CN115880863A

CN115880863A - Shallow loess landslide early warning method and device

Info

Publication number: CN115880863A
Application number: CN202211557969.XA
Authority: CN
Inventors: 张志强; 张贵峰; 宋永超; 朱永兴; 李�昊; 赵林杰; 张海鹏; 朱登杰; 黄增浩; 廖永力; 龚博
Original assignee: CSG Electric Power Research Institute; China Southern Power Grid Co Ltd
Current assignee: CSG Electric Power Research Institute; China Southern Power Grid Co Ltd
Priority date: 2022-12-06
Filing date: 2022-12-06
Publication date: 2023-03-31

Abstract

The invention relates to the technical field of landslide early warning, in particular to a shallow loess landslide early warning method and device. The invention discloses a shallow loess landslide early warning method and a device, wherein the method comprises the following steps: acquiring terrain data of a landslide body to be detected in a loess region, wherein the terrain data comprises the slope of the landslide body, the area of the landslide body and the area of a catchment area on the upper side of the landslide body; calculating a terrain factor of the landslide body to be measured according to the terrain data; acquiring real-time rainfall data of the loess area, and performing rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting a shallow loess landslide; calculating a landslide early warning value according to the terrain factor and the first rainfall data; and outputting an early warning signal according to the comparison result of the landslide early warning value and a preset landslide early warning critical value, so that the early warning accuracy of the shallow loess landslide is improved.

Description

Shallow loess landslide early warning method and device

Technical Field

The invention relates to the technical field of landslide early warning, in particular to a shallow loess landslide early warning method and device.

Background

The shallow loess landslide refers to the phenomenon that soil body integrally slides down along the weak surface under the action of gravity in the thick loess high slope section. According to the thickness division of the landslide body, the landslide can be divided into four types, namely shallow layer landslide, middle layer landslide, rear layer landslide and huge thick layer landslide. The shallow loess landslide has the characteristics of high outbreak frequency and high distribution density, and is easy to cause outbreak regional geological disaster events. Therefore, shallow loess landslide needs to be monitored and early-warning is timely performed to reduce safety risks.

The existing landslide early warning technology is to analyze and early warn landslide through rainfall data. However, not all rainfall creates a landslide risk, and different terrains have different geographical characteristics, and may have different effects even under the same rainfall conditions. Therefore, rainfall data and terrain conditions can affect the accuracy of landslide warning. How to provide a shallow loess landslide early warning method to improve the accuracy of shallow loess landslide early warning becomes a problem to be solved.

Disclosure of Invention

The invention provides a shallow loess landslide early warning method and device, which are used for improving the early warning accuracy of shallow loess landslide.

The invention provides a shallow loess landslide early warning method on one hand, which comprises the following steps:

acquiring terrain data of a landslide body to be detected in a loess region, wherein the terrain data comprises the slope of the landslide body, the area of the landslide body and the area of a catchment area on the upper side of the landslide body;

calculating a terrain factor of the landslide body to be measured according to the terrain data;

acquiring real-time rainfall data of the loess area, and performing rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting a shallow loess landslide;

calculating a landslide early warning value according to the terrain factor and the first rainfall data;

and outputting an early warning signal according to a comparison result of the landslide early warning value and a preset landslide early warning critical value.

Optionally, acquire the real-time rainfall data in loess area, it is right real-time rainfall data carries out the rainfall and cuts apart, and the first rainfall data that obtains arousing shallow loess landslide includes:

s1: acquiring meteorological data of the loess area, and determining a rainfall critical value and a rainfall intensity critical value according to the meteorological data;

s2: acquiring and accumulating the real-time rainfall of the loess area to obtain a second real-time rainfall total value, and accumulating the acquisition time of the real-time rainfall to obtain the duration of a second rainfall;

s3: when the second real-time rainfall total value reaches a rainfall critical value, judging whether the duration of the second rainfall is greater than a second preset duration, and if not, executing S4; if so, clearing the second real-time rainfall total value and the second rainfall duration, and executing S2 again;

s4: and calculating second rainfall intensity according to the second rainfall duration and the second real-time rainfall total value, outputting the second real-time rainfall total value and the second rainfall duration as first rainfall data of the current excitation of the shallow loess landslide when the second rainfall intensity is smaller than the rainfall intensity critical value, then clearing the second real-time rainfall total value and the second rainfall duration, and executing S2 again.

Optionally, the S4 further includes:

and when the second rainfall intensity is not less than the rainfall intensity critical value, continuously updating the second real-time rainfall total value and the second rainfall duration according to the S2, and updating the second rainfall intensity according to the updated second real-time rainfall total value and the updated second rainfall duration until the updated second rainfall intensity is less than the rainfall intensity critical value.

Optionally, the first rainfall data includes a first real-time rainfall total value and a first rainfall duration, and the calculating a landslide warning value according to the terrain factor and the first rainfall data includes:

calculating to obtain first rainfall intensity according to the first real-time rainfall total value and the first rainfall duration;

calculating a landslide early warning value according to the terrain factor, the first rainfall intensity and the first rainfall duration;

the landslide early warning value is calculated according to the following formula:

Cr＝T(I/IM)(D/Dd)0.45

cr is a landslide early warning value, T is a terrain factor, I is a first rainfall intensity, IM is a rainfall intensity critical value, D is the duration of the first rainfall, and Dd is unit time.

