A rainfall early warning method

Abstract

The present invention provides a rainfall warning method, including: determining the area type of the target road, the area types include areas with insufficient historical rainfall data and areas with abundant historical rainfall data; for areas with insufficient historical rainfall data, obtaining environmental parameters of slope collapse risk points with limited historical rainfall data, and calculating and determining target data; for areas with abundant historical rainfall data, determining target data based on statistics of historical rainfall data; and establishing a rainfall warning surface in a three-dimensional rainfall warning space based on cumulative rainfall, maximum rainfall at the hour, and rainfall duration, based on the target data. Based on the technical solution of the present invention, targeted methods are proposed for areas with different historical rainfall data; especially for areas with insufficient historical rainfall data, full consideration is given to conditions such as previous rainfall characteristics, slope soil properties, and slope surface morphology, providing a method and reference for establishing an effective rainfall warning system along the area.

Description

Technical Field

[0001] The present invention relates to the technical field of rainfall early warning, and in particular to a rainfall early warning method. Background Art

[0002] Rainfall infiltration is the primary factor triggering shallow landslides on roadbed slopes. This is essentially due to the long-term effects of rain, wind, and climatic fluctuations on the shallow slope soil, which is subject to a perennial dry-wet cycle. This causes the soil density to decrease year by year, leading to severe deterioration of the roadbed slope. After saturation with rainwater, the shallow soil softens and its matrix suction is significantly reduced. Statistics show that 80% of railway flooding incidents are caused by rainfall on the slopes of older, existing earthen embankments or cuttings. In practice, slope landslides are defined as the collapse of soil or rock slopes with an indeterminate sliding surface and a sliding depth ranging from 0.5 to 4 meters. Shallow slope landslides are a common type of flooding.

[0003] For a long time, the problem of shallow collapse of railway embankment slopes has been a common but insufficiently studied topic in my country's railway operation and maintenance work. This type of disease is common on existing lines in mountainous areas.

[0004] To prevent shallow railway landslides or rainfall-induced landslides from harming human life and property, railway authorities employ a method for managing rainfall early warnings using rainfall warning values. The "Railway Flood Control Management Measures" stipulate that railway flood control management should be based on two rainfall warning indicators: hourly rainfall or continuous rainfall combined with hourly rainfall. However, this method is developed based on experience by local engineering departments, with a single threshold indicator. It does not comprehensively consider the different rainfall characteristics of shallow railway landslides, resulting in a low success rate for early warnings. In summary, scientifically establishing rainfall warning indicators and methods has significant economic and social significance.

[0005] At present, many scholars at home and abroad have carried out extensive research on rainfall warning values. However, existing studies mainly focus on studying rainfall warning values ​​with single or two warning indicators. The selection of threshold indicators is relatively simple, which has limitations in describing slope collapse or shallow landslides caused by different rainfall types. In addition, there is little discussion on the relationship between rainfall warning values ​​and previous rainfall characteristics and slope soil properties.

[0006] Therefore, a new rainfall warning method is proposed here, which fully considers the previous rainfall characteristics and slope soil properties to improve the accuracy of rainfall warning and provide more scientific guidance for the formulation of a more complete line water disaster warning plan. Summary of the Invention

[0007] In response to the above-mentioned problems in the prior art, the present application proposes a rainfall early warning method.

[0008] The present invention provides a rainfall early warning method, comprising the following steps:

[0009] Determine the region type of the target road area, where the region type includes regions with scarce historical rainfall data and regions with abundant historical rainfall data;

[0010] According to the type of region, for areas with insufficient historical rainfall data, the environmental parameters of the slope collapse risk point of the target road are obtained using limited historical rainfall data, and the target data is calculated and determined; for areas with abundant historical rainfall data, the target data is determined based on the statistics of the historical rainfall data;

[0011] According to the target data, a rainfall warning surface is established in a three-dimensional rainfall warning space established based on the accumulated rainfall, the hourly maximum rainfall and the rainfall duration.

[0012] In one embodiment, the cumulative rainfall is the rainfall in a preset time period before the slope is damaged, the maximum rainfall is the hourly maximum rainfall intensity on the day the slope is damaged, and the rainfall duration is the duration of a rainfall that causes the slope to be damaged.

[0013] In one embodiment, the calculating and determining target data includes:

[0014] For areas where historical rainfall data are scarce, a slope generalization model is established based on the environmental parameters and limited historical rainfall data to determine the target factors that have a decisive impact on slope stability;

[0015] Taking the target factor as a control variable, determining the slope stability safety factor under different rainfall conditions, wherein the rainfall conditions include cumulative rainfall and hourly maximum rainfall;

[0016] Recording the rainfall duration corresponding to the target value of the slope stability safety factor and using it as the critical rainfall duration;

[0017] The critical rainfall duration corresponding to the different cumulative rainfall amounts and the maximum rainfall amount at that time is recorded and used as the target data.

[0018] In one embodiment, the slope stability safety factor is calculated using the limit equilibrium method or the strength reduction method. S =1.2 when the corresponding rainfall duration is taken as the critical rainfall duration.

[0019] In one embodiment, determining target data based on historical rainfall data statistics includes:

[0020] Determine the effective rainfall at the time of slope failure based on the historical rainfall data, and use it as the cumulative rainfall;

[0021] The effective rainfall, the maximum rainfall and the rainfall duration at the time of slope failure are recorded and used as the target data.

[0022] In one embodiment, the effective rainfall is determined by:

[0023] R c =R0+αR1+α 2 R2+…+α n R n

[0024] Among them, R c is the effective rainfall, R0 is the rainfall on the day, R n is the rainfall n days ago, α is the effective rainfall coefficient, and n is the number of rainy days.

[0025] In one embodiment, before determining the effective rainfall at the time of slope failure based on the historical rainfall data, the method further includes:

[0026] According to the evaluation indicators of the slopes along the target road, the rainfall warning areas along the target road are divided, wherein the evaluation indicators include slope lithology, slope morphology, slope soil properties, rainfall characteristics and slope vegetation conditions.

[0027] In one embodiment, establishing a rainfall warning surface in a three-dimensional rainfall warning space based on the target data includes:

[0028] Determining a plurality of target coordinate points in the three-dimensional rainfall warning space according to the target data;

[0029] The rainfall warning surface is fitted in the three-dimensional rainfall warning space according to the multiple target coordinate points.

[0030] In one embodiment, the environmental parameters include the slope height, slope shape, vegetation coverage, distance from the road and slope accumulation layer thickness, slope gradient, slope direction, groundwater seepage conditions and soil parameters of the slope collapse risk point, and the soil parameters include soil shear strength, soil permeability coefficient and soil matrix suction.

[0031] In one embodiment, the limited historical rainfall information includes historical average annual rainfall data.

[0032] The above technical features can be combined in various suitable ways or replaced by equivalent technical features, as long as the purpose of the present invention can be achieved.

[0033] The rainfall early warning method provided by the present invention has at least the following beneficial effects compared with the prior art:

[0034] A rainfall warning method of the present invention proposes two corresponding methods for establishing a rainfall warning surface based on the historical rainfall data of different regions. Especially for areas with a lack of historical rainfall data, the method of the present invention fully considers the establishment of a rainfall warning surface under changing conditions such as previous rainfall characteristics, slope soil properties, and slope surface morphology, providing a method and reference for establishing a scientific and effective rainfall warning system along areas with a lack of historical rainfall data. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be described in more detail below based on embodiments and with reference to the accompanying drawings, wherein:

[0036] Figure 1 A schematic diagram showing the main process of the method of the present invention;

[0037] Figure 2 A schematic diagram showing the complete process of the method of the present invention;

[0038] Figure 3 A schematic diagram showing the rainfall warning surface determined using average annual rainfall as the control variable;

[0039] Figure 4 A schematic diagram showing the rainfall warning surface determined using shear strength as the control variable;

[0040] Figure 5 A schematic diagram showing the rainfall warning surface determined using the permeability coefficient as the control variable;

[0041] Figure 6 A schematic diagram showing the rainfall warning surface determined using slope gradient as the control variable.

