, runoff area, slope length and geomorphic location.

[0067] Methods for establishing time-varying pore water pressure response include:

[0068] Disaster scenarios are defined as rainfall scenarios and earthquake scenarios. For rainfall scenarios, historical rainfall and rainfall duration are collected within the spatial cell grid, and the total rainfall is evenly distributed to each time step within the rainfall duration. The rainfall intensity at each time step is calculated to obtain the rainfall duration curve.

[0069] The rainfall duration curve was processed using the confluence memory kernel convolution method to obtain the transient equivalent water level rise of each unit. The time series of pore water pressure under rainfall was obtained by converting the unit weight of water into time-varying pore water pressure.

[0070] Transient equivalent water level rise: ;in, Representation unit The transient equivalent rise in water level; This indicates that when the instantaneous rainfall intensity exceeds the permeability limit At that time, penetration was limited; Indicates the intensity of instantaneous rainfall; Representation unit The penetration limit; This indicates the amplified term of the upper confluence, describing the replenishment that accumulates from upstream or slope direction; Indicates the bus amplification factor; Representation unit The catchment area; Representation unit The base area; Indicates the unit time delay parameter; Indicates the current time point; This represents a historical time variable, indicating a point in time in the past when rainfall occurred.

[0071] The time-varying pore water pressure is: ;in, Representation unit Time-varying pore water pressure caused by rainfall; This represents the unit weight of water (density × gravitational acceleration).

[0072] For earthquake scenarios, peak ground acceleration within a spatial cell grid is statistically analyzed using earthquake records observed by regional seismic stations; effective overburden stress is calculated based on soil layer thickness and soil weight within the spatial cell grid.

[0073] By combining peak ground acceleration with effective overburden stress of the unit, the equivalent pore water pressure increment under seismic action is calculated, and the equivalent pore water pressure increment under seismic action is mapped into an equivalent pore pressure sequence that can be superimposed on the time series.

[0074] The equivalent pore water pressure increment is: ;in, Representation unit Seismic equivalent pore water pressure increment; The pore pressure conversion coefficient is related to the soil's particle composition, consolidation state, and liquefaction potential, and is obtained through expert experience. Indicates peak ground acceleration; Indicates the effective soil cover stress of the element;

[0075] Methods for outputting the pore pressure response results of each unit include:

[0076] By superimposing the pore pressure time series under rainfall and the equivalent pore pressure series after earthquake mapping, a unified time-varying pore water pressure response series for each spatial unit is formed, realizing the isomorphic processing of disaster factors and outputting the unified pore pressure response results for each spatial unit.

[0077] Methods for determining unstable elements include:

[0078] Based on the unified time-varying pore water pressure response sequence of each spatial unit, and combined with the soil strength degradation law of the unit, the safety factor of each unit is calculated over time. The safety factor is obtained based on the ratio of the unit's shear strength to the effective shear stress after being affected by pore water pressure.

[0079] The system sets a critical threshold for the safety factor and a threshold for the degree of soil strength deterioration. It then compares the safety factor with the critical threshold for the safety factor and the degree of soil strength deterioration with the threshold for the degree of soil strength deterioration.

[0080] When the unit safety factor is less than the preset safety factor threshold and the soil strength deterioration degree is greater than the preset soil strength deterioration degree threshold, the unit is determined to be an unstable unit; the spatial location, instability time, corresponding safety factor and soil strength deterioration degree of the unstable unit are output.

[0081] Methods for assessing the motion trend of a sliding body include:

[0082] The unstable cells are identified in the spatial cell grid to form a set of unstable cells; for each unstable cell, the spatial adjacency relationship with the adjacent cells is checked, and the adjacency relationship can be determined by the cells sharing edges or sharing vertices; and according to the adjacency relationship between cells, the interconnected unstable cells are merged into different connected domains, and each connected domain is a candidate region of a potential sliding body.

[0083] Using graph theory, each unstable unit is treated as a graph node, and edges are established between adjacent units. Connected subgraph algorithms (such as depth-first search or breadth-first search) are used to identify each connected domain. For each connected domain, the spatial extent, area, and centroid location are statistically analyzed. Combined with topographic information such as slope, aspect, valley line, and ridge line, the unit with the steepest slope within the connected domain is identified, and the aspect of the unit with the steepest slope is taken as the main sliding direction of the potential sliding body.

