CN116486584A - Rainfall type shallow landslide early warning method based on probability analysis - Google Patents
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Abstract
The invention relates to a rainfall type shallow landslide early warning method based on probability analysis, which constructs a rainfall I-D threshold curve of a rainfall type shallow landslide based on probability analysis, and realizes early warning of the rainfall type shallow landslide by using the rainfall I-D threshold curve. According to the invention, historical rainfall data statistics is not completely relied on, and the influence of a catastrophe mechanism, a hydrologic effect and geological environment conditions of a slope under the action of rainfall is considered, so that accurate early warning of different areas is realized; the method can realize the fine early warning of a small-scale area or the degree of 'one slope one threshold', and the rainfall threshold is relatively accurate and has low false alarm rate; the dynamic early warning under the I-D rainfall threshold curve is realized, the landslide hazard degree can be effectively reflected by feeding back the landslide hazard degree according to the magnitude of the landslide occurrence probability based on the dynamic and quantitative updating of the landslide hazard degree according to the real-time rainfall data, and the landslide hazard degree is reflected to the early warning level.
Description
Technical Field
The present invention relates to computing; the technical field of calculation or counting, in particular to a rainfall type shallow landslide early warning method based on probability analysis in the technical field of landslide hazard prevention.
Background
Landslide refers to the natural phenomenon that soil or rock mass on a slope slides downwards along a certain weak surface or a weak belt integrally or dispersedly under the action of gravity after being influenced by river scouring, groundwater movement, rainwater soaking, earthquake, manual slope cutting and other factors. The landslide body can be divided into shallow landslide, middle landslide, deep landslide and ultra-deep landslide according to the thickness of the landslide body, wherein, shallow landslide refers to the landslide of the rock and soil body on the surface. The strong rainfall is the leading cause of damage to shallow layer accumulation landslide, the shallow layer accumulation landslide is composed of specific substances, the structural characteristics and thickness conditions determine the special rainfall affinity, and the rainfall infiltration process, the underlying bedrock confluence condition and the hydraulic influence degree determined by the characteristic conditions cause the special sensitivity of the landslide to rainfall.
The rainfall-induced shallow landslide has the characteristics of burst, mass-emission, difficult early warning and prevention and the like, rainfall is closely related to the triggering of the shallow landslide, and in order to achieve the purposes of early warning and forecasting of the rainfall-induced shallow landslide and disaster prevention and reduction, students often adopt rainfall parameters as indicators of landslide disaster early warning and release, and the aim of early warning the rainfall-induced shallow landslide is achieved by means of real-time rainfall monitoring data. The currently adopted I-D threshold curve takes average rainfall intensity (I) as an ordinate and rainfall duration (D) as an abscissa, landslide events caused by rainfall in a certain area history record are collected and counted, corresponding I value and D value combinations in rainfall data are obtained, and a lower envelope curve of the points is drawn to serve as a landslide rainfall I-D threshold curve of the area. The method is a traditional I-D rainfall threshold curve construction method, and when a rainfall event is above the I-D threshold curve, landslide early warning information is sent out, so that the method is a main early warning method adopted by the rainfall landslide at present.
The conventional I-D rainfall threshold curve described above has mainly the following problems:
1. the traditional rainfall threshold curve is completely obtained by statistics of historical rainfall data, is an experience-based statistical method, and is difficult to realize accurate early warning of different areas because the influence of disaster mechanism, hydrologic effect and geological environment conditions of a slope under the rainfall effect is not considered;
2. the historical rainfall data according to the traditional threshold curve is generally derived from rainfall monitoring data of provincial scale, is an average value of the whole area, has the problems of low rainfall threshold value, false alarm rate and high false alarm rate, and cannot realize fine early warning of small-scale area or 'one slope one threshold value' degree;
3. the existing I-D rainfall threshold curve is a static early warning method, and the dangerous degree of landslide disasters cannot be dynamically and quantitatively updated according to real-time rainfall data; the combination of rainfall intensity and rainfall duration is positioned above the threshold curve to represent potential landslide risk, but the traditional I-D rainfall threshold curve cannot reflect the landslide occurrence probability, and cannot quantitatively reflect the landslide risk degree and reflect the landslide risk degree to the early warning level.