Optionally, the meteorological data comprises an average annual rainfall and an average annual maximum minimum rainfall intensity; the step of determining a rainfall threshold value and a rainfall intensity threshold value according to the meteorological data comprises:

calculating a rainfall critical value according to the annual average rainfall;

and calculating a rainfall intensity critical value according to the average value of the rainfall intensity when the year is maximum and minimum.

Optionally, the formula for calculating the rainfall critical value is as follows:

R*＝0.1RN

wherein R is a rainfall critical value, and RN is the annual average rainfall of the loess region.

Optionally, the formula for calculating the critical value of rainfall intensity is as follows:

I*＝0.02IM

wherein I is a critical value of rainfall intensity, and IM is an average value of the rainfall intensity of the loess region at the maximum and minimum year.

Optionally, the calculation formula for obtaining the terrain factor of the to-be-measured landslide mass by calculation according to the terrain data is as follows:

T＝tana+1.25U＝(1+1.25Au/A)tana

wherein U is a slow-up factor; au is the area of the upper side catchment area; a is the slope of the landslide body; a is the area of a landslide body; t is a terrain factor.

Optionally, the outputting an early warning signal according to a comparison result between the landslide early warning value and a preset landslide early warning critical value includes:

when the landslide early warning value is smaller than a first landslide early warning critical value, outputting a first grade early warning signal;

when the landslide early warning value is greater than or equal to a first landslide early warning critical value and smaller than a second landslide early warning critical value, outputting a second-level early warning signal;

when the landslide early warning value is greater than or equal to a second landslide early warning critical value and smaller than a third landslide early warning critical value, outputting a third grade early warning signal;

and outputting a fourth grade early warning signal when the landslide early warning value is greater than or equal to a third landslide early warning critical value.

In another aspect, the present invention provides a shallow loess landslide warning device, comprising:

the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring topographic data of a landslide body to be detected in a loess region, and the topographic data comprises the slope of the landslide body, the area of the landslide body and the area of a catchment area on the upper side of the landslide body;

the first calculation module is used for calculating a terrain factor of the to-be-detected landslide mass according to the terrain data;

a rainfall segmentation module for acquiring real-time rainfall data of the loess area, performing rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting the shallow loess landslide,

the second calculation module is used for calculating a landslide early warning value according to the terrain factor and the first rainfall data;

and the early warning module is used for outputting an early warning signal according to the comparison result of the landslide early warning value and a preset landslide early warning critical value.

According to the technical scheme, the invention has the following advantages:

the invention provides a shallow loess landslide early warning method, which comprises the steps of obtaining terrain data of a landslide body to be detected in a loess region, calculating a terrain factor of the landslide body to be detected according to the terrain data, considering the influence of the terrain condition of the loess region on the shallow loess landslide, obtaining real-time rainfall data of the loess region, carrying out rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting the shallow loess landslide, distinguishing rainfall data influencing the landslide and not influencing the landslide, avoiding the interference of the rainfall data without influence on the early warning of the shallow loess landslide, improving the early warning accuracy of the shallow loess landslide, calculating a landslide early warning value by using the first rainfall data and the terrain factor, outputting an early warning signal according to the comparison result of the landslide early warning value and a preset landslide early warning critical value, fully considering the combined action of the geological factor of the loess region and the rainfall factor on the shallow loess landslide, and accurately predicting the risk of the landslide to be detected.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.

Fig. 1 is a schematic diagram illustrating a shallow loess landslide warning method according to an aspect of an embodiment of the present invention;

fig. 2 is a schematic diagram illustrating a shallow loess landslide warning method according to another aspect of the present invention;

fig. 3 is a shallow loess landslide warning device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in 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 obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention is applied to shallow landslide early warning in loess areas, and particularly relates to shallow landslide early warning in loess areas with specific terrain conditions, wherein the specific terrain conditions mean that an upper catchment area of a landslide body is located on a tableland in the loess areas, the catchment area is a gentle terrain with a slope of almost 0 degree, and the lower part of the landslide body is provided with an empty surface.

Referring to fig. 1, fig. 1 is a schematic view illustrating a shallow loess landslide warning method according to an aspect of the present invention.

The shallow loess landslide early warning method provided by the embodiment comprises the following steps:

101. and acquiring the topographic data of the landslide body to be detected in the loess area, wherein the topographic data comprises the slope of the landslide body, the area of the landslide body and the area of the catchment area on the upper side of the landslide body.

It should be noted that the landslide mass to be measured refers to a potential landslide mass, i.e., a mountain mass in which landslide is relatively likely to occur.

The acquisition mode of the terrain data can be obtained through field survey and mapping, or the terrain data of each landslide body can be measured in advance and stored in a database, each landslide body is numbered, the number of the landslide body is associated with the corresponding terrain data, the corresponding association relation is stored, and during acquisition, the corresponding terrain data can be inquired through the number of the landslide body to be detected.

The schematic diagram of the landslide body is shown in fig. 3, wherein Au is the area of the catchment area on the upper side; a is the slope of the landslide body; a is the area of the landslide body.

102. And calculating the terrain factor of the landslide body to be measured according to the terrain data.

In the embodiment, the terrain factor of the landslide body is calculated according to the slope of the landslide body, the area of the landslide body and the area of the catchment area on the upper side of the landslide body. The calculation formula is as follows:

T＝tana+1.25U＝(1+1.25Au/A)tana

wherein U is a slow-up factor; au is the area of the upper side catchment area; a is the slope of the landslide body; a is the area of the landslide body; t is a terrain factor.