[0084] It should be noted that if there is more than one unit with the steepest slope in the connected domain, then for all units with the steepest slope, the average of their slope directions is taken, and the direction of the average vector is taken as the main sliding direction.

[0085] Methods for extrapolating potential slip paths and accumulation zones include:

[0086] An energy balance model was established to calculate the release of gravitational potential energy, the consumption of frictional resistance, and the surface resistance during the movement of the sliding body. In the energy balance model, the surface roughness was added as a friction correction factor to the consumption of frictional resistance. The vegetation cover type and density information of the sliding body were obtained, and the vegetation resistance coefficient was calculated through field surveys and converted into additional friction during the movement of the sliding body.

[0087] It should be noted that the energy balance model first treats the movement of the sliding body along the slope as a process of energy conversion and consumption. In this model, the sliding body releases gravitational potential energy as it slides down, while simultaneously consuming energy to overcome frictional resistance and surface drag. The model integrates the mass of the sliding body, changes in slope height, slope gradient, and surface features to form a holistic framework describing the energy changes in the sliding body's motion.

[0088] In the calculation process, as the sliding body descends through each spatial unit, the amount of gravitational potential energy released is first estimated based on the unit height difference and the mass of the sliding body. The calculation of frictional resistance consumption not only considers the basic friction between the sliding body and the slope surface but also incorporates surface roughness as a correction factor. Furthermore, it combines vegetation type and cover density, converting the vegetation resistance coefficient obtained through field surveys into additional friction to calculate the frictional energy consumption. The calculation of surface resistance considers factors such as slope obstacles, slope bottom conditions, and topographic relief, converting these resistances into additional energy consumption during the sliding body's movement. Through these methods, the energy balance model can simultaneously quantify the gravitational potential energy released by the sliding body and the energy consumed during its descent due to friction and surface resistance.

[0089] Based on the modified energy balance model, the path is deduced along the main sliding direction of each potential sliding body, and the energy surplus of the sliding body in each unit is calculated step by step. The movement trend of the sliding body is judged based on the energy surplus. If the energy surplus is positive, it means that the sliding body moves along the main slope direction. If the energy surplus is zero or negative, it means that the movement of the sliding body is hindered.

[0090] Based on the termination position of the sliding body and its spatial distribution along the path, the spatial range of the potential accumulation zone is formed. Combining the slope toe topography, valley width, and slope bottom resistance conditions, a spatial buffer algorithm is used to correct the boundary of the accumulation zone, outputting the sliding path of each potential sliding body and the corresponding spatial information of the accumulation zone.

[0091] Methods for conducting integrated risk assessments of landslides and secondary disasters include:

[0092] After completing the simulation of potential slip paths and deposition zones, for each unit where the sliding body reaches the toe of the slope, gully, or river channel, the lowest unit is identified as the bottom unit of the gully; the erosion shear stress of the bottom unit of the gully is calculated and compared with the preset erosion shear stress threshold.

[0093] The erosion shear stress of the bottom element of the channel is: ;in, This represents the erosion shear stress of the bottom element of the channel; Indicates the density of water; Represents gravitational acceleration; Indicates the water depth at the bottom of the channel unit; The gradient represents the energy gradient of a sliding body moving along a slope.

[0094] When the erosion shear stress exceeds the preset erosion shear stress threshold, it is determined that the landslide meets the initiation conditions for transformation into debris flow; the volume rate of landslide transformation into debris flow is calculated, and the risk level of landslide transformation into debris flow is determined based on the volume rate of landslide transformation into debris flow, and an integrated risk assessment of landslide and secondary disasters is carried out.

[0095] The volume transformation rate of the landslide body is: ;in, This indicates the volume transformation rate of the landslide mass; This represents the conversion coefficient, which is related to the landslide volume and water content. Indicates the volume of the landslide; This indicates the preset erosion shear stress threshold; This represents a function that takes positive values; its meaning is that in... At that time, take The difference, in When the value is 0, it means there is no transformation of the landslide into a debris flow;

[0096] It should be noted that the risk level of landslide transformation into debris flow can be determined using the following method: A first threshold and a second threshold for the preset conversion volumetric rate are used. When the volumetric rate of landslide transformation into debris flow is less than the first threshold, the risk level is determined to be low. When the volumetric rate is greater than or equal to the first threshold but less than the second threshold, the risk level is determined to be medium. When the volumetric rate is greater than or equal to the second threshold, the risk level is determined to be high.