Disclosure of Invention
The invention solves the problems existing in the prior art, and provides a rainfall shallow landslide early warning method based on probability analysis, in particular to a method for implementing rainfall-induced shallow landslide early warning by constructing a rainfall intensity-rainfall duration threshold curve (I-D threshold curve) according to probability analysis results based on landslide probability analysis of a physical process model.
The technical scheme adopted by the invention is that a rainfall type shallow landslide early warning method based on probability analysis is used for constructing a rainfall I-D threshold curve of a rainfall type shallow landslide based on probability analysis, and the rainfall type shallow landslide early warning is realized by the rainfall I-D threshold curve.
Preferably, the method comprises the steps of:
step 1: acquiring landslide research area data, and determining soil parameters required for infiltration analysis and limit balance analysis according to conventional methods such as post-disaster field investigation, indoor test, computer simulation inversion and the like; determining probability distribution characteristics of the soil parameters, wherein the probability distribution characteristics are described by statistics including but not limited to probability distribution types, mean values, standard deviation, coefficient of variation and the like;
step 2: constructing a deterministic slope stability evaluation model;
step 3: constructing a slope stability probability evaluation model on the basis of the probability distribution characteristics of the soil parameters in the step 1 and the model in the step 2, and obtaining the slope instability probability in the rainfall process;
step 4: acquiring historical rainfall data, constructing a rainfall data set with rainfall characteristics of the landslide research area, inputting the rainfall data set into a slope stability probability evaluation model, making early warning of different grades according to probability, and constructing a rainfall I-D threshold curve of early warning of each grade;
step 5: and on the basis of the obtained rainfall I-D threshold curves with different early warning grades, combining real-time rainfall monitoring data, and dynamically early warning landslide.
Preferably, in step 1, the landslide study area data includes rainfall data including: rainfall duration, real-time rainfall intensity, accumulated rainfall and the like are obtained by a rainfall monitoring station near a landslide disaster point.
Preferably, the step 2 includes the steps of:
step 2.1: simulating a rainfall infiltration process according to the real-time rainfall intensity, and simulating a rainfall infiltration physical process by combining an unsaturated soil infiltration model to obtain the depth z of a slope wetting front in the real-time rainfall process w ；
Step 2.2: determining key parameters for calculating a slope stability safety coefficient, wherein the key parameters comprise soil body weight, effective cohesive force, effective internal friction angle, saturation permeability coefficient, matrix suction force, saturation volume water content and initial volume water content;
step 2.3: depth z of wetting front using step 2.1 w And (3) carrying out slope stability analysis by combining an unsaturated soil mechanical limit balance method to obtain a slope safety coefficient in the continuous rainfall process.
Preferably, in the step 2.1, the unsaturated soil rainfall infiltration model is that the rainfall direction is vertical to the horizontal plane, the intensity is q, the unit of q is m/s, the slope angle is alpha, the unit of alpha is degrees, and the unsaturated soil rainfall infiltration model is determined according to a conventional method; only rainfall in the normal direction of the slope surface infiltrates into the soil body, and the rainfall downward along the slope surface flows along the slope surface, so that the effective rainfall intensity is q cos alpha; in the rainfall infiltration process, the slope body is gradually saturated from top to bottom, the upper saturated soil body and the lower unsaturated soil body are separated by a wetting front, and the volume water content of the upper saturated soil body and the lower unsaturated soil body is respectively theta 1 、θ 0 ，θ 1 Regarded as the saturated volume water content, θ 0 The water content of the initial volume is represented and is determined according to investigation sampling and test experiments; calculating the depth z of the wetting front according to the accumulated infiltration rainfall in the rainfall process w The unit is m, as shown in formula (1),
wherein I is accumulated infiltration quantity, the unit is m, the relation between the accumulated infiltration quantity and soil infiltration rate I (the unit is m/s) obtained by calculation according to rainfall data and soil parameters is shown as the formulas (2-1) to (2-3),
when I is equal to or greater than qcos α, I=qcos αt (2-2)
When I < qcos α, i=it (2-3)
In the invention, the infiltration rate i determines the rainfall infiltrated into the slope, the infiltration rate is the maximum rainfall absorbed by the soil body in unit time, and is related to the water content of the soil body, and the drier the soil body is, the larger the infiltration rate is; assuming that the infiltration rate is infinite at the beginning of rainfall, all rainwater is absorbed by soil; in the early period of rainfall, i is more than q cos alpha, and the infiltration amount is determined by the effective rainfall intensity; along with the gradual saturation of the upper soil body, the infiltration rate i of the soil body rapidly decreases, i is less than q cos alpha, the infiltration amount is determined by the infiltration rate, and the redundant rainwater flows along the slope surface.
Meanwhile, the accumulated infiltration amount I and the rainfall duration t (unit: s) satisfy the formulas (3-1) to (3-3),
wherein k is s The saturation permeability coefficient of the wetting front is determined according to investigation sampling and test experiments, and the unit is m/s; s is(s) f The unit is m, which is determined according to the characteristic curve of soil mass and soil water for the matrix suction force at the wetting front.
Preferably, in the step 2.3, the slope safety factor F in the continuous rainfall is obtained according to the unsaturated soil mechanics limit balance method on the basis of the rainfall infiltration model s ，
Wherein c' is the effective cohesion, in kPa,is the effective internal friction angle, the unit is DEG, gamma t Is the soil body weightDegree, in kN/m 3 C' and->The method is determined by combining investigation sampling and test experiments with computer simulation inversion;
safety factor F s Is the criterion of slope stability, F s >Slope is stable at 1 time, F s Slope instability is less than or equal to 1.
Preferably, the step 3 includes the steps of:
step 3.1: constructing a slope stability probability evaluation model based on Monte Carlo simulation: generating a plurality of groups, such as 100000 groups of soil parameter random vectors, by using probability distribution characteristics of soil parameters in the step 1, inputting the soil parameters into the model of the step 2, and performing Monte Carlo simulation to obtain corresponding group numbers, such as 100000 groups of slope safety coefficients F s Obtaining landslide probability of a slope in a rainfall process;
step 3.2: f based on the groups s And constructing a slope stability probability evaluation model, and formulating different rainfall threshold early warning grades corresponding to landslide probability, for example, taking landslide occurrence probabilities of 1%, 5% and 10% as early warning indexes of three grades from low to high, and formulating rainfall threshold early warning grade standards of yellow, orange and red.
Preferably, in step 4, a rainfall data set with the rainfall characteristics of the landslide research area is constructed by adopting a method of uniform design according to the rainfall duration, the accumulated rainfall, the rainfall intensity and the like of the historical rainfall data of the landslide research area, and a plurality of groups, such as 30 groups, of rainfall data sets with the rainfall characteristics of the landslide research area are constructed, and the rainfall data sets cover a plurality of rainfall types (uniform, peak type, incremental and decremental type), different rainfall durations, the accumulated rainfall and the rainfall intensity.
Preferably, the constructed rainfall data set is input into a slope stability probability evaluation model to obtain corresponding group numbers, namely 30 groups of landslide occurrence probability in the rainfall process; recording different landslide occurrence probabilities, wherein the average rainfall intensity I and the rainfall duration D corresponding to 1%, 5% and 10% are combined, I is taken as an ordinate, D is taken as an abscissa, the rainfall threshold curves corresponding to the landslide occurrence probabilities (1%, 5% and 10%) are obtained by fitting the data points, and the I-D rainfall threshold early warning curves of all the levels corresponding to the different landslide occurrence probabilities are obtained, wherein the I-D rainfall threshold early warning curves are three levels of yellow, orange and red.
Preferably, in step 5, a combination of rainfall duration (D) and rainfall intensity (I) is obtained according to the real-time rainfall monitoring data, the relative positions of the combination and the I-D rainfall threshold early-warning curve are compared, and when the point is higher than an early-warning curve with a certain level (yellow, orange and red), an early-warning signal with a corresponding level is sent out based on the early-warning curve.
The invention relates to a rainfall type shallow landslide early warning method based on probability analysis, which constructs a rainfall I-D threshold curve of a rainfall type shallow landslide based on probability analysis, and realizes early warning of the rainfall type shallow landslide by using the rainfall I-D threshold curve.
The invention has the beneficial effects that:
(1) The method is not completely dependent on historical rainfall data statistics, and influences of catastrophe mechanisms, hydrologic effects and geological environment conditions of slopes under rainfall are considered, so that accurate early warning of different areas is realized;
(2) The method can realize the fine early warning of a small-scale area or the degree of 'one slope one threshold', and the rainfall threshold is relatively accurate and has low false alarm rate;
(3) The dynamic early warning under the I-D rainfall threshold curve is realized, the landslide hazard degree can be effectively reflected by feeding back the landslide hazard degree according to the magnitude of the landslide occurrence probability based on the dynamic and quantitative updating of the landslide hazard degree according to the real-time rainfall data, and the landslide hazard degree is reflected to the early warning level.
Drawings
FIG. 1 is a schematic view of a ramp according to the present invention;
FIG. 2 is a diagram of a road map for constructing an I-D rainfall threshold curve and a real-time early warning application technology according to the invention;
FIG. 3 is an I-D rainfall threshold early warning graph of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1 to 2, the specific implementation steps of the present invention are:
s1, acquiring the gradient, soil parameters and statistical distribution characteristics of the slope shown in the figure 1, wherein the table 1 is shown;
TABLE 1 statistical distribution of landslide soil hydrology and mechanical parameters
And randomly generating 100000 groups of parameter samples obeying a statistical distribution rule.
S2, constructing a rainfall database representing rainfall characteristics of the area by adopting a uniform design method according to historical rainfall data, wherein the rainfall database comprises 30 groups of rainfall data of four types of uniform, peak value type, incremental and decremental rainfall data, and the 30 groups of rainfall data are shown in a table 2;
table 2 study area rainfall database
In table 2, D represents the duration of rainfall in units: h, performing H; i represents the intensity of the rainfall in hours, unit: mm; e represents the accumulated rainfall, unit: mm.
S3, referring to FIG. 2, 100000 groups of soil parameters and rainfall data sets (table 2) in the step S1 are sequentially input into a slope stability evaluation model (formulas 1-4), and landslide probabilities under 30 groups of different rainfall conditions are obtained through Monte Carlo simulation.
S4, calculating a combination of rainfall duration (D) and rainfall intensity (I) corresponding to landslide probabilities of 1%, 5% and 10% in the calculation result of the step S3; and respectively fitting points with the landslide occurrence probability of 1%, 5% and 10% by taking D as an abscissa and I as an ordinate to obtain corresponding rainfall I-D threshold early warning curves, namely yellow, orange and red threshold early warning curves, as shown in figure 3.
S5, referring to FIG. 2, a method for implementing early warning according to a rainfall threshold early warning curve comprises the following steps: and comparing the relative positions of the combination of the I value and the D value of the real-time rainfall monitoring data and the I-D threshold early warning curve, and sending out an early warning signal of a corresponding grade when the point is higher than the early warning curve of a certain grade (yellow, orange and red).
By the method, a rainfall threshold curve of the rainfall type landslide can be constructed from the geological and hydrological characteristics of the slope, so that the rainfall type shallow landslide fine early warning is realized.
In order to achieve the above, the present invention also relates to a computer readable storage medium, on which a program for early warning of a rainfall shallow landslide based on probability analysis is stored, which when executed by a processor, implements the method for early warning of a rainfall shallow landslide based on probability analysis.
In order to achieve the above, the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the method for early warning of rainfall shallow landslide based on probability analysis when executing the program.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A rainfall type shallow landslide early warning method based on probability analysis is characterized in that: and constructing a rainfall I-D threshold curve of the rainfall shallow landslide based on probability analysis, and realizing early warning of the rainfall shallow landslide by using the rainfall I-D threshold curve.
2. The rainfall shallow landslide early warning method based on probability analysis according to claim 1, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: the method comprises the following steps:
step 1: acquiring landslide research area data and soil parameters required by infiltration analysis and limit balance analysis; determining probability distribution characteristics of the soil parameters;
step 2: constructing a deterministic slope stability evaluation model;
step 3: constructing a slope stability probability evaluation model on the basis of the probability distribution characteristics of the soil parameters in the step 1 and the model in the step 2, and obtaining the slope instability probability in the rainfall process;
step 4: acquiring historical rainfall data, constructing a rainfall data set with rainfall characteristics of the landslide research area, inputting the rainfall data set into a slope stability probability evaluation model, making early warning of different grades according to probability, and constructing a rainfall I-D threshold curve of early warning of each grade;
step 5: and on the basis of the obtained rainfall I-D threshold curves with different early warning grades, combining real-time rainfall monitoring data, and dynamically early warning landslide.
3. The rainfall shallow landslide early warning method based on probability analysis according to claim 2, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: in step 1, the landslide study area data includes rainfall data.
4. The rainfall shallow landslide early warning method based on probability analysis according to claim 2, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: the step 2 comprises the following steps:
step 2.1: simulating a rainfall infiltration process according to the real-time rainfall intensity to obtain the depth z of a slope wetting front in the real-time rainfall process w ；
Step 2.2: determining key parameters for calculating a slope stability safety coefficient;
step 2.3: depth z of wetting front using step 2.1 w And (3) carrying out slope stability analysis by combining an unsaturated soil mechanical limit balance method to obtain a slope safety coefficient in the continuous rainfall process.
5. The rainfall type shallow landslide early warning method based on probability analysis according to claim 4, wherein the rainfall type shallow landslide early warning method based on probability analysis is characterized in that: in the step 2.1, the rainfall direction is perpendicular to the horizontal plane, the intensity is q, the slope angle is alpha, only the rainfall in the normal direction of the slope surface infiltrates into the soil body, and the rainfall along the slope surface downwards flows along the slope surface, so that the effective rainfall intensity is q cos alpha; in the rainfall infiltration process, the slope body is gradually saturated from top to bottom, the upper saturated soil body and the lower unsaturated soil body are separated by a wetting front, and the volume water content of the upper saturated soil body and the lower unsaturated soil body is respectively theta 1 、θ 0 Calculating the depth z of the wetting front according to the accumulated infiltration rainfall in the rainfall process w ，
I is the accumulated infiltration quantity, which is satisfied,
when I is equal to or greater than qcos α, I=qcos αt (2-2)
When I < qcos α, i=it (2-3)
The accumulated infiltration quantity I and the rainfall duration t are satisfied,
i is infiltration rate, t is rainfall duration, k s Is the saturation permeability coefficient at the wetting front, s f Is the suction of the matrix at the wetting front.
6. The rainfall type shallow landslide early warning method based on probability analysis according to claim 4, wherein the rainfall type shallow landslide early warning method based on probability analysis is characterized in that: in the step 2.3, the slope safety coefficient F in the continuous rainfall process is obtained s ，
Wherein c' is the effective cohesion,the effective internal friction angle is gamma, and the soil body weight is gamma; f (F) s >Slope is stable at 1 time, F s Slope instability is less than or equal to 1.
7. The rainfall shallow landslide early warning method based on probability analysis according to claim 2, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: the step 3 comprises the following steps:
step 3.1: generating a plurality of groups of soil parameter random vectors according to probability distribution characteristics of soil parameters in the step 1, inputting the soil parameter random vectors into the model of the step 2, and performing Monte Carlo simulation to obtain slope safety coefficients F of corresponding groups s Obtaining landslide probability of a slope in a rainfall process; step 3.2: f based on the groups s And constructing a slope stability probability evaluation model, and formulating different rainfall threshold early warning grades corresponding to the landslide probability.
8. The rainfall shallow landslide early warning method based on probability analysis according to claim 2, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: in step 4, constructing a rainfall data set with rainfall characteristics of the landslide study area as follows: according to the rainfall duration, the accumulated rainfall and the rainfall intensity of the historical rainfall data of the landslide research area, a plurality of groups of rainfall data sets with the rainfall characteristics of the landslide research area are constructed by adopting a uniform design method, and the rainfall data sets cover a plurality of rainfall types, different rainfall durations, the accumulated rainfall and the rainfall intensity.
9. The rainfall shallow landslide early warning method based on probability analysis according to claim 8, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: inputting the constructed rainfall data set into a slope stability probability evaluation model to obtain landslide occurrence probability in the rainfall process of the corresponding group number; and recording the combination of the average rainfall intensity I and the rainfall duration D corresponding to different landslide occurrence probabilities, taking I as an ordinate and D as an abscissa, fitting the data points to obtain rainfall threshold curves corresponding to the landslide occurrence probabilities, and obtaining I-D rainfall threshold early warning curves of various grades corresponding to the different landslide occurrence probabilities.
10. The rainfall shallow landslide early warning method based on probability analysis according to claim 9, wherein the rainfall shallow landslide early warning method based on probability analysis is characterized in that: and 5, obtaining a combination of rainfall duration and rainfall intensity according to the real-time rainfall monitoring data, comparing the relative positions of the combination and the I-D rainfall threshold early warning curve, and sending out early warning signals of corresponding grades based on the early warning curve.
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