It can be understood that, upper portion catchment district to the landslide body is in on the tableland of loess area, the catchment district has the slope and is the gentle topography of 0 degree almost, and the lower part of landslide body has the topography condition that faces the free surface, the upper portion slope is mild, and the landslide body slope is great, cause easily to pull the crack, the rainwater infiltrates easily, lead to soil body subassembly saturation and softening, and when the landslide body has and faces the free surface, the rainwater continues to infiltrate, form after the shear plane along the soil body in the same direction as the passageway and down, it infiltrates to link up in face free surface department easily, lead to the slope body gliding, cause shallow loess layer landslide. Therefore, aiming at the special topographic characteristics that the shallow loess landslide is easily caused, the topographic factor of the landslide body is calculated by acquiring the slope of the landslide body to be detected, the area of the landslide body and the area of the catchment area on the upper side of the landslide body, the topographic factor is fully utilized to carry out early warning analysis on the shallow loess landslide, and the early warning accuracy of the shallow loess landslide is improved.

103. The method comprises the steps of obtaining real-time rainfall data of a loess area, and carrying out rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting a shallow loess landslide.

It should be noted that, in this embodiment, real-time rainfall data in the loess region tableland is acquired. And the upper catchment area of the landslide body is positioned on the tableland, and the rainfall elevation on the tableland is consistent with the elevation of the catchment area of the landslide body, so that the rainfall data on the tableland is basically the same as the rainfall data of the landslide body to be detected, and therefore errors caused by rainfall acquisition can be effectively reduced by acquiring real-time rainfall data on the tableland as the rainfall data of the landslide body to be detected, and the reliability of the rainfall data is further improved.

After the real-time rainfall data are obtained, rainfall segmentation is carried out on the rainfall data, rainfall influencing and non-influencing on shallow loess landslide is distinguished, so that first rainfall data for exciting the shallow loess landslide are obtained, interference of the rainfall data without landslide influence on landslide early warning is avoided, and accuracy of the landslide early warning is improved.

It is understood that the first rainfall data exciting the shallow loess landslide is rainfall data that may induce the shallow loess landslide. The first rainfall data comprises a first total real-time rainfall value and a first rainfall duration

104. And calculating a landslide early warning value according to the terrain factor and the first rainfall data.

It should be noted that the first rainfall data includes a first rainfall duration and a first total real-time rainfall amount value, and the first rainfall intensity may be determined according to the first total real-time rainfall amount value and the first rainfall duration. Then, calculating a landslide early warning value according to the first rainfall intensity, the first rainfall duration and the terrain factor

The formula for calculating the landslide early warning value is as follows:

Cr＝T(I/IM)(D/Dd) ^0.45

In this embodiment, dd is preferably 1h.

The landslide early warning value that shallow loess landslide was induced is calculated to topographic data and the rainfall data through utilizing the loess area landslide body to this embodiment, has fully considered the geological characteristics and the rainfall characteristics in loess area for the landslide early warning value that obtains calculates more accords with the inside texture that induces shallow loess landslide, can accurately predict the landslide risk of the loess area landslide body that awaits measuring, has improved the early warning degree of accuracy to shallow loess landslide.

105. And outputting an early warning signal according to a comparison result of the landslide early warning value and a preset landslide early warning critical value.

It should be noted that the preset landslide early warning critical values include a first landslide early warning critical value, a second landslide early warning critical value, and a third landslide early warning critical value.

This embodiment is through comparing landslide early warning value and landslide early warning critical value, according to the comparative result, falls into a plurality of risk levels to the early warning signal that output and risk level correspond, with carry out the early warning to shallow loess landslide, the early warning fineness is high, has improved the practicality of landslide prevention and cure.

The shallow loess landslide early warning method provided by the embodiment comprises the steps of obtaining terrain data of a landslide body to be detected in a loess region, calculating a terrain factor of the landslide body to be detected according to the terrain data, considering the influence of terrain conditions of the loess region on the shallow loess landslide, obtaining real-time rainfall data of the loess region, carrying out rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting the shallow loess landslide, distinguishing rainfall data influencing the landslide and not influencing the landslide, avoiding the interference of the rainfall data without influence on the shallow loess landslide, improving the early warning accuracy of the shallow loess landslide, calculating a landslide early warning value by using the first rainfall data and the terrain factor, outputting an early warning signal according to a comparison result of the landslide early warning value and a preset landslide early warning critical value, fully considering the combined action of the geological factors of the loess region and the rainfall factors on the shallow loess landslide, and improving the early warning accuracy of the early warning of the landslide body to be detected.

Example two:

referring to fig. 2, fig. 2 is a schematic view of a shallow loess landslide warning method according to an embodiment of the present invention.

This embodiment further defines step 103 on the basis of including the whole content of the first embodiment. The method comprises the following specific steps:

s1: and acquiring meteorological data of the loess area, and determining a rainfall critical value and a rainfall intensity critical value according to the meteorological data.

It should be noted that the meteorological data is historical data, and includes an average annual rainfall and an average annual rainfall at maximum and minimum. Wherein, the meteorological data can be obtained by consulting the hydrologic manual or meteorological station data of loess gas degree.

After the meteorological data is acquired, the rainfall critical value and the rainfall intensity critical value which accord with the loess area are determined by using the special geographical features of the loess area and combining the meteorological data, and the rainfall critical value and the rainfall intensity critical value are used as the judgment reference of rainfall affecting the shallow loess landslide.

Specifically, the steps of determining the rainfall critical value and the rainfall intensity critical value according to the meteorological data are as follows:

s11: calculating a rainfall critical value according to the annual average rainfall; the formula for calculating the rainfall critical value is as follows:

R*＝0.1RN

r is the critical value of rainfall, and RN is the average annual rainfall in the loess area.