[0097] The preset minimum area threshold is set by staff based on historical data analysis results. This historical analysis process includes the system collecting multiple minimum areas and calculating their average value as a reference to obtain the preset minimum area threshold. Similarly, the preset safety factor critical threshold, the preset soil strength deterioration threshold, and the preset erosion shear stress threshold are also set by staff based on the system's historical operating data and the specific application scenario requirements.

[0098] This embodiment maps the effects of rainfall infiltration and seismic action into superimposed pore water pressure time series, achieving isomorphic processing of different disaster-causing factors and solving the problem of unified characterization of multi-source disaster factors at the unit scale. It employs a confluence memory kernel convolution approximation, simulating the transient response of the unit using an exponential decay kernel, while simultaneously considering the permeability limit and upstream water supply. This approximates the transient response of the Richards equations and facilitates analytical and numerical calculations, significantly improving computational efficiency. By combining peak ground acceleration with the effective overburden stress of the unit, the equivalent pore pressure increment is calculated using empirical or semi-analytical mapping, and can be converted into a time series form and superimposed with rainfall pore pressure, achieving quantification and temporal processing of the seismic impact. Based on a spatial cell grid, combined with a digital elevation model, soil layer thickness, and soil unit weight, the permeability characteristics, time delay parameters, and effective overburden stress of each unit are precisely calculated, enabling rainfall and seismic action to respond accurately at the unit scale, improving spatial determination accuracy; and allowing landslide instability determination to more accurately reflect spatial heterogeneity and the dynamic characteristics of disaster triggering.

[0099] By calculating the erosion shear stress of the bottom unit of the gully and comparing it with a preset threshold, the initiation conditions for the transformation of landslides into debris flows can be scientifically identified, improving the accuracy of secondary disaster prediction. Using the transformation volume and rate of the landslide, combined with gully geometry and source remobilization capacity, spatial corrections are made to the deposition area, avoiding the irrationality of fixing the deposition range in traditional methods, making downstream landslide deposition predictions closer to reality. Through the landslide volume transformation rate and downstream deposition area information, a landslide-to-debris flow risk level is established, achieving integrated risk assessment of landslides and debris flows, providing a more comprehensive and scientific basis for disaster prevention and mitigation. Based on a spatial analysis model, the movement, erosion, and transformation risk of the landslide along different cells are quantified, making the assessment results operable and spatially resolvable, suitable for application in complex terrain and multi-source data environments.

[0100] Example 2

[0101] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A landslide hazard risk assessment system based on a spatial analysis model is provided, including:

[0102] The spatial unit division module divides the landslide disaster research area into a spatial cell grid according to slope aspect and geomorphological characteristics, and acquires and stores the geological spatial information of each cell;

[0103] The disaster factor characterization module, based on spatial cell grid, uniformly characterizes disaster triggering events under different disaster scenarios, establishes time-varying pore water pressure response, maps rainfall infiltration effect and earthquake additional impact as equivalent pore pressure increment, performs disaster factor isomorphism processing, and outputs the pore pressure response results of each cell.

[0104] The dual-threshold instability criterion module determines the unstable unit based on the pore pressure response results and the soil strength degradation law, using a dual-threshold criterion based on the safety factor and the degree of deterioration.

[0105] The sliding body identification module performs spatial connectivity analysis on unstable units, identifies potential sliding bodies, evaluates the movement trend of sliding bodies based on the energy balance method, introduces surface roughness and vegetation resistance to correct the movement process, and deduces potential sliding paths and deposition areas.

[0106] The secondary disaster assessment module, after completing the simulation of potential sliding paths and deposition areas, determines the evolution of sliding bodies located in gullies and river channels. When the erosion shear stress reaches the preset judgment rules, it identifies the transformation process of landslides into debris flows and outputs the corresponding risk level, thus conducting an integrated risk assessment of landslides and secondary disasters.

[0107] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0108] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A landslide disaster risk assessment method based on a spatial analysis model, characterized by, The application relates to a landslide disaster risk assessment method based on a spatial unit cell grid. S1, a landslide disaster research region is divided into a spatial unit cell grid according to slope directions and landform characteristics, and the geological spatial information of each unit is acquired and stored; S2, based on the spatial unit cell grid, disaster triggering events under different disaster scenarios are uniformly represented, time-varying pore water pressure responses are established, rainfall infiltration effects and earthquake additional effects are mapped into equivalent pore pressure increments, disaster factor isomorphism processing is carried out, and pore pressure response results of each unit are outputted; The method for establishing the time-varying pore water pressure response comprises the following steps: Defining disaster scenarios including rainfall scenarios and earthquake scenarios, collecting historical rainfall and rainfall duration in the spatial unit cell grid for the rainfall scenario, and evenly distributing the total rainfall to each time step within the rainfall duration, calculating the rainfall intensity of each time step, and obtaining a rainfall duration curve; The rainfall duration curve is processed by using a confluence memory kernel convolution method, the transient equivalent water level rise of each unit is obtained, and the time-varying pore water pressure is converted from the unit weight of water, and the pore pressure time sequence under the action of rainfall is obtained; For the earthquake scenario, the peak ground acceleration in the spatial unit cell grid is calculated by using the seismic record observed by the regional seismic station; the effective overburden stress of the unit is calculated based on the soil layer thickness and the soil body gravity in the spatial unit cell grid; The peak ground acceleration and the effective overburden stress of the unit are combined to calculate the equivalent pore water pressure increment under the action of the earthquake, and the equivalent pore water pressure increment under the action of the earthquake is mapped into an equivalent pore pressure sequence which can be superimposed on the time sequence; S3, according to the pore pressure response result, combining the soil body strength degradation law, using a double-threshold criterion based on a safety factor and a deterioration degree, the unstable unit is determined; S4, the spatial connectivity of the unstable unit is analyzed, the potential sliding body is identified, the movement trend of the sliding body is evaluated based on an energy balance method, the ground roughness and the vegetation resistance are introduced to modify the movement process, and the potential sliding path and the accumulation area are deduced; S5, after the potential sliding path and the accumulation area are deduced, the evolution of the sliding body in the valley and river area is determined, when the erosion shear stress reaches the preset determination rule, the landslide to debris flow conversion process is identified, and the corresponding risk level is outputted, and the landslide and secondary disaster integrated risk assessment is carried out; The method for carrying out the landslide and secondary disaster integrated risk assessment comprises the following steps: After the potential sliding path and the accumulation area are deduced, the lowest unit in each unit of the sliding body reaching the slope foot, the valley or the river area is identified as the channel bottom unit; the erosion shear stress of the channel bottom unit is calculated and compared with the preset erosion shear stress threshold value; When the erosion shear stress is greater than the preset erosion shear stress threshold value, it is judged that the landslide body meets the starting condition of the transformation to the debris flow; the volume rate of the transformation of the landslide body to the debris flow is calculated, the risk level of the transformation of the landslide to the debris flow is judged according to the volume rate of the transformation of the landslide body to the debris flow, and the landslide and secondary disaster integrated risk assessment is carried out. 2.The landslide disaster risk assessment method based on a spatial analysis model according to claim 1, characterized in that, The method for dividing the spatial unit cell grid comprises the following steps: A digital elevation model of a landslide disaster research area is acquired, the digital elevation model is preprocessed, slope, slope direction, curvature and flow accumulation are extracted based on the preprocessed digital elevation model, and a valley line and a ridge line are identified to form a geomorphic framework; The landslide disaster research area is preliminarily divided into different units with the ridge line and the valley line as boundaries, and each unit is divided according to the slope direction consistency criterion; under the premise of meeting the slope direction consistency, a strip-shaped unit grid is generated along the main slope direction, and the grid scale is adaptively controlled through a preset unit length-width ratio and a preset minimum area threshold; The units that do not meet the preset unit length-width ratio and the preset minimum area threshold are preferentially merged with adjacent units with similar slope directions, and the generated strip-shaped unit grid is topologically checked and coded to form a spatial unit grid. 3.The landslide disaster risk assessment method based on a spatial analysis model according to claim 2, characterized in that, The method for acquiring the geological spatial information comprises: Based on the generated spatial unit grid, the geological spatial information of each unit is acquired and stored from a digital elevation model, remote sensing images and geological survey data through indexing by unit coding and spatial position, and the geological spatial information comprises slope, slope direction, curvature, flow accumulation, slope length and geomorphic position. 4.The landslide disaster risk assessment method based on a spatial analysis model according to claim 3, characterized in that, The method for outputting the pore pressure response results of each unit comprises: The pore pressure time series under the action of rainfall and the equivalent pore pressure sequence after seismic mapping are superimposed to form a unified time-varying pore water pressure response sequence of each spatial unit, the isomorphic processing of disaster factors is realized, and the unified pore pressure response results of each spatial unit are outputted. 5.The landslide disaster risk assessment method based on a spatial analysis model according to claim 4, characterized in that, The method for determining the unstable units comprises: Based on the unified time-varying pore water pressure response sequence of each spatial unit, the safety factor of each unit is calculated over time in combination with the unit soil strength degradation law, and the safety factor is acquired according to the ratio of the unit shear strength to the effective shear stress affected by the pore water pressure; A preset safety factor threshold and a preset soil strength degradation degree threshold are set, the safety factor is compared with the preset safety factor threshold, and the soil strength degradation degree is compared with the preset soil strength degradation degree threshold; When the unit safety factor is less than the preset safety factor threshold and the soil strength degradation degree is greater than the preset soil strength degradation degree threshold, the unit is determined as an unstable unit; and the spatial position, the instability time, the corresponding safety factor and the soil strength degradation degree of the unstable unit are outputted. 6.The landslide disaster risk assessment method based on a spatial analysis model according to claim 5, wherein, The method for evaluating the movement trend of the sliding body comprises: The unstable units are identified in the spatial unit grid to form an unstable unit set; for each unstable unit, the spatial adjacency relationship with adjacent units is checked, and the adjacency relationship is determined by shared edges or shared vertices of the units; and according to the adjacency relationship between the units, the unstable units that are connected to each other are merged into different connected domains, and each connected domain is a candidate region of a potential sliding body; The method for outputting the movement trend of the sliding body comprises: The movement trend of the sliding body is outputted according to the spatial position of the unstable unit set. The method comprises the following steps: 7.The landslide disaster risk assessment method based on a spatial analysis model according to claim 6, wherein, The method for deducing the potential sliding path and the accumulation area comprises the following steps: An energy balance model is established to calculate the gravitational potential energy release, friction resistance consumption and surface resistance during the movement of the sliding body, in which the surface roughness is added to the friction resistance consumption as a friction correction factor; the vegetation coverage type and density information of the sliding body are obtained, the vegetation resistance coefficient is calculated through field investigation, and the additional friction during the movement of the sliding body is converted; Based on the corrected energy balance model, the path is deduced along the main sliding direction of each potential sliding body, the energy surplus of the sliding body on each unit is gradually calculated, and the movement trend of the sliding body is judged according to the energy surplus; if the energy surplus is positive, the sliding body moves along the main slope direction, if the energy surplus is zero or negative, the movement of the sliding body is blocked; According to the movement termination position of the sliding body and the spatial distribution along the path, the spatial range of the potential accumulation area is formed; and the space buffer algorithm is used to correct the boundary of the accumulation area according to the slope foot terrain, the valley width and the slope bottom resistance condition, and the sliding path and the corresponding accumulation area spatial information of each potential sliding body are output.