[0042] In the drawings, like reference numerals are used for like parts, but the drawings are not necessarily true to scale. DETAILED DESCRIPTION

[0043] The present invention will be further described below with reference to the accompanying drawings.

[0044] At present, many scholars at home and abroad have conducted extensive research on rainfall warning values, including but not limited to the following:

[0045] Brand and Au believed that most landslides in Hong Kong, China were caused by short-term high-intensity rainfall, with a critical rainfall intensity of 70 mm / h.

[0046] Sugiyama believed that railway slope landslides in Japan can be divided into shallow and deep landslides, and established the statistical method Rm r n As critical rainfall parameters, where R is the cumulative rainfall, r is the hourly rainfall, m and n are parameters and it is concluded that for shallow landslides in the study area, m = 0.2, n = 0.9, and for deep landslides, m = 0.4, n = 0.2;

[0047] Liuyuan conducted research on critical rainfall intensities in several key rainstorm landslide hotspots across China: The Sichuan Basin has a critical rainfall intensity of 200 mm / day, and the cumulative rainfall in this region has no significant impact on landslides; in southern Shaanxi, concentrated shallow landslides occur when the rainfall exceeds 70 mm / day, and there is a very clear positive correlation between cumulative rainfall and landslides; in western Hubei, with the Yangtze River as the boundary, annual rainfall tends to be higher in the south and lower in the north, and the critical rainfall intensity is roughly around 100 mm / day;

[0048] Liu Chuanzheng divided the regional early warning methods for geological disasters into three types: implicit statistical early warning, explicit statistical early warning, and dynamic early warning, and proposed a new development direction for regional early warning of geological disasters.

[0049] Based on data from 246 landslides in Zhejiang Province, Zhang Guirong used an effective rainfall model to perform statistical calculations and analysis on rainfall data, and obtained the critical rainfall values ​​for landslide hazards in areas affected by typhoons and plum rains.

[0050] Wen Mingsheng statistically analyzed the correlation between geological hazards in the Ailao Mountain area and previous cumulative rainfall, daily induced rainfall, and slope gradient, and established a multi-index early warning model.

[0051] Jian Wenbin assumed that the initial moisture content of the soil was linearly distributed along the depth of the slope soil, and deduced the maximum infiltration depth of the soil from the relationship between saturation and moisture content, and then obtained the theoretical effective rainfall value of the slope soil;

[0052] Zhan Liangtong used numerical simulation methods to calculate and analyze the influence of factors such as initial wetting conditions, soil shear strength, saturated permeability coefficient, slope gradient, slope residual soil thickness, and rainfall type on the ID curve, laying the foundation for theoretical calculation of feasible rainfall warning values.

[0053] Existing studies, including the above studies, basically focus on studying rainfall warning values ​​with a single or two warning indicators. The threshold indicator is single, which has limitations in describing slope collapse or shallow landslides caused by different rainfall types. There is also little discussion of the relationship between rainfall warning values ​​and previous rainfall characteristics and slope soil properties.

[0054] Example 1

[0055] This embodiment mainly describes the application of the rainfall early warning method of the present invention in areas where historical rainfall data is scarce. The embodiment of the present invention provides a rainfall early warning method, comprising the following steps:

[0056] Step S100: determining the region type of the target traffic route, where the region type includes regions with scarce historical rainfall data and regions with abundant historical rainfall data;

[0057] Step S200: Based on the region type, for regions with insufficient historical rainfall data, obtain environmental parameters of the slope collapse risk points of the target traffic route using limited historical rainfall data, and calculate and determine target data;

[0058] Environmental parameters include the slope height, slope shape, vegetation coverage, distance from the line, slope accumulation layer thickness, slope gradient, slope direction, groundwater seepage conditions and soil parameters of the slope collapse risk point. Soil parameters include soil shear strength, soil permeability and soil matrix suction. Limited historical rainfall data include historical annual average rainfall data.

[0059] Specifically, in areas where historical rainfall data is scarce, slope stability analysis during rainfall can only be conducted based on the slope's environmental parameters. Whether or not a slope will collapse depends on these parameters. By determining the slope's environmental parameters and valid historical rainfall data, it's possible to determine the critical rainfall condition above which a slope is susceptible to collapse. This critical rainfall condition can then serve as the target data.

[0060] A survey was conducted on the slopes along the line, focusing on the statistics of factors such as slope height, slope shape, vegetation coverage, distance from the line, slope accumulation layer thickness, slope gradient, slope direction, groundwater seepage conditions, etc., which are prone to shallow landslides or slope collapse risks. This provided support for the establishment of a generalized slope numerical model, and the mean, standard deviation, coefficient of variation and other parameters of the above factors were counted.

[0061] Conduct relevant soil property tests on-site to determine soil parameters at risk points for shallow landslides or slope collapse. Field soil property tests include determining soil density using water or sand injection methods, determining shear strength using on-site shear tests or cross-plate shear tests, determining soil permeability using test pit penetration tests, and determining soil matrix suction using tensiometers or electrical / thermal conductivity sensors. Indoor soil property tests include determining the liquid and plastic limits of soil using a combined liquid and plastic limit measuring instrument, and plotting soil gradation curves using particle analysis tests. Statistical analysis is performed on parameters such as the mean, standard deviation, and coefficient of variation of shear strength.

[0062] For areas with limited historical rainfall data, such as historical average annual rainfall, a statistical analysis of meteorological data collected over a large area is conducted to determine the historical average annual rainfall and its distribution. Statistical indicators should include parameters such as mean, standard deviation, and coefficient of variation.

[0063] Step S210: For areas with insufficient historical rainfall data, a slope generalization model is established based on environmental parameters and limited historical rainfall data to determine target factors that have a decisive impact on slope stability;

[0064] Specifically, slope environmental parameters are composed of multiple parameters, of which only certain ones may have a significant impact on slope stability. The types of parameters that have a significant impact on slope stability may also vary across regions. Therefore, we first establish a generalized slope model to identify the key factors that have a decisive impact on slope stability within the environmental parameters.

[0065] Step S220: using the target factor as a control variable, determining the slope stability safety factor under different rainfall conditions, where the rainfall conditions include the cumulative rainfall and the maximum rainfall at that time;

[0066] Specifically, after determining the target factors that have a decisive influence on slope stability, the target factors are used as control variables to simulate slopes in different regions and environments. After determining the values ​​of the control variables, different rainfall conditions are simulated by changing the cumulative rainfall and the maximum rainfall at the time, and the corresponding slope stability safety factor (F S ). That is, after the type and value of the target factor are determined, the slope stability safety factor is different under different rainfall conditions. Generally speaking, the slope stability safety factor F S =1 is the critical point of slope stability, F S When it is less than 1, it indicates that the slope has been damaged.

[0067] Step S230: Record the rainfall duration corresponding to the target value of the slope stability safety factor and use it as the critical rainfall duration; calculate the slope stability safety factor using the limit equilibrium method or strength reduction method, and use the slope stability safety factor F S =1.2 when the corresponding rainfall duration is taken as the critical rainfall duration;

[0068] Specifically, after the control variables (target factors) and rainfall conditions are determined, the slope stability safety factor is negatively correlated with the rainfall duration, that is, as the rainfall duration continues to increase, the slope stability safety factor continues to decrease. For safety reasons, the slope stability safety factor F S =1.2 is taken as the critical point of stability, and the corresponding rainfall duration at this time is the critical rainfall duration.

[0069] Step S240: Record different cumulative rainfall amounts and critical rainfall durations corresponding to the maximum rainfall amount at that time, and use them as target data.

[0070] Specifically, after determining the critical rainfall duration, the corresponding cumulative rainfall and the maximum rainfall at that time are recorded. The values ​​of these three indicators are used as target data. At the same time, the levels of the corresponding control variables (target factors) are also recorded.

[0071] Step S300: Based on the target data, a rainfall warning surface is established in the three-dimensional rainfall warning space established based on the cumulative rainfall, the hourly maximum rainfall and the rainfall duration; the cumulative rainfall is the rainfall in the preset time period before the slope is damaged, and the cumulative rainfall can be further reduced to a certain extent using the vegetation coverage obtained from the on-site investigation. The reduction method can be found in relevant technical literature; the hourly maximum rainfall is the hourly maximum rainfall intensity on the day the slope is damaged; the rainfall duration is the duration of a rainfall that causes the slope to be damaged.

[0072] Step S310: determining multiple target coordinate points in the three-dimensional rainfall warning space according to the target data;

[0073] Specifically, based on the cumulative rainfall, hourly maximum rainfall, and critical rainfall duration in the target data, multiple target coordinate points are determined in the three-dimensional rainfall warning space. The same three-dimensional rainfall warning space can have multiple target coordinate points. These target coordinate points are determined by varying the rainfall conditions of cumulative rainfall and hourly maximum rainfall under the same level of the control variable (target factor). Finally, a scatter plot is generated in the three-dimensional rainfall warning space.

[0074] Step S320: fitting a rainfall warning surface in the three-dimensional rainfall warning space according to the multiple target coordinate points.

[0075] Specifically, by fitting the scatter plot, we can derive the rainfall warning surface under the corresponding control variables (target factors). When the actual rainfall data (accumulated rainfall, hourly maximum rainfall, and rainfall duration) under the corresponding environmental conditions (target factors) approach the rainfall warning surface, a warning can be issued.

[0076] Example 2

[0077] This embodiment mainly describes the application of the rainfall early warning method of the present invention in areas with abundant historical rainfall data. Some of the same contents refer to Example 1 and are not repeated in this embodiment. The embodiment of the present invention provides a rainfall early warning method, comprising the following steps:

[0078] Step S000: Based on the evaluation indicators of the slopes along the target road, the target road is divided into rainfall warning zones. The evaluation indicators include slope lithology, slope morphology, slope soil properties, rainfall characteristics, and slope vegetation conditions. The route evaluation zones should not be too detailed to avoid difficulties in on-site management.

[0079] Step S100: determining the region type of the target traffic route, where the region type includes regions with scarce historical rainfall data and regions with abundant historical rainfall data;

[0080] Step S200: According to the region type, for regions with rich historical rainfall data, target data is determined based on the statistics of the historical rainfall data;

[0081] Specifically, for areas with rich historical rainfall data, the target data required for early warning can be directly obtained based on the rainfall data at the time of corresponding slope failure;

[0082] Step S210: Determine the effective rainfall at the time of slope failure based on historical rainfall data and use it as the cumulative rainfall. The effective rainfall is determined by the following power exponent method:

[0083] R c =R0+αR1+α 2 R2+…+α n R n

[0084] Among them, R c is the effective rainfall, R0 is the rainfall on the day, R n is the rainfall n days ago, α is the effective rainfall coefficient, and n is the number of rainy days;

[0085] Specifically, since a single rainfall does not necessarily lead to the occurrence of slope collapse, and only a portion of the rainfall in each rainfall penetrates into the slope soil to affect the occurrence of collapse, the cumulative rainfall obviously cannot be used as disaster-causing rainfall. Therefore, it is more reasonable to multiply the daily rainfall over a period of time by the effective rainfall coefficient to obtain the effective rainfall, and to conduct assessment and early warning based on the effective rainfall.

[0086] In the above power exponential formula, the rainfall on the day R0, the number of rainy days n, and the rainfall n days ago R n All of these can be directly obtained through statistical analysis of historical rainfall data. The only thing that needs to be determined is the effective rainfall coefficient α. Based on historical rainfall data, the effective rainfall model is used to statistically analyze the correlation between the number of slope failures and the effective rainfall coefficient α, and the optimal value of the effective rainfall coefficient α can be determined.

[0087] Step S220: Record the effective rainfall, maximum rainfall, and rainfall duration at the time of slope failure as target data;

[0088] Step S300: Based on the target data, a rainfall warning surface is established in a three-dimensional rainfall warning space established based on the cumulative rainfall, the hourly maximum rainfall and the rainfall duration; the cumulative rainfall is the rainfall in the preset time period before the slope is damaged, the hourly maximum rainfall is the hourly maximum rainfall intensity on the day the slope is damaged, and the rainfall duration is the duration of a rainfall that causes the slope to be damaged.

[0089] Step S310: determining multiple target coordinate points in the three-dimensional rainfall warning space according to the target data;

[0090] Step S320: fitting a rainfall warning surface in the three-dimensional rainfall warning space according to the multiple target coordinate points.

[0091] Example 3

[0092] This embodiment mainly describes the actual data calculation process of the rainfall early warning method of the present invention for areas with scarce historical rainfall data. Some of the same contents refer to the previous embodiment and are not repeated in this embodiment.

[0093] For areas with scarce historical rainfall data, the environmental parameters of the slope collapse risk points are first obtained, and then the analysis model is used to analyze the environmental parameters (target parameters) closely related to slope stability. The environmental parameters mainly include: density, porosity, saturation, cohesion, internal friction angle, permeability coefficient (related to the average annual rainfall), slope, rainfall intensity, rainfall duration and vegetation conditions.

[0094] In this example, the corresponding environmental parameters were first determined based on the collected data models. Correlation analysis (Pearson correlation) of the slope stability coefficient was performed, revealing that cohesion, slope, rainfall duration, and permeability coefficient had a high correlation with the stability coefficient. A multiple regression analysis method was then used to establish a multiple regression analysis model to further determine the relationship between the above parameters and the slope stability coefficient. Cohesion, slope, rainfall duration, and permeability coefficient were then input into the model as variables to derive a specific expression for the multiple regression analysis model.

[0095] After determining cohesion, slope, rainfall duration and permeability coefficient as target factors, cohesion, slope and permeability coefficient are used as control variables. After determining the values ​​of the control variables, the limit equilibrium method or strength reduction method is used to change the rainfall conditions of cumulative rainfall and maximum rainfall at the time, and the slope stability safety factor under different rainfall conditions is calculated, and the slope stability safety factor F is used as the control variable. S =1.2 is used as the critical rainfall duration. In this way, multiple data groups can be obtained. Each data group includes the critical rainfall duration and its corresponding cumulative rainfall and maximum rainfall. Multiple data groups constitute the target data.

[0096] The target data forms a scatter plot in the three-dimensional rainfall warning space, and the Poly2D function is used to make the rainfall warning surface of the scatter plot. The general expression of the Poly2D function is:

[0097] Z=Z0+ax+by+cx2+dy2+fxy

[0098] Attached photos Figures 3 to 6 The rainfall warning surface in the three-dimensional rainfall warning space obtained by using different parameters as control variables is shown.

[0099] Example 4

[0100] This embodiment mainly describes the determination of the effective rainfall coefficient α by the rainfall warning method of the present invention for areas with abundant historical rainfall data. For some of the same contents, please refer to the previous embodiment and will not be repeated in this embodiment.

[0101] First, according to the effective rainfall model, coefficients α = 0.9, 0.8, 0.7, 0.6, etc. were selected for calculation respectively. Based on historical rainfall data, the correlation between each coefficient value and the number of slope collapses was analyzed, and the coefficient value with the highest correlation was taken as the optimal value of the effective rainfall coefficient α.

[0102] Then, based on the value of the effective rainfall coefficient α and historical rainfall data, the effective rainfall is calculated using the following formula.

[0103] R c =R0+αR1+α 2 R2+…+α n R n

[0104] Finally, a scatter plot is formed in the three-dimensional rainfall warning space based on the effective rainfall (cumulative rainfall) at the time of slope failure, the maximum rainfall at the time, and the rainfall duration. Finally, a rainfall warning surface is fitted based on the scatter plot. Refer to the attached figure Figures 3 to 6 The form of the rainfall warning surface.

[0105] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be employed in conjunction with other described embodiments.

Claims

1. A rainfall early warning method, characterized in that: The following steps are involved: Determine the region type of the target transportation route, wherein the region type includes regions with scarce historical rainfall data and regions with abundant historical rainfall data; According to the regional type, for areas with insufficient historical rainfall data, the environmental parameters of the slope collapse risk points of the target traffic route are obtained with limited historical rainfall data, and the target data are calculated and determined; for areas with abundant historical rainfall data, the target data are determined based on the statistics of the historical rainfall data; Based on the target data, a rainfall warning surface is established in a three-dimensional rainfall warning space based on the cumulative rainfall, the hourly maximum rainfall, and the rainfall duration; the cumulative rainfall is the rainfall in a preset time period before the slope failure occurs; the hourly maximum rainfall is the hourly maximum rainfall intensity on the day the slope failure occurs; The rainfall duration is the duration of a rainfall that causes slope damage; The calculation to determine the target data includes: For areas where historical rainfall data are scarce, a slope generalization model is established based on the environmental parameters and limited historical rainfall data to determine the target factors that have a decisive impact on slope stability; Taking the target factor as a control variable, determining the slope stability safety factor under different rainfall conditions, wherein the rainfall conditions include cumulative rainfall and hourly maximum rainfall; Recording the rainfall duration corresponding to the target value of the slope stability safety factor and using it as the critical rainfall duration; The different accumulated rainfall amounts, the maximum rainfall amounts at the time and the corresponding critical rainfall durations are recorded and used as the target data.

2. The rainfall early warning method according to claim 1, characterized in that: The slope stability safety factor is calculated using the limit equilibrium method or the strength reduction method. S =1.2 when the corresponding rainfall duration is taken as the critical rainfall duration.

3. The rainfall early warning method according to claim 1, characterized in that: The target data is determined based on the statistics of historical rainfall data, including: Determine the effective rainfall at the time of slope failure based on the historical rainfall data, and use it as the cumulative rainfall; The effective rainfall, the maximum rainfall and the rainfall duration at the time of slope failure are recorded and used as the target data.

4. The rainfall early warning method according to claim 3, characterized in that: The effective rainfall is determined in the following way: in, is the effective rainfall, The rainfall for the day, is the rainfall n days ago, Effective rainfall coefficient, n is the number of rainy days.

5. The rainfall early warning method according to claim 3, characterized in that: According to the historical rainfall data, before determining the effective rainfall at the time of slope failure, the following should be included: According to the evaluation indicators of the slopes along the target traffic route, the rainfall warning areas along the target traffic route are divided, wherein the evaluation indicators include slope lithology, slope morphology, slope soil properties, rainfall characteristics and slope vegetation conditions.

6. The rainfall early warning method according to any one of claims 1 to 5, characterized in that: The step of establishing a rainfall warning surface in a three-dimensional rainfall warning space based on the target data includes: Determining a plurality of target coordinate points in the three-dimensional rainfall warning space according to the target data; The rainfall warning surface is fitted in the three-dimensional rainfall warning space according to the multiple target coordinate points.

7. The rainfall early warning method according to any one of claims 1 to 5, characterized in that: The environmental parameters include the slope height, slope shape, vegetation coverage, distance from the line and slope accumulation layer thickness, slope gradient, slope direction, groundwater seepage conditions and soil parameters of the slope collapse risk point. The soil parameters include soil shear strength, soil permeability coefficient and soil matrix suction.

8. The rainfall early warning method according to any one of claims 1 to 5, characterized in that: The limited historical rainfall information mentioned includes historical annual average rainfall data.

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