It should be noted that the soil body permeability coefficient of the common homogeneous loess is 10-8 m/s-10-6 m/s, namely the common infiltration of the rainwater requires 11.6 days-1157.4 days to reach the soil body depth of 1m, and the thickness of the loess shallow layer landslide is generally 0.5-2m, so the common rainfall infiltration cannot directly influence the landslide. However, vertical cracks of loess soil bodies are developed, potential landslide bodies have steep slopes and upper flat slopes, tensile cracks are formed in upper catchment areas, rainwater collected on the upper portions of the landslide bodies seeps down to sliding surfaces through the vertical cracks and the tensile cracks, and landslide is induced. However, even if vertical cracks-tension cracks exist, rainwater needs to seep downwards in the cracks and seep downwards to the sliding surface along the crack channel for a long time, and the smaller rainfall is intercepted by the loess soil layer in the seepage channel, so that the landslide is not influenced.

Therefore, the present embodiment calculates the rainfall critical value by using 10% of the average local annual rainfall according to the geological characteristics of the loess area, and determines the preset time period to be 72 hours according to the infiltration time of the rainwater in the loess area in the loess soil fracture channel. Therefore, the duration range of 1-72 hours is used as one of the judgment conditions for judging whether the rainfall calculation stage for exciting the shallow loess landslide is entered, so that the rainfall data for determining the excitation of the shallow loess landslide is more accurate, the condition that excessive rainfall processes are calculated in the rainfall data influencing the loess landslide is avoided, the possibility of early warning and misjudgment of the shallow loess landslide is reduced, and the early warning accuracy of the shallow loess landslide is further improved.

S12: and calculating the critical value of the rainfall intensity according to the average value of the rainfall intensity when the year is maximum and minimum.

The formula for calculating the critical value of rainfall intensity is as follows:

I*＝0.02IM

The loess area is a drought area, the average annual rainfall of the drought area is not more than 1000mm, and the average annual rainfall of the loess area is about 500 mm; generally, the sunshine time in arid areas is more than 2000h, and the loess areas are more than 2500h, so that the loess areas have the characteristics of less rainfall, long sunshine time and large evaporation capacity. In the loess area, the limited rainfall is easy to evaporate along with the larger sunshine time and evaporation capacity, and particularly, the rainfall is easier to evaporate when not entering the soil, becomes ineffective rainfall and cannot influence the landslide. In addition, the loess landslide body is provided with a platform with the upper part being nearly flat, and is a landslide catchment area and also a main rainwater catchment area for inducing the loess landslide by rainfall; however, since the slope of the catchment area is substantially 0, the rainwater in the catchment area cannot be gathered together very quickly, and the evaporation speed is higher. In addition, although the plants exist in the loess area, the plants are rare, rainwater is intercepted by the plants, and the rainwater intercepted by root systems is less, so that more evaporation phenomena exist in the rainwater gathering process.

Based on the characteristics of the sunshine in above-mentioned loess area, topography, vegetation, the rainfall intensity critical value is obtained through utilizing local 2% calculation of the biggest hour rainfall mean value many years, the rainfall process of having avoided being taken into account because of the rainfall of undersize, and then the rainfall duration has been prolonged, cause very little rainfall to still take into account the rainfall in-process that influences the loess landslide, lead to the problem of erroneous judgement loess landslide, for the analysis of loess landslide provides effectual first rainfall data support, and then the degree of accuracy of shallow loess landslide early warning has been improved.

S2: and acquiring and accumulating the real-time rainfall of the loess area to obtain a second real-time rainfall total value, and accumulating the acquisition time of the real-time rainfall to obtain the second rainfall duration.

In the present embodiment, a sensor is provided in the tableland of the loess area to collect rainfall in the loess area. The real-time rainfall refers to the rainfall per hour on the tablelands in the loess area. And accumulated once per hour.

When the real-time rainfall is obtained once, the obtained real-time rainfall is superposed on the basis of the second total real-time rainfall obtained through the previous accumulation to obtain a second total real-time rainfall, and 1 is added on the basis of the second rainfall duration obtained through the previous accumulation to obtain a second rainfall duration obtained through the current accumulation. For example, at the time of the 12 th acquisition, the accumulated second rainfall duration is 12 hours, the accumulated second real-time rainfall total value is 20mm, if the acquired rainfall at the time of the 13 th acquisition is 0.5mm, the accumulated second real-time rainfall total value is 20.5mm, and the accumulated second rainfall duration is 12+1=13 hours.

It is understood that when the first collection receives real-time rainfall, the second rainfall is accumulated for one hour. When the real-time rainfall value is acquired for the first time, the accumulated second real-time rainfall total value is the real-time rainfall itself. For example, if the real-time rainfall acquired for the first time is a, the total value of the second real-time rainfall accumulated this time is a.

S3: when the second real-time rainfall total value reaches the rainfall critical value, judging whether the duration of the second rainfall is greater than a second preset time, and if not, executing S4; if yes, clearing the second total real-time rainfall value and the second rainfall duration, and executing S2 again.

It should be noted that, in steps S2 to S3, the second real-time total rainfall value and the second rainfall duration are accumulated once per hour, and after accumulation, whether the second real-time total rainfall value reaches the rainfall critical value is determined until it is determined that the second real-time total rainfall value reaches the rainfall critical value.