8. A landslide disaster risk assessment system based on a spatial analysis model, for implementing a landslide disaster risk assessment method based on a spatial analysis model according to any one of claims 1 to 7, characterized in that, It comprises: The spatial unit division module divides the landslide disaster research area into a spatial unit grid according to the slope direction and the landform characteristics, obtains and stores the geological spatial information of each unit; The disaster factor representation module uniformly represents the disaster triggering events under different disaster scenarios based on the spatial unit grid, establishes the time-varying pore water pressure response, maps the rainfall infiltration effect and the earthquake additional influence into equivalent pore pressure increment, performs the isomorphism processing of the disaster factors, and outputs the pore pressure response results of each unit; The double-threshold instability criterion module determines the unstable unit by using the double-threshold criterion based on the safety factor and the deterioration degree according to the pore pressure response results and the soil strength degradation law; The sliding body identification module analyzes the spatial connectivity of the unstable units, identifies the potential sliding body, evaluates the movement trend of the sliding body based on the energy balance method, introduces the surface roughness and the vegetation resistance to correct the movement process, and deduces the potential sliding path and the accumulation area; The secondary disaster evaluation module, after completing the deduction of the potential sliding path and the accumulation area, determines the evolution of the sliding body in the valley and the river area, identifies the conversion process of the landslide to debris flow when the erosion shear stress reaches the preset determination rule, and outputs the corresponding risk level, and performs the integrated risk assessment of the landslide and the secondary disaster.

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