Method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment

Abstract

The invention provides a method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment, comprising the following steps: S1, constructing a threshold model as follows: #imgabs0# S2, using the rainfall threshold model to analyze the rainfall threshold that induces landslide disasters, thereby determining the regional slope benchmark threshold R S S3. Select the controlling slope geological environmental factors in the region based on the slope deformation and failure mechanism; S4. Describe the overall benchmark slope of the region based on the selected slope geological environmental factors; S5. Use numerical simulation methods to determine the slope stability changes caused by each slope geological environmental factor of the benchmark slope under different rainfall conditions, and obtain the threshold adjustment change ΔR caused by each slope geological environmental factor at different durations. i The beneficial effects of the present invention are as follows: considering the impact of various geological environmental factors on slope stability during rainfall infiltration, the threshold system based on the disaster-pregnancy mechanism improves the accuracy of early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering geological landslide early warning and forecasting, and in particular to a method for establishing a rainfall-type landslide risk early warning threshold system based on geological environment. Background Art

[0002] Landslides are a common natural disaster, causing significant casualties and economic losses annually. Over half of landslides in my country are rainfall-induced. Rainfall infiltration alters the physical and mechanical properties of the landslide rock and soil, disturbs the groundwater level, and reduces the shear strength of the soil, thereby affecting slope stability. To prevent and mitigate these types of landslides, a meteorological landslide risk warning system must be established. The key to this is the selection of landslide warning thresholds.

[0003] Research on rainfall-induced geological disaster early warning and its thresholds can be summarized into two categories: 1. Statistical analysis methods, which collect historical rainfall data and geological disaster occurrence data and conduct statistical comparative analysis to determine qualitative, semi-quantitative, or quantitative relationships between geological disasters and rainfall. This method is currently widely used. Statistical thresholds are divided into four categories: rainfall intensity-duration threshold (ID), cumulative rainfall threshold (E), cumulative rainfall-duration threshold (ED), and cumulative rainfall-intensity threshold (EI). Based on these thresholds, many countries and regions have established early warning systems for rainfall-induced landslides. 2. Mechanistic analysis methods, which primarily use slope hydrological models to analyze the rainfall-seepage-hazard mechanism to analyze the early warning thresholds for rainfall-induced landslides.

[0004] However, in the practice of landslide early warning and forecasting, the current threshold model has the following problems: ① The threshold model based on mathematical statistics is a statistical result of multiple landslides that have occurred in the region. Its accuracy is directly controlled by the precision and number of samples. Therefore, it has strict requirements on the historical disaster records used for analysis; ② The threshold model based on mathematical statistics ignores the physical process of landslide occurrence, especially the change process of the physical and mechanical properties of landslide rock and soil after rainfall infiltration, which makes it impossible to explain the threshold from the perspective of disaster mechanism. Specifically for a single landslide, the error is large, resulting in a large number of false alarms and missed alarms of landslides, and the overall forecast accuracy is low; ③ The threshold model based on mathematical statistics is a macro consideration of a region. However, the geological environmental conditions of different slopes vary greatly. Specifically for each slope, the statistical threshold cannot be adjusted according to the characteristics of the slope, which also limits the accuracy of the threshold in application practice. Summary of the Invention

[0005] In view of this, in order to solve the problem of obtaining warning thresholds using threshold models for rainfall-induced landslide disasters in the background art, an embodiment of the present invention provides a method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment.

[0006] An embodiment of the present invention provides a method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment, characterized by comprising the following steps:

[0007] S1. Construct a rainfall-induced landslide meteorological risk warning threshold model based on the slope geological environment as follows:

[0008]

[0009] Among them, R is the meteorological risk warning threshold for slope geological disasters, R S is the regional slope reference threshold, ΔR i represents the threshold adjustment change brought about by various geological environmental factors; η is the effective rainfall coefficient;

[0010] S2. Use the rainfall threshold model to analyze the rainfall threshold that induces landslide disasters, and thus determine the regional slope benchmark threshold R S ;

[0011] S3. Select the controlling slope geological environmental factors in the region based on the slope deformation and failure mechanism;

[0012] S4. Describe the overall regional benchmark slope based on the selected slope geological environment factors;

[0013] S5. Use numerical simulation to determine the slope stability change caused by each slope geological environment factor of the benchmark slope under different rainfall conditions, and obtain the threshold adjustment change ΔR caused by each slope geological environment factor at different durations. i , thereby establishing a rainfall-induced landslide meteorological risk warning threshold system based on the slope geological environment from regional to slope scales.

[0014] Furthermore, in step S3, all slope geological environmental factors are divided into three categories: slope spatial structure, slope material composition and hydrological conditions.

[0015] Furthermore, the slope spatial structure includes the slope gradient α, the thickness d of the loose rock and soil, and whether the slope is cut; the slope material composition includes the rock and soil cohesion c, the internal friction angle φ, and the permeability coefficient k; and the hydrological conditions include the vegetation type.

[0016] Furthermore, in step S4, when the slope geological environment factor is a continuous factor, the average value is used to characterize the benchmark slope; when the slope geological environment factor is a discrete factor, the mode is used to characterize the benchmark slope.

[0017] Furthermore, the threshold adjustment change ΔR caused by each slope geological environment factor in step S5 i The method of determining is:

[0018] Determine the upper and lower limits of the threshold adjustment changes brought about by each geological environmental factor;

[0019] Threshold adjustment change ΔR caused by ramp gradient α =m α α+n α , where m α 、n α is the coefficient;

[0020] Threshold adjustment change ΔR caused by cover layer thickness d =m d d+n d , where m d 、n d is the coefficient;

[0021] Threshold adjustment change ΔR caused by internal friction angle φ =m φ φ+n φ , where m φ 、n φ is the coefficient;

[0022] Threshold adjustment change ΔR caused by cohesion c : The cohesion c0 when the threshold adjustment change caused by the cohesion c is 0 is used as the baseline cohesion. When the cohesion c increases by Δc relative to the baseline cohesion c0, ΔR c Adjust to the upper limit, and adjust the middle linear interpolation; when the cohesion c decreases by Δc relative to the reference cohesion c0, ΔR c Adjust to the lower limit, and adjust by linear interpolation in the middle;

[0023] Threshold adjustment change ΔR caused by permeability coefficient k : The cohesion k0 when the threshold adjustment change brought by the permeability coefficient k is 0 is used as the permeability coefficient. When the k value increases to the first permeability coefficient k1 and above, ΔR k Take the lower limit; when the k value decreases to the second permeability coefficient k2 and below, ΔR k Take the upper limit;

[0024] Threshold adjustment change ΔR caused by slope cutting slope : When there is a cut slope, ΔR slope 0; ΔR when there is no slope slope As the upper limit.

[0025] Furthermore, the upper and lower limits of the threshold adjustment change brought about by each geological environmental factor are respectively ±20% of the regional slope benchmark threshold.

[0026] Furthermore, in step S5, the threshold adjustment change ΔR caused by each slope geological environment factor over a period of 1 / 3 / 6 / 12 / 24 hours is obtained. i .

[0027] Furthermore, the calculation formula of the effective rainfall coefficient η is as follows:

[0028] η=O / P

[0029] Where: P is the rainfall; O is the rainfall that is not intercepted by the canopy and penetrates.

[0030] Furthermore, in step S2, the ID threshold model is used to analyze the rainfall threshold that induces landslide disasters. The power exponential form of the threshold model is expressed as follows:

[0031] I=a+γD β

[0032] Where: I is the cumulative rainfall; D is the rainfall duration; γ, β, and a are statistical parameters, and a ≥ 0.

[0033] Furthermore, in step S3, the selection of the slope geological environment factor is determined by the principle of geological environment factor validity and the principle of geological environment factor parameter accessibility.

[0034] The beneficial effects brought about by the technical solution provided by the embodiments of the present invention are:

[0035] 1. The present invention provides a method for establishing a rainfall-induced landslide risk warning threshold system based on the geological environment. Starting from the geological environmental conditions of slopes where landslides develop, the method considers the impact of various geological environmental factors on slope stability during rainfall infiltration. The threshold system based on the disaster-pregnancy mechanism improves the accuracy of warnings.

[0036] 2. The present invention provides a method for establishing a rainfall-induced landslide risk warning threshold system based on the geological environment. This system establishes a slope-scale rainfall-induced landslide warning threshold system, which can meet the needs of slope-scale meteorological warnings based on regional geological disaster meteorological warnings, achieving a one-slope-one-threshold system. When slope environmental conditions change, the threshold can be dynamically adjusted based on the changes in environmental factors through a threshold model, thereby matching the warning threshold to the actual slope state. This warning threshold system can provide a scientific theoretical basis and technical support for geological disaster risk meteorological warning and management.

[0037] 3. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment of the present invention is applicable to the early warning and forecast of rainfall-induced landslides in mountainous and hilly areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1It is a rainfall-induced landslide meteorological risk warning threshold model based on the slope geological environment;

[0039] Figure 2 is the rainfall-induced landslide ID threshold curve in the study area of the embodiment;

[0040] Figure 3 is the benchmark slope model of the study area of the embodiment;

[0041] Figure 4 It is 1h-50mm rainfall condition;

[0042] Figure 5 It is 3h-90mm rainfall condition;

[0043] Figure 6 It is a 6h-138mm rainfall condition;

[0044] Figure 7 It is 12h-252mm rainfall condition;

[0045] Figure 8 It is a 24h-300mm rainfall condition;

[0046] Figure 9 is the change in stability coefficient of slopes with different slope gradients under 1h-50mm rainfall conditions;

[0047] Figure 10 It is the adjustment amount of rainfall threshold for slopes with different slope gradients under 1h-50mm rainfall conditions;

[0048] Figure 11 is the change in stability coefficient of slopes with different slope gradients under 3h-90mm rainfall conditions;

[0049] Figure 12 It is the adjustment amount of rainfall threshold for slopes with different slope gradients under 3h-90mm rainfall conditions;

[0050] Figure 13 is the change in stability coefficient of slopes with different slope gradients under 6h-138mm rainfall conditions;

[0051] Figure 14 It is the adjustment amount of rainfall threshold for slopes with different slope gradients under 6h-138mm rainfall conditions;

[0052] Figure 15 is the change in stability coefficient of slopes with different slope gradients under 12h-252mm rainfall conditions;

[0053] Figure 16 It is the adjustment amount of rainfall threshold for slopes with different slope gradients under 12h-252mm rainfall conditions;

[0054] Figure 17It is the change of stability coefficient of slopes with different slope gradients under 24h-300mm rainfall conditions;

[0055] Figure 18 It is the adjustment amount of rainfall threshold for slopes with different slope gradients under 24h-300mm rainfall conditions;

[0056] Figure 19 is the change in stability coefficient of slopes with different cover thicknesses under 1h-50mm rainfall conditions;

[0057] Figure 20 is the adjustment amount of the slope rainfall threshold for different cover thicknesses under 1h-50mm rainfall conditions;

[0058] Figure 21 is the change in stability coefficient of slopes with different cover thicknesses under 3h-90mm rainfall conditions;

[0059] Figure 22 is the adjustment amount of the slope rainfall threshold for different cover thicknesses under 3h-90mm rainfall conditions;

[0060] Figure 23 is the change in stability coefficient of slopes with different cover thicknesses under 6h-138mm rainfall conditions;

[0061] Figure 24 It is the adjustment amount of the slope rainfall threshold under the 6h-138mm rainfall condition with different cover thicknesses;

[0062] Figure 25 is the change in stability coefficient of slopes with different cover thicknesses under 12h-252mm rainfall conditions;

[0063] Figure 26 It is the adjustment amount of the slope rainfall threshold under the rainfall condition of 12h-252mm with different cover thickness;

[0064] Figure 27 is the change in stability coefficient of slopes with different cover thicknesses under 24h-300mm rainfall conditions;

[0065] Figure 28 It is the adjustment amount of the slope rainfall threshold under the 24h-300mm rainfall condition with different cover thicknesses;

[0066] Figure 29 is the change in stability coefficient of slopes with different internal friction angles under 1h-50mm rainfall conditions;

[0067] Figure 30 It is the adjustment amount of rainfall threshold for slopes with different internal friction angles under 1h-50mm rainfall conditions;

[0068] Figure 31is the change in stability coefficient of slopes with different internal friction angles under 3h-90mm rainfall conditions;

[0069] Figure 32 It is the adjustment amount of rainfall threshold for slopes with different internal friction angles under 3h-90mm rainfall conditions;

[0070] Figure 33 is the change in stability coefficient of slopes with different internal friction angles under 6h-138mm rainfall conditions;

[0071] Figure 34 It is the adjustment amount of rainfall threshold for slopes with different internal friction angles under 6h-138mm rainfall conditions;

[0072] Figure 35 is the change in stability coefficient of slopes with different internal friction angles under 12h-252mm rainfall conditions;

[0073] Figure 36 It is the adjustment amount of rainfall threshold for slopes with different internal friction angles under 12h-252mm rainfall conditions;

[0074] Figure 37 is the change in stability coefficient of slopes with different internal friction angles under 24h-300mm rainfall conditions;

[0075] Figure 38 is the threshold adjustment for slopes with different internal friction angles under 24h-300mm rainfall conditions;

[0076] Figure 39 is the initial F of slopes with different cohesion under rainfall conditions s and the lowest F s Value fitting curve;

[0077] Figure 40 is the change in stability coefficient of slopes with different permeability coefficients under rainfall conditions;

[0078] Figure 41 It is the fitting curve of the stability coefficient change value of slopes with different permeability coefficients under rainfall conditions;

[0079] Figure 42 It is the initial stability coefficient of slopes with different cover thicknesses with and without cut slopes. DETAILED DESCRIPTION

[0080] To make the objectives, technical solutions, and advantages of the present invention more apparent, embodiments of the present invention will be further described below with reference to the accompanying drawings. The following describes a preferred embodiment of the present invention among multiple possible embodiments, which is intended to provide a basic understanding of the present invention but is not intended to identify the key or decisive elements of the present invention or to limit the scope of protection.

[0081] In all examples shown and discussed herein, any specific values should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0082] Technologies, methods, and equipment known to those skilled in the art may not be discussed in detail.

[0083] However, where appropriate, the technology, methods and equipment described shall be deemed to be part of the license specification. Figure 1 The embodiment of the present invention provides a method for establishing a rainfall-induced landslide risk warning threshold system based on the geological environment, which is particularly suitable for early warning and forecasting of rainfall-induced landslides in mountainous and hilly areas in southern my country, represented by Zhejiang Province, and mainly includes the following steps S1-S5.

[0084] S1. Constructing a meteorological risk warning threshold model for rainfall-induced landslides based on the slope geological environment:

[0085] The meteorological risk warning threshold model for rainfall-induced landslides based on the slope geological environment includes two parts: the regional benchmark threshold and the slope geological environment factor adjustment method. Figure 1 Since the geological environment conditions of each slope are different, the core content of the model is to characterize the specificity of the slope and formulate an adjustment plan for the rainfall threshold brought about by different slope geological environments.

[0086] The regional benchmark threshold uses the ID threshold model to propose a meteorological warning threshold for regional geological hazard risk. The mechanism of rainfall-induced landslide disasters is analyzed, and numerical simulation methods are used to simulate the rainfall infiltration process on slopes. This explores the changes in slope stability caused by slope geological environmental conditions and derives a rainfall threshold adjustment scheme. The meteorological risk warning threshold model for rainfall-induced landslides based on the slope geological environment is as follows:

[0087]

[0088] Where R is the meteorological risk warning threshold for slope geological disasters, R S is the regional slope reference threshold, ΔR i It represents the threshold adjustment change brought about by various geological environmental factors; η is the effective rainfall coefficient.

[0089] S2. Use the rainfall threshold model to analyze the rainfall threshold that induces landslide disasters, and thus determine the regional slope benchmark threshold R S .

[0090] The ID threshold model is used to analyze the rainfall threshold that triggers landslide disasters. The model is often expressed in the form of a power exponent as follows:

[0091] I=a+γD β

[0092] Where: I is the cumulative rainfall (mm); D is the rainfall duration; γ, β, and a are statistical parameters, and a ≥ 0.

[0093] With rainfall duration as the horizontal axis and average rainfall intensity as the vertical axis, a semi-logarithmic coordinate scatter plot was drawn, and the ID threshold curve was fitted. The classification threshold was determined according to the probability levels of 0%, 20%, 40%, and 60% for landslide occurrence, and the rainfall intensity and cumulative rainfall were calculated to obtain the threshold result based on the ID model, which is the regional slope benchmark threshold R S .

[0094] Collect the hourly rainfall data of the meteorological station in the study area for many years (corresponding to the landslide records), and obtain the threshold value result based on the ID model according to the method described ( Figure 2 ), which is the benchmark threshold of rainfall-induced landslide in the study area of the embodiment (Table 1).

[0095] Table 1 Example Study Area Rainfall-induced Landslide Early Warning Benchmark Thresholds

[0096]

[0097] S3. Select the controlling geological environmental factors of the slope in the region based on the mechanism of slope deformation and failure:

[0098] The geological environment of a slope encompasses multiple factors, making it difficult to fully incorporate them into evaluation models. Therefore, it is essential to select a subset of these factors for threshold adjustment calculations. Two principles have been proposed for selecting these factors, combining the fundamental methods of engineering geology with the actual geological hazards in the work area: the principle of geological environmental factor validity and the principle of geological environmental factor parameter accessibility.

[0099] The effectiveness of geological environmental factors means that the selected geological environmental factors play a decisive and major role in the deformation and destruction of slopes under rainfall, and can reflect the mechanism of slope deformation and destruction.

[0100] The availability of geological environment factor parameters means that the selected geological environment factor parameters can be obtained in the actual survey work, and the acquisition method is simple and the data accuracy can be guaranteed. The reason is that with the reduction of the evaluation unit size and the exponential growth of the number of evaluation units, the data collection work is massive, so the availability of factor parameters must be guaranteed.

[0101] The proposed rainfall-induced landslide meteorological risk warning threshold model based on the slope geological environment takes into account three geological environmental factors in the study area of this example: slope spatial structure, slope material composition, and hydrological conditions. Slope spatial structure includes slope gradient α, loose rock and soil thickness d, and whether the slope is cut; slope material composition includes rock and soil cohesion c, internal friction angle φ, and permeability coefficient k; and hydrological conditions focus on vegetation type.

[0102] S4. Describe the regional benchmark slope based on the selected slope geological environment factors:

[0103] The benchmark slope is a generalized slope that represents the characteristics of the slopes in the study area. It is not necessarily a physical slope. Its core function is to comprehensively characterize and describe the geological environment conditions of the slopes in the study area. It represents the general state of slopes in the region. Based on the selected slope geological environment factors, regional slopes are surveyed and statistically analyzed to characterize the benchmark slope for the entire region. In this example, the average values of the five continuous factors (slope gradient, loose rock thickness, rock cohesion, internal friction angle, and permeability coefficient) are used to characterize the benchmark slope. For the two discrete factors (whether the slope is cut and vegetation type), the mode is used to represent the slopes of the entire region.

[0104] The rainfall-induced landslide in the study area of this embodiment is a shallow slip in the overburden layer and is small in scale. An infinite slope model is established based on the benchmark slope in the study area, such as Figure 3 The model is a rock-soil mixed slope with a loose overburden layer. The toe of the slope cuts through the overburden layer. The infinite slope geological model has a slope of 25°, a 3m thick overburden layer, and a 5m high cut.

[0105] S5. Use numerical simulation to determine the slope stability change caused by each slope geological environment factor of the benchmark slope under different rainfall conditions, and obtain the threshold adjustment change ΔR caused by each slope geological environment factor at different durations. i , thereby establishing a rainfall-induced landslide meteorological risk warning threshold system based on the slope geological environment from regional to slope scales.

[0106] Determination of threshold adjustment rules

[0107] Taking into account the differences in geological environmental conditions across the region, and based on rainfall infiltration patterns, numerical simulation methods are used to explore the changes in slope stability caused by various geological environmental factors under different rainfall conditions, thereby deriving patterns of rainfall threshold changes over different durations. Furthermore, considering the practical needs of landslide early warning and the effectiveness of these patterns, it is necessary to restrict the threshold adjustment range, determining upper and lower limits for the threshold adjustment caused by each geological environmental factor. In this embodiment, the upper and lower limits for the threshold adjustment caused by each geological environmental factor are respectively ±20% of the regional slope baseline threshold.

[0108] This model's threshold adjustment method draws inspiration from the mechanism of rainfall infiltration and analyzes how various geological environmental factors affect seepage or soil strength. Slope rainfall infiltration is the process by which water moves from the surface to the water table, encompassing the transition from unsaturated to saturated soil on a slope. The infiltration process is influenced by rainfall intensity and soil permeability. Furthermore, as infiltration progresses, soil moisture increases, matrix suction decreases, the water potential gradient decreases, and the infiltration rate slows, ultimately leading to stable infiltration.

[0109] This embodiment fully considers the differences in geological environmental conditions among various slopes in the region, establishes a model for the gradient changes of geological environmental factors on each slope, studies the variation patterns of the seepage field of typical slopes after factor changes under rainfall conditions, and analyzes the trends and patterns of slope stability changes, thereby inverting the variation patterns of the slope instability warning threshold.

[0110] In order to realize geological disaster early warning under different rainfall duration conditions, this embodiment forms geological disaster rainfall thresholds of 1 / 3 / 6 / 12 / 24h. According to the rainfall thresholds of different durations, the setting of rainfall conditions is divided into two categories: one is a short-term heavy rainfall process of 1 / 3 / 6h, and the other is a rainfall process of 12 / 24h. According to the typical disaster-causing short-term heavy rainfall process, the rainfall conditions of 1 / 3 / 6h are set, and the total rainfall is 50mm ( Figure 4 ), 90mm( Figure 5 ) and 138mm( Figure 6 ), maintaining uniform rainfall intensity. According to the typical typhoon rainfall process that causes disasters, the rainfall conditions lasting 12 and 24 hours were set. The 12-hour rainfall process ( Figure 7 ) The total rainfall was 252 mm, and the rainfall intensity changed with time, showing an overall trend of first increasing and then decreasing; similarly, the total rainfall in 24 hours was 300 mm ( Figure 8 ), the rainfall intensity reached its peak within 16-17 hours, and the overall rainfall process was in line with the typical typhoon rainfall distribution pattern.

[0111] According to the influence of slope α, the threshold adjustment change ΔR caused by the slope is determined α :

[0112] Slope gradient is a key factor affecting slope stability under rainfall conditions. The greater the slope gradient, the smaller its initial stability coefficient. Under rainfall conditions, the slope stability factor has a smaller safety margin, making it more susceptible to instability.

[0113] The embodiment establishes slope models with slopes of 15°, 20°, 25°, 30°, and 35° and a cover thickness of 3m. The initial stability coefficients of slopes with different slopes are made equal, and the variation law of their stability coefficients under the same rainfall conditions is explored. The threshold adjustment change ΔR caused by the slope gradient α =m α α+n α , where m α 、n α is the coefficient. Specifically:

[0114] Figure 9 The stability coefficient of slopes with different slope gradients under 1h-50mm rainfall conditions is shown in the figure. Under the condition of 50mm rainfall in 1h, the slope stability coefficient continues to decrease. When the cumulative rainfall is 30mm, the stability coefficient of the 35° slope decreases to 1.0, and the slope is in an unstable state. The critical rainfall for slopes with slopes of 30°, 25°, 20° and 15° are 35mm, 40mm, 45mm and 50mm respectively. According to the above law between the rainfall and slope changes during instability, under 1h rainfall, the adjustment rule of the rainfall threshold and the slope gradient satisfies the relationship y=-x+25( Figure 10 Taking into account the actual needs of early warning work and the limitations of actual slope changes, the final adjustment range of the threshold is restricted, that is, the rainfall threshold range for the 1-hour red warning is 32-48 mm.

[0115] Similarly: the slope stability changes under 3h rainfall are as follows: Figure 11 As shown, the adjustment rule of the rainfall threshold and slope gradient for different slopes is: y = -1.5x + 36.9 ( Figure 12 ), the threshold adjustment limit range is 60-90mm; the slope stability changes under 6h rainfall are as follows Figure 13 As shown, the threshold adjustment rule is: y = -2.3x + 57.5 ( Figure 14 ), the threshold adjustment limit range is 92-138mm; the slope stability changes under 12h rainfall are as follows Figure 15 As shown, the threshold adjustment rule is: y = -3.36 + 83.4 ( Figure 16 ), the threshold adjustment limit range is 162-252mm; the slope stability changes under 24h rainfall are as follows Figure 17 As shown, the threshold adjustment rule is: y = -4.72x + 118 ( Figure 18 ), the threshold adjustment limit range is 200-300mm.

[0116] Determine the threshold adjustment change ΔR caused by the covering layer thickness according to the influence law of the covering layer thickness d d :

[0117] The thickness of a slope's cover layer is a significant factor influencing slope stability under rainfall conditions. The thicker the slope's cover layer, the smaller its initial stability coefficient and the smaller the decrease in its stability coefficient. This is because the thicker the cover layer, the greater the deadweight of the overlying soil, and the greater the downward force on the slope. Under the same rainfall conditions, slopes with different cover layer thicknesses react differently to rainfall infiltration. The thinner the cover layer, the more likely the slope is to reach saturation under rainfall infiltration, resulting in a loss of matrix suction, a decrease in the shear strength of the slope soil, and a greater decrease in slope stability. Conversely, the thicker the cover layer, the longer the saturation time or even the inability to reach saturation under the same rainfall conditions. Therefore, if the initial slope stability is low, the decrease in stability is limited.

[0118] The present embodiment establishes a slope model with a cover layer thickness of 2m, 3m, 4m, and 5m and a slope of 25°. The initial stability coefficients of slopes with different cover layer thicknesses are made equal, and the variation pattern of their stability coefficients under the same rainfall conditions is explored. The threshold adjustment change ΔR caused by the cover layer thickness is d =m d d+n d , where m d 、n d is the coefficient. Specifically:

[0119] Under the condition of 50mm rainfall in 1h, the slope stability coefficient continues to decrease ( Figure 19 ). When the cumulative rainfall is 35mm, the slope stability coefficient of d = 2m is reduced to 1.0, and the slope is in an unstable state. The critical rainfall of slopes with cover layer thickness of 3m, 4m, and 5m are 40mm, 45mm, and 50mm respectively. According to the above law between the rainfall and cover layer thickness changes during instability, under 1h rainfall, the adjustment rule of rainfall threshold and slope cover layer thickness satisfies the relationship y = 5x-15( Figure 20 ), the threshold adjustment limit range is 32-48mm.

[0120] Similarly: the slope stability changes under 3h rainfall are as follows: Figure 21 As shown in the figure, the adjustment rule of slope rainfall threshold and slope gradient for different cover layer thickness is: y = 9.8x - 29.7 ( Figure 22 ), the threshold adjustment limit range is 60-90mm; the slope stability changes under 6h rainfall are as follows Figure 23 As shown, the threshold adjustment rule is: y = 13.9x-41.7 ( Figure 24 ), the threshold adjustment limit range is 92-138mm; the slope stability changes under 12h rainfall are as follows Figure 25 As shown, the threshold adjustment rule is: y = 14.5x-45.5 ( Figure 26), the threshold adjustment limit range is 162-252mm; the slope stability changes under 24h rainfall are as follows Figure 27 As shown, the threshold adjustment rule is: y = 28.5x-78.5 ( Figure 28 ), the threshold adjustment limit range is 200-300mm.

[0121] According to the influence of the internal friction angle φ, the threshold adjustment change ΔR caused by the internal friction angle is determined φ :

[0122] The internal friction angle φ is a key parameter that determines the shear strength of soil. Changes in the internal friction angle directly affect slope stability. As the internal friction angle increases, the soil's shear strength increases, and the slope stability coefficient increases. As the internal friction angle decreases, the soil's shear strength decreases, and the slope stability coefficient decreases.

[0123] In this example, a slope model with internal friction angles of 15°, 20°, 25°, 30°, and 35°, a cover thickness of 3m, and a slope gradient of 25° was established. The initial stability coefficients of slopes with different internal friction angles were made equal, and the variation pattern of their stability coefficients under the same rainfall conditions was explored. The threshold adjustment change ΔR caused by the internal friction angle is φ =m φ φ+n φ , where m φ 、n φ is the coefficient. Specifically:

[0124] Under the same rainfall conditions, slopes generally reach saturation at the same time, due to the same overburden thickness, permeability coefficient, and slope gradient. At this point, the stability coefficient drops to its lowest value. When the slope's Fs value reaches 1.0, the slope becomes unstable, and the accumulated rainfall at this point is the rainfall threshold. Due to differences in initial Fs values, slopes with different internal friction angles experience different instability times. A larger initial Fs value indicates a longer time to slope instability and a correspondingly higher rainfall threshold.

[0125] Under the condition of 50mm rainfall in 1h, the slope stability coefficient continues to decrease ( Figure 29 ). When the cumulative rainfall is 23mm, the stability coefficient of the slope with φ=15° is reduced to 1.0, and the slope is in an unstable state. The critical rainfall of the slopes with internal friction angles of 20°, 25°, 30°, and 35° are 35mm, 43mm, 47mm, and 49mm, respectively. According to the above-mentioned law between the rainfall and the change of the internal friction angle during instability, under 1h rainfall, when the internal friction angle is less than 25°, the rainfall threshold is too small, that is, the slope becomes unstable under small rainfall conditions, and its law is different from that of slopes of 25° and above; when the internal friction angle is greater than 25°, the adjustment rule of the rainfall threshold and the slope internal friction angle satisfies the relationship y=0.6x-15( Figure 30), the threshold adjustment limit range is 32-48mm.

[0126] Similarly: the slope stability changes under 3h rainfall are as follows: Figure 31 As shown in the figure, the adjustment rule of the rainfall threshold and slope gradient for slopes with different internal friction angles is: y = 0.8x-20( Figure 32 ), the threshold adjustment limit range is 60-90mm; the slope stability changes under 6h rainfall are as follows Figure 33 As shown, the threshold adjustment rule is: y = 1.38x-34.5 ( Figure 34 ), the threshold adjustment limit range is 92-138mm; the slope stability changes under 12h rainfall are as follows Figure 35 As shown, the threshold adjustment rule is: y = x-25 ( Figure 36 ), the threshold adjustment limit range is 162-252mm; the slope stability changes under 24h rainfall are as follows Figure 37 As shown, the threshold adjustment rule is: y = 1.8x-45 ( Figure 38 ), the threshold adjustment limit range is 200-300mm.

[0127] According to the influence law of cohesion c, the threshold adjustment change ΔR caused by cohesion is determined c :

[0128] Cohesion, c, is a key parameter that determines soil shear strength. Changes in cohesion directly affect slope stability. Increasing cohesion increases soil shear strength and the slope stability coefficient. Decreasing cohesion decreases soil shear strength and reduces the slope stability coefficient.

[0129] Based on a slope with a slope of 25° and a cover layer thickness of 3m, the changes in the stability coefficient of the slope are calculated when the cohesion values are 15kPa, 20kPa, 25kPa, 30kPa, and 35kPa respectively. Figure 39 is the initial F under different cohesion conditions s and the lowest F s The curve shows that the c value directly causes the change of the initial stability coefficient. The c value increases, the initial F s increases accordingly; c value decreases, initial F s The initial F value decreases and the initial F value changes with different c values. s The value distribution shows a linear change relationship, which conforms to the fitting formula F s1 =0.0566x+0.3349. The change of c value will not lead to the change of stability coefficient. When the c value is large, the minimum F s When the c value is small, the lowest F s The value is also smaller, and the lowest F at different c values sThe value distribution shows a linear change relationship, which conforms to the fitting formula F s2 =0.0557x+0.1204.

[0130] The above results show that changes in the c value only lead to changes in the initial slope stability coefficient and the corresponding minimum stability coefficient after rainfall, and they show a highly linear correlation with each other, increasing and decreasing at the same time. Therefore, the larger the c value, the greater the slope stability coefficient, the greater the safety margin, and the greater the critical rainfall threshold required to induce slope instability. In the generalized slope model, the initial slope stability coefficient is controlled by c and φ. Figure 39 The calculation results are obtained by controlling the φ value for the same benchmark and changing the c value. This simply reflects the change in the stability coefficient caused by changes in c. In actual natural slopes, c and φ values have a wide range of complex combinations. When determining rainfall thresholds for various slopes, it is necessary to consider both the regular changes in the stability coefficient caused by changes in c and the stability coefficient controlled by both c and φ.

[0131] Specifically, when determining the threshold, the F value caused by the increase of the c value can be referred to. s The law of increasing value, at the same time, it should be noted that F s The value is also affected by the φ value, and there may be a negative correlation, that is, the φ value may decrease. Therefore, when designing the change rule of the rainfall threshold caused by the change of the c value, it is important to consider the negative correlation between c and φ. The rainfall threshold is adjusted up and down based on the threshold adjustment change caused by the cohesion c of the slope model c0 = 25kPa as 0. Specifically, when the cohesion c increases by Δc relative to the baseline cohesion c0, ΔR c Adjust to the upper limit, and adjust the middle linear interpolation; when the cohesion c decreases by Δc relative to the reference cohesion c0, ΔR c Adjust to the lower limit and adjust by linear interpolation in the middle, where Δc = 10 kPa.

[0132] Determine the threshold adjustment change ΔR caused by the permeability coefficient based on the influence law of the permeability coefficient k k :

[0133] The permeability coefficient is a key factor influencing the magnitude and state of change in the slope stability coefficient. Under the same rainfall intensity, slopes with different permeability coefficients show significant differences in the magnitude of the decrease in the stability coefficient. During sustained rainfall, changes in the permeability of the overburden layer have a significant impact on slope stability. At the same rainfall intensity, the greater the permeability coefficient of the overburden soil, the greater the decrease in the slope safety factor and the more pronounced the impact on slope stability. This is because slope stability is primarily related to the soil's deadweight, cohesion, and internal friction angle, and is unrelated to the permeability coefficient. Under sustained rainfall, the greater the permeability coefficient of the overburden soil, the greater the slope's infiltration capacity, the faster the rate of rainwater infiltration, the greater the amount of rainwater infiltrated, the faster the rate of increase in the overburden soil's volumetric moisture content, the greater the decrease in matrix suction, and the more pronounced the decrease in the slope's shear strength, ultimately leading to a significant decrease in slope stability.

[0134] Based on the slope model with a slope gradient of 25°, a cover layer thickness of 3m, and a cut slope, the change in the slope stability coefficient for different permeability coefficient k values is calculated, such as Figure 40 As shown in the figure. The calculation results show that the change of permeability coefficient will not cause the change of the initial stability coefficient of the slope, but it will cause the change process of the slope stability coefficient under rainfall conditions to change. That is, the initial stability coefficient of the slope is equal under different permeability coefficients, but the reduction of the stability coefficient is different. Specifically, when the permeability coefficient value is large (k=1*10 -5 m / s), the slope stability coefficient decreases the most, and the slope can reach saturation within 1 hour of rainfall, and the stability coefficient decreases to the minimum value; when the permeability coefficient value is large (k=5*10 -6 m / s), the slope is not completely saturated, but the stability coefficient is greatly reduced; when the permeability coefficient is small (k≤1*10 -6 m / s), the slope's response to rainfall is far less sensitive than when the permeability coefficient is large, and the reduction in the stability coefficient is limited. This shows that changes in the permeability coefficient play a controlling role in the state and magnitude of changes in the slope's stability coefficient under rainfall conditions.

[0135] Fitting the slope stability coefficient reduction curve under different permeability coefficients under rainfall conditions, such as Figure 41 As shown. From the curve, we can see that when k=1*10 -5 m / s(0.864m / d) to k=1*10 -7 When the permeability coefficient increases within the range of m / s (0.00864m / d), the stability coefficient decreases due to the increase in the permeability coefficient. The R 2 =0.9987, the curve fit is good, and the curve has a strong ability to explain the law of change. -6m / s (0.432m / d), after 1 hour of rainfall, the slope stability coefficient drops below 1.0, and the slope is in an unstable state. -6 m / s is the benchmark, when the k value increases to the first permeability coefficient k1 and above, k1=1*10 -5 m / s, the slope stability coefficient faces the risk of being greatly reduced. At this time, the critical rainfall threshold corresponding to the slope is smaller, and the lower threshold is taken. When the k value decreases to the second permeability coefficient k2 or below, k2=1*10 -6 m / s, the slope stability coefficient decreases to a limited extent, and the slope stability safety margin is large. At this time, the critical rainfall threshold corresponding to the slope is larger, and the upper threshold is taken.

[0136] According to the influence of slope cutting, determine the threshold adjustment change ΔR caused by slope cutting. slope :

[0137] Slope cutting, or excavation, is a load-removing process. Slope cutting alters the slope's geological environment, including its geometry, vegetation cover, hydrological conditions, and stratum exposure. When slope cutting increases its steepness, it worsens the slope's geological environment. Essentially, the mechanism by which slope cutting and excavation induce landslides is that excavation alters the initial boundary conditions of the slope, triggering a chain reaction of physical and mechanical effects within the slope's geotechnical medium. Numerous slope cutting projects have resulted from road construction, housing development, and other engineering activities in the study area. The impact of slope cutting on the slope was determined by calculating the change in initial stability coefficient for the same slope morphology, both in the cut and uncut states.

[0138] The initial stability coefficient of the slope model with a slope gradient of 20° and cover layer thicknesses of 2m, 3m, 4m, and 5m is calculated under two working conditions: with and without slope cutting. The slope gradient is 90° and the slope cutting depth is greater than the cover layer thickness. Figure 42 That is, the initial stability coefficient of slopes with different cover layer thicknesses when there is or is no cut slope. As can be seen from the figure, when the slope model is the same thickness, the slope cutting will cause a significant reduction in the initial stability of the slope. The main reason is that after the cut slope is unloaded, the stress distribution of the air-facing part changes, and small-scale slippage in the cover layer is prone to occur. The volume of the sliding body in this type of instability mode is small, but because the cut slope is generally close to disaster-bearing bodies such as houses and roads, instability can easily cause casualties and economic losses. Since the initial stability coefficient of the slope is larger when the slope is not cut, the safety margin is higher, so the rainfall threshold that induces slope instability is larger. At this time, the original benchmark threshold is floated to the upper limit value as the rainfall threshold when there is no cut slope. When there is a cut slope, ΔR slope 0; ΔR when there is no slope slope As the upper limit.

[0139] Determine the effective rainfall coefficient η according to the influence of vegetation type:

[0140] Different vegetation types, due to their varying structures, have varying capacities for intercepting rainfall. Plant canopy interception refers to the process by which some water is absorbed by surface plants and evaporates, preventing it from directly entering the soil. In actual rainfall, rainfall can be divided into intercepted and unintercepted rainfall. Intercepted rainfall is absorbed by leaves and tree trunks, while the remaining intercepted rainfall remains on the surface of leaves and trunks, evaporating or disappearing over time. Unintercepted rainfall falls onto the soil surface, forming surface runoff or recharging groundwater through soil infiltration. Surface runoff, through scouring the surface soil, can cause geological hazards such as landslides. Groundwater recharge, when rainwater infiltrates into the soil, increases pore water pressure, reducing soil shear strength, leading to geological hazards such as slope instability. Therefore, during short, intense rainfall events, rainfall not intercepted by the canopy is the only one that effectively recharges groundwater, reducing soil shear strength through infiltration.

[0141] The effective rainfall coefficient is the ratio of the amount of rainfall that penetrates without being intercepted by the tree canopy to the actual rainfall value. The formula is as follows: η = O / P; where η is the effective rainfall coefficient; P is the rainfall (mm), i.e., the rainfall measured in the deserted area; O is the amount of rainfall that penetrates without being intercepted by the tree canopy (mm). The effective rainfall coefficients of common vegetation in the study area are shown in Table 2.

[0142] Table 2 Common vegetation and their reference values of effective rainfall coefficient

[0143]

[0144]

[0145] Example The vegetation type in the study area is mainly bamboo, so the effective rainfall coefficient is 0.93.

[0146] Determination of meteorological risk warning threshold system for rainfall-induced landslides

[0147] Finally, according to the changes in the geological environmental factors of each slope and the threshold adjustment plan, the meteorological risk rainfall warning thresholds of each slope geological environmental factor are formed, and a rainfall-type landslide meteorological risk warning threshold system based on the slope geological environment is realized from the regional to the slope scale.

[0148] Example The study area is divided into rainfall thresholds of different durations of 1 / 3 / 6 / 12 / 24h under the three indicators of slope gradient, cover thickness and internal friction angle. The rainfall threshold will be adjusted with the change of the geological environmental factors of a certain slope. The adjustment rule is determined by the inherent law of the effect of each indicator on the slope. The expression of the threshold adjustment variation specifically reflects the adjustment rules of different indicators for rainfall thresholds of different durations. Under the indicators of cohesion c and permeability coefficient k, the thresholds of different durations are adjusted to different values in a gradient. The slope is adjusted according to whether there is a cut slope. When there is a cut slope, refer to the adjustment results of other indicators. When there is no cut slope, the threshold is adjusted to the upper limit value. The vegetation coverage is adjusted according to the vegetation type and the rainfall coefficient. The specific threshold adjustment model is as follows:

[0149]

[0150] Where, ΔR α , ΔR d , ΔR φ , ΔR c , ΔR k , ΔR slope They are the adjustment changes of the refinement threshold due to slope gradient, cover layer thickness, internal friction angle, cohesion, permeability coefficient and slope cutting conditions. The specific calculation methods and values are shown in Table 3.

[0151] Table 3 Example Study Area "One Area One Threshold" Adjustment Plan

[0152]

[0153]

[0154] The process of establishing the rainfall threshold adjustment rules embodies the three principles of "comprehensiveness", "limitedness" and "dynamicity". These three principles ensure the scientific nature and operability of the "one area, one threshold" results.

[0155] Comprehensiveness means that the threshold is the result of considering the combined effect of multiple indicators. The main factors that may affect the change of the threshold, such as the slope itself and external conditions, are comprehensively considered. The threshold result generally reflects the effect of real indicators on the change of the threshold.

[0156] Finiteness means that the threshold adjustment is within a range limit, and the threshold result is within a reasonable and controllable range. Considering the actual laws of the effects of various indicators on slope stability and the feasibility of actual operations, the threshold adjustment result in this embodiment is within a range of 20% above and below the baseline threshold.

[0157] Dynamicity means that the rainfall thresholds established based on historical disaster and rainfall data are updateable. The main problem with thresholds is the subjectivity of analyzing and estimating rainfall events during the establishment process. A large number of studies have discussed statistical means and methods for establishing thresholds, with the aim of reducing subjectivity. However, there is an easily overlooked problem in the application of rainfall thresholds, namely that thresholds are time-sensitive. As time changes, the various factors used to establish thresholds and those related to them, such as the number of landslides, land use conditions, and rainfall monitoring networks, are constantly updated. This requires that thresholds must also keep pace with the times and be updated. In Pingyang County, the refined thresholds established through this plan refer to the threshold adjustment plan when the geological environment conditions of the slope change, which not only achieves refined threshold assignment but also dynamic adjustment of the threshold.

[0158] In this document, directional terms such as front, back, top, and bottom are defined based on the positions of components in the accompanying drawings and relative to each other, and are intended for clarity and convenience in describing the technical solution. It should be understood that these terms are relative and may vary depending on usage and placement. The use of these directional terms should not limit the scope of protection claimed in this application.

[0159] In the absence of conflict, the above embodiments and features in the embodiments may be combined with each other.

[0160] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment, characterized in that: The following steps are involved: S1. Construct a rainfall-induced landslide meteorological risk warning threshold model based on the slope geological environment as follows: Among them, R is the meteorological risk warning threshold for slope geological disasters, R S is the regional slope reference threshold, ΔR i It represents the threshold adjustment change brought about by various geological environmental factors; η is the effective rainfall coefficient, n is the number of geological environmental factors; S2. Use the rainfall threshold model to analyze the rainfall threshold that induces landslide disasters, and thus determine the regional slope benchmark threshold R S ; S3. Select the controlling slope geological environmental factors within the region based on the mechanism of slope deformation and failure. All slope geological environmental factors are divided into three categories: slope spatial structure, slope material composition, and hydrological conditions. The slope spatial structure includes slope gradient α, thickness of loose rock and soil d, and whether the slope is cut; the slope material composition includes rock and soil cohesion c, internal friction angle φ, and permeability coefficient k; and the hydrological conditions include vegetation type. S4. Describe the overall regional benchmark slope based on the selected slope geological environment factors; S5. Use numerical simulation to determine the slope stability change caused by each slope geological environment factor of the benchmark slope under different rainfall conditions, and obtain the threshold adjustment change ΔR caused by each slope geological environment factor at different durations. i , thus establishing a rainfall-induced landslide meteorological risk warning threshold system based on the slope geological environment from regional to slope scales, where the threshold adjustment change ΔR brought by each slope geological environment factor is i The method of determining is: Determine the upper and lower limits of the threshold adjustment changes brought about by each geological environmental factor; Threshold adjustment change ΔR caused by ramp gradient α =m α α+n α , where m α 、n α is the coefficient; Threshold adjustment change ΔR caused by cover layer thickness d =m d d+n d , where m d 、n d is the coefficient; Threshold adjustment change ΔR caused by internal friction angle φ =m φ φ+n φ , where m φ 、n φ is the coefficient; Threshold adjustment change ΔR caused by cohesion c : The cohesion c0 when the threshold adjustment change caused by the cohesion c is 0 is used as the baseline cohesion. When the cohesion c increases by Δc relative to the baseline cohesion c0, ΔR c Adjust to the upper limit, and adjust the middle linear interpolation; when the cohesion c decreases by Δc relative to the reference cohesion c0, ΔR c Adjust to the lower limit, and adjust by linear interpolation in the middle; Threshold adjustment change ΔR caused by permeability coefficient k : Taking the cohesion k0 when the threshold adjustment change brought by the permeability coefficient k is 0 as the permeability coefficient, when the k value increases to the first permeability coefficient k1 and above, ΔR k Take the lower limit; when the k value decreases to the second permeability coefficient k2 and below, ΔR k Take the upper limit; Threshold adjustment change ΔR caused by slope cutting slope : When there is a cut slope, ΔR slope 0; ΔR when there is no slope slope As the upper limit.

2. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment according to claim 1, characterized in that: In step S4, when the slope geological environment factor is a continuous factor, the average value is used to characterize the benchmark slope; when the slope geological environment factor is a discrete factor, the mode is used to characterize the benchmark slope.

3. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment according to claim 1, characterized in that: The upper and lower limits of the threshold adjustment changes brought about by each geological environmental factor are ±20% of the regional slope benchmark threshold.

4. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment according to claim 1, characterized in that: In step S5, the threshold adjustment change ΔR caused by each slope geological environment factor for 1 / 3 / 6 / 12 / 24 hours is obtained. i .

5. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment according to claim 1, characterized in that: The calculation formula of effective rainfall coefficient η is as follows: η=O / P Where: P is the rainfall; O is the rainfall that is not intercepted by the canopy and penetrates.

6. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment according to claim 1, characterized in that: In step S2, the ID rainfall threshold model is used to analyze the rainfall threshold that induces landslide disasters. The threshold model is expressed in power exponential form as follows: I=a+γD β Where: I is the cumulative rainfall; D is the rainfall duration; γ, β, and a are statistical parameters, and a ≥ 0.

7. The method for establishing a rainfall-induced landslide risk warning threshold system based on geological environment according to claim 1, characterized in that: In step S3, the selection of the slope geological environment factor is determined by the principle of geological environment factor validity and the principle of geological environment factor parameter availability.

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