When the second real-time rainfall total value is smaller than the rainfall critical value and the second rainfall duration is not longer than the preset duration, the rainfall accumulation stage is indicated, and continuous accumulation is needed to determine whether to perform rainfall segmentation. Therefore, S2 is executed continuously to obtain the next real-time rainfall, and on the basis of the second real-time rainfall total value, the next real-time rainfall is accumulated to obtain the next second real-time rainfall total value. And adding 1 to the second rainfall duration of the current time, and accumulating to obtain the next second rainfall duration. And then S3 is executed, whether the total rainfall value of the next time reaches the rainfall critical value is judged, if the total rainfall value is still smaller than the rainfall critical value, S2 is continuously executed again until the second real-time rainfall total value reaches the rainfall critical value, or the duration of the second rainfall exceeds the preset duration.

When the second real-time total rainfall value is smaller than the rainfall critical value and the second rainfall duration is longer than the preset duration, it is indicated that the rainfall does not exceed the rainfall critical value all the time in the rainfall accumulation within the preset duration, and it is indicated that the rainfall in the period has no influence on the loess landslide, so that the rainfall data influencing the landslide is not counted, namely the rainfall segmentation is finished in the current round, and the rainfall calculation stage for exciting the shallow loess landslide is not entered, so that the second real-time total rainfall value and the second rainfall duration accumulated in the current round are cleared, and S2 is executed again to enter the next round of rainfall segmentation.

When the second real-time total rainfall value reaches the rainfall critical value and the second rainfall duration exceeds the preset duration, although the second real-time total rainfall value exceeds the rainfall critical value, the second rainfall duration already exceeds the preset duration, so that the current rainfall accumulation stage is ended, the next rainfall accumulation stage is restarted instead of the rainfall calculation stage for exciting the shallow loess landslide, therefore, the moment for judging the ending is taken as the current moment, the current accumulation is cleared to obtain the second rainfall duration and the second real-time total rainfall value, S2 is executed again, the next rainfall accumulation is started, and the next rainfall data for exciting the shallow loess landslide is calculated.

S4: calculating second rainfall intensity according to the second rainfall duration and the second real-time rainfall total value, outputting the second real-time rainfall total value and the second rainfall duration as first rainfall data of the excitation of the shallow loess landslide when the second rainfall intensity is smaller than a rainfall intensity critical value, clearing the second real-time rainfall total value and the second rainfall duration, and executing S2 again; and when the second rainfall intensity is not less than the rainfall intensity critical value, continuously updating the second real-time rainfall total value and the second rainfall duration according to the S2, and updating the second rainfall intensity according to the updated second real-time rainfall total value and the updated second rainfall duration until the updated second rainfall intensity is less than the rainfall intensity critical value.

It should be noted that, when the second real-time total rainfall value reaches the rainfall critical value and the second rainfall duration is not longer than the preset duration, it indicates that the rainfall affecting the loess landslide has started, and the rainfall calculation stage of exciting the shallow loess landslide is entered. In the rainfall calculation stage, the second real-time total rainfall value at the moment is used as an initial value of the rainfall in the rainfall calculation stage, namely the initial value is used for exciting early rainfall of the shallow loess landslide. The second rainfall duration at this time is taken as an initial value of the second rainfall duration in the rainfall calculation stage. Based on the method, the early-stage rainfall for exciting the shallow loess landslide and the corresponding duration of the second rainfall are determined, so that rainfall unrelated to the excitation of the shallow loess landslide is preliminarily distinguished.

And after entering a rainfall calculation stage for exciting the shallow loess landslide, calculating the current rainfall intensity according to the second real-time rainfall total value and the second rainfall duration, continuously judging whether the rainfall intensity is smaller than a rainfall intensity critical value, and dividing into two conditions according to the judgment result of the rainfall intensity.

(1) When the rainfall intensity is smaller than the rainfall intensity critical value, the rainfall at the moment is not influenced on the landslide, therefore, the rainfall for exciting the shallow loess landslide is finished, the duration of the second rainfall obtained at present is used as the duration of the second rainfall for exciting the shallow loess landslide at the moment, the total value of the second real-time rainfall is used as the total value of the rainfall for exciting the shallow loess landslide at the moment, and the duration of the second rainfall and the total value of the rainfall are output as first rainfall data for exciting the shallow loess landslide at the moment. Therefore, rainfall influencing the loess landslide and rainfall not influencing the loess landslide are separated, rainfall data for exciting the shallow loess landslide are obtained, effective rainfall data are provided for early warning of the shallow loess landslide, and the early warning accuracy of the shallow loess landslide is improved.

It is understood that the second rainfall duration output is the first rainfall duration in the first rainfall data. The output total rainfall value is the first real-time total rainfall value in the first rainfall data.

(2) When the rainfall intensity is not less than the rainfall intensity critical value, the current rainfall intensity can continuously cause landslide influence on the loess region, namely the rainfall exciting the shallow loess landslide at the time is not stopped yet and continues, therefore, on the basis of the second real-time rainfall total value obtained by current accumulation, the next real-time rainfall obtained by accumulation is continuously accumulated, the second real-time rainfall total value obtained by next accumulation in the rainfall calculation stage is obtained, 1 is added on the basis of the second rainfall duration obtained by current accumulation, the second rainfall duration obtained by next accumulation is obtained, then the next rainfall intensity is calculated according to the next second real-time rainfall total value and the second rainfall duration, and whether the next rainfall intensity is less than the rainfall intensity critical value is judged, so that whether the rainfall exciting the shallow loess landslide at the time is finished or not is determined.

For example: when the total value of the second real-time rainfall obtained by the accumulation of the rainfall stage is greater than the rainfall critical value R and the corresponding duration of the second rainfall does not exceed 72 hours, entering a rainfall calculation stage, and accumulating the rainfall accumulation stage to obtain the total value of the second real-time rainfall, which is used as an initial value R0 of the rainfall in the rainfall calculation stage (namely early rainfall); and accumulating the rainfall accumulation stage to obtain a second rainfall duration serving as an initial value D0 of the second rainfall duration in the rainfall calculation stage.

In the rainfall calculation stage, dividing the initial value R0 of the rainfall by the initial value D0 of the second rainfall duration to obtain an average rainfall intensity I0, and when the average rainfall intensity I0 is smaller than the rainfall intensity critical value, indicating that the rainfall of the current excitation of the shallow loess landslide is finished, wherein the total rainfall value of the current excitation of the shallow loess landslide is R0, and the total second rainfall duration is D0. And then, clearing the current accumulation to obtain a second real-time rainfall total value and a second rainfall duration, and entering a rainfall accumulation stage and a rainfall calculation stage of the next round, thereby completing rainfall segmentation of the next round.

When the average rainfall intensity I0 is larger than or equal to the rainfall intensity critical value, the rainfall of the loess landslide excited in the shallow layer continues, so that the real-time rainfall R1 acquired in the next hour continues to be superposed on the basis of the rainfall R0, and the second real-time rainfall total value R is R0+ R1. And adding 1 to D0, resulting in a second rainfall duration for the next hour of D = D0+1, after which the rainfall intensity I1= R/D = (R0 + R1)/(D0 + 1) is calculated. And then, judging whether the rainfall intensity I1 is smaller than the critical rainfall intensity, if so, indicating that the rainfall of the stimulated shallow loess landslide is finished, wherein the total rainfall capacity of the stimulated shallow loess landslide is R0+ R1, and the second rainfall duration is (D0 + 1). If not, the rainfall for exciting the shallow loess landslide is still continued, on the basis of R0+ R1, the real-time rainfall R2 acquired in the next hour is continuously superposed to obtain a second real-time rainfall total value R which is R0+ R1+ R2, on the basis of D0+1, the second rainfall duration obtained is D = D0+ 1= D0+2, the current rainfall intensity I2= R/D = (R0 + R1+ R2)/(D0 + 2) is calculated, whether the current rainfall intensity I2 is smaller than the critical value of the rainfall intensity is judged, if yes, the rainfall for exciting the shallow loess landslide is ended, if not, the second rainfall and the second real-time rainfall total value are continuously accumulated for the duration, until the rainfall intensity is judged to be smaller than the critical value of the rainfall, the rainfall calculation for exciting the shallow loess slide is ended, and the total value of the rainfall and the second rainfall for exciting the shallow loess landslide are obtained. Wherein the total rainfall value R = R0+ R1+ R2+ … … + Rn, the corresponding second rainfall duration D = D0+ n is calculated, and the total average rainfall intensity I is calculated by I = R/D. n is the nth hour. Rn is the real-time rainfall collected in the nth hour in the rainfall calculation stage.

In this embodiment, whether the rainfall calculation stage for exciting the shallow loess landslide is started is judged according to the second real-time rainfall total value and the judgment result of the duration of the second rainfall, so that the initial rainfall value and the rainfall starting time for exciting the shallow loess landslide are determined, whether the rainfall for exciting the shallow loess landslide is finished is determined according to the judgment result of the rainfall intensity, the rainfall finishing time for exciting the shallow loess landslide is determined, the problem that the rainfall data irrelevant to the loess landslide is counted into the rainfall data for exciting the shallow loess landslide is avoided, the accuracy of the early warning of the shallow loess landslide is reduced, influences and uninfluenced rainfall are distinguished, the obtained effective rainfall data for exciting the shallow loess landslide is obtained, and the accuracy of the early warning of the shallow loess landslide is improved.

The rainfall data of arousing shallow loess landslide that this embodiment calculated, do not receive the restriction of time, only relevant with the rainfall process, need not artificially to control the decay coefficient of the early rainfall of arousing shallow loess landslide, consequently, the rainfall data that causes the influence to shallow landslide that the calculation obtained accords with actual conditions more, can effectually will arouse the rainfall of shallow loess landslide and cut apart with the rainfall irrelevant with the landslide, thereby reflection rainfall that can be fine is to the infiltration influence of loess tension crack, improve the initial rainfall amount in rainfall calculation stage and to arousing the referential of shallow loess landslide, and then improve landslide early warning degree of accuracy.

In another embodiment, real-time rainfall is collected by sensors located at the tablelands.

The sensor that is used for gathering real-time rainfall is arranged through on the tableland in loess area to this embodiment for rainfall monitoring's elevation height is the same with the catchment area elevation height of the landslide body, thereby the real-time rainfall that gathers through the sensor is more accurate, more accords with the rainfall characteristic in loess area, very big promotion but data referential nature and accuracy, more be favorable to improving landslide early warning degree of accuracy.

In a specific embodiment, the number of sensors is multiple.

In the present embodiment, a plurality of sensors for acquiring real-time rainfall are arranged in the tableland in the loess area, so that the accuracy of data acquisition is improved. And after the real-time rainfall collected by the sensors is obtained, the real-time rainfall collected by the sensors is averaged to obtain a real-time rainfall average value, and the real-time rainfall average value is used as the real-time rainfall of the loess area to be detected, so that the precision of the real-time rainfall is further improved, and the landslide early warning accuracy can be improved.

In another specific embodiment, when the sensors are arranged, the tablelands in the loess area may be equally divided into grid areas according to the area of the tablelands in the loess area, and one sensor may be disposed at the center of each grid area, so as to further improve the accuracy of the collected real-time rainfall.

Example three:

the shallow loess landslide early warning method provided by this embodiment limits step 105 on the basis of including the first embodiment or the second embodiment. The method comprises the following specific steps:

when the landslide early warning value is greater than or equal to the first landslide early warning critical value and smaller than the second landslide early warning critical value, outputting a second-level early warning signal;

when the landslide early warning value is greater than or equal to the second landslide early warning critical value and smaller than a third landslide early warning critical value, outputting a third grade early warning signal;

and when the landslide early warning value is greater than or equal to the third landslide early warning critical value, outputting a fourth grade early warning signal.

It should be noted that the first landslide warning threshold value is 0.69. When the early warning critical value Cr of the loess shallow landslide is less than 0.69, the possibility of landslide is low, the first grade is obtained, and a first grade early warning signal is output.

The second landslide warning threshold is 0.88. When the early warning critical value Cr of the loess shallow landslide meets the following requirements: cr is more than or equal to 0.69 and less than 0.88, which indicates that the possibility of landslide is medium, and is a second grade, and a second grade early warning signal is output.

The early warning critical value of the third landslide is 1.15, and when the early warning critical value Cr of the loess shallow landslide meets the following requirements: cr is more than or equal to 0.88 and less than 1.15, the possibility of landslide is high, and a third grade early warning signal is sent out when the third grade is high

When the early warning critical value Cr of the loess shallow landslide is larger than or equal to 1.15, the landslide probability is very high, and the level is the fourth level, and a fourth early warning signal is sent.

The color of the first early warning signal is green, the color of the second early warning signal is yellow, the color of the third early warning signal is orange, and the color of the fourth early warning signal is red.

According to the landslide early warning method and the landslide early warning device, the grade of the landslide is divided according to the comparison result of the landslide early warning value and the preset landslide early warning critical value, and early warning fineness and intuition are improved.

The early warning method for shallow loess landslide provided by the invention will be further explained by combining with a specific application example.

In 2013, strong continuous rainfall in Yanan city pagoda region, yanchuan county and extension county from 7 months to 13 days causes large-area landslide, multiple cave cavities are damaged, and multiple persons casualty occurs. Landslide concentration occurred in 2013, 7 and 13 and 9. The local annual average rainfall RN is consulted as follows: 572.3mm in the pagoda region of Yanan city, 561.9mm in Yanchuan county, the prolonged county 514.8mm, the average value IM of rainfall intensity for 1 hour at the maximum over the years is: 29.5mm/h for pagoda district, yanchuan county, 29.9mm/h, and Yanchuan county, 29.3mm/h. The terrain factors T of 71 landslides are measured on site, the rainfall intensity I and the rainfall duration D of each landslide point are calculated by interpolating point by point and hour according to the rainfall station position, the hourly rainfall and the landslide point position, and the terrain factors, the first rainfall intensity, the first rainfall duration and the landslide early warning critical value of each landslide point are obtained by calculation and are shown in table 1.

Table 1 Yanan city 2013, 7 month, 13 day landslide body parameters, rainfall parameters and early warning table

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Comparative results for landslide grade, see table 2.

TABLE 2 landslide grade judgment correspondence table

As can be seen from table 2: the landslide risk grades of all landslide bodies are above the second grade; the number of landslides at the third level and the fourth level is 80.3%, i.e., there is a high possibility that 80.3% of the landslide bodies exist, and the number of landslides at the fourth level is 32.4%, i.e., there is a high possibility that the landslide is close to 1/3 (32.4%) of the landslide bodies. Through the verification of the historical data, the shallow loess landslide early warning method can accurately predict landslide conditions, greatly reduce the rate of missing judgment and ensure the landslide early warning reliability.

To sum up, the rainfall segmentation method for the shallow loess landslide provided by the embodiment of the invention has the following beneficial effects:

1. according to the embodiment of the invention, the terrain data of the landslide body to be detected in the loess region is obtained, the terrain factor of the landslide body to be detected is calculated according to the terrain data, the influence of the terrain condition of the loess region on the shallow loess landslide is considered, the real-time rainfall data of the loess region is obtained, the rainfall segmentation is carried out on the real-time rainfall data, the first rainfall data for exciting the shallow loess landslide is obtained, the rainfall data which influence the landslide and have no influence are distinguished, the interference of the rainfall data which have no influence on the shallow loess landslide on the early warning of the shallow loess landslide is avoided, the early warning accuracy of the shallow loess landslide is improved, the landslide early warning value is calculated by utilizing the first rainfall data and the terrain factor, the early warning signal is output according to the comparison result of the landslide early warning value and the preset landslide early warning critical value, the combined action of the geological factor of the loess region and the rainfall factor on the shallow loess landslide is fully considered, the early warning value obtained by calculation is more in line with the internal texture of inducing the loess, the landslide of the shallow landslide can be accurately predicted, and the early warning accuracy of the shallow landslide on the shallow loess landslide is improved.

2. In the embodiment of the invention, when the acquired real-time rainfall data is subjected to rainfall segmentation to obtain first rainfall data for exciting the shallow loess landslide, the meteorological data of the loess area are acquired, the rainfall critical value and the rainfall intensity critical value are determined according to the meteorological data, the real-time rainfall of the loess area is acquired, the duration of rainfall and the total real-time rainfall are obtained through accumulation, whether the total real-time rainfall reaches or exceeds the rainfall critical value in a preset time period is determined, if yes, the initial rainfall value for exciting the shallow loess landslide is calculated, and corresponding rainfall data accumulation for exciting the shallow loess landslide is carried out according to the calculated rainfall intensity, so that the first rainfall data for exciting the shallow loess landslide is obtained.

In the embodiment of the invention, the calculated rainfall data for exciting the shallow loess landslide is not limited by time, is only related to the rainfall process, and does not need to artificially control the attenuation coefficient of early rainfall for exciting the shallow loess landslide, so that the calculated rainfall data influencing the landslide better conforms to the actual condition of the loess region, the rainfall for exciting the shallow loess landslide can be effectively separated from the rainfall irrelevant to the landslide, the infiltration influence of the rainfall on loess tension cracks can be well reflected, the reference of the initial rainfall in the rainfall calculation stage on the excited shallow loess landslide is improved, and more accurate and effective data support is provided for the subsequent calculation of landslide early warning values, thereby improving the landslide early warning accuracy, and reducing the major loss and casualties caused by landslide.

2. According to the embodiment of the invention, the plurality of sensors are arranged on the tableland in the loess area, so that the rainfall monitoring elevation is consistent with the elevation of the landslide body catchment area.

3. According to the embodiment of the invention, whether the early rainfall which excites the shallow loess landslide is recalculated is judged by calculating the second rainfall intensity in each time period, and when the second rainfall intensity I is smaller than the critical value I, the second real-time rainfall total value is cleared, and the early rainfall is recalculated. Therefore, the calculated second real-time rainfall total value for exciting the shallow loess landslide is obtained by analyzing the rainfall process and the landslide possibility, and the method has a wider application range.

4. According to the embodiment of the invention, the rainfall segmentation method is not obtained based on the condition that a large amount of collapse and landslide occur in a strong earthquake area, so that the method is suitable for loess areas without earthquake influence or with small earthquake influence and in a long time period after the earthquake, and has wide applicability to measurement and calculation of early rainfall inducing the landslide. In addition, according to the embodiment, a plurality of sensors are arranged on the tableland according to the monitored landslide point, rainfall is monitored in real time through the sensors, the rainfall within 1-72h under the hourly condition is obtained, the judgment result of early rainfall for exciting the shallow loess landslide is obtained by comparing the rainfall critical value, the landslide misjudgment caused by less rainfall is greatly reduced, and the early warning accuracy is greatly improved.

5. According to the embodiment of the invention, the preset time is determined to be 72h according to the special geology of the loess area, the rainfall critical value is calculated by adopting 10% of the average rainfall in the local year, the rainfall critical value is used as the judgment reference for judging whether the second real-time rainfall total value is counted into the rainfall data for exciting the shallow loess landslide, the calculated rainfall data for exciting the shallow loess landslide not only comprises the influence of short-time strong rainfall, but also can not miss the middle rainfall but also can not be used for a long time, and is not limited to the rainfall process which can only be 72h, so that the interference of invalid rainfall for the duration of the landslide early warning is avoided, the early warning accuracy is greatly improved, and the occurrence of false early warning is reduced.

6. In the embodiment of the invention, when the rainfall partition is carried out, the rainfall for exciting the shallow loess landslide is divided into two processes: early rainfall (rainfall accumulation stage) + late rainfall (rainfall calculation stage). The early rainfall is at least 10% of the average rainfall of the local year, and in the late rainfall, the rainfall intensity critical value is used as the judgment reference of the end point of the late rainfall, so that the early rainfall belongs to a larger rainfall process in the rainfall data for exciting the shallow loess landslide, and the subsequent rainfall still needs to keep larger rainfall to belong to the rainfall data for exciting the loess landslide, thereby avoiding the condition that the rainfall data causes landslide early warning misjudgment when the rainfall is not large, reducing the occurrence of landslide early warning misjudgment, and greatly improving the accuracy of rainfall early warning landslide.

7. According to the embodiment of the invention, the rainfall critical value is calculated according to the average annual rainfall, and is used as the judgment reference of the rainfall starting point for exciting the shallow loess landslide, so that the interference conditions of evaporation of rainfall passing through an upper catchment area, absorption of the rainfall by loess soil and the like are eliminated, the obtained first rainfall data only comprises the condition that the rainfall seeps to deeper soil along a tension fracture channel and can continuously influence the landslide, the calculated landslide early warning value is more consistent with the geological condition and rainfall condition of the landslide body to be detected, and the early warning accuracy is improved.

8. According to the embodiment of the invention, the rainfall intensity critical value is calculated according to the average value of the rainfall intensity when the maximum and minimum of the year is adopted, the rainfall intensity critical value is used as the judgment reference of the rainfall end point of the shallow loess landslide excitation, and only when the rainfall intensity is greater than or equal to the rainfall intensity critical value, the rainfall data of the shallow loess landslide excitation can be continuously taken into account, so that the condition that the landslide is continuously influenced by continuous infiltration in the tension crack through evaporation, absorption by loess soil and the like under the condition of low rainfall intensity is eliminated, the reliability of the first rainfall data is improved, and the misjudgment rate of landslide early warning is reduced.

Example four:

referring to fig. 3, fig. 3 is a diagram illustrating a shallow loess landslide warning device according to an embodiment of the present invention. Wherein, the device includes:

the acquisition module 301 is used for acquiring topographic data of a landslide body to be detected in a loess region, wherein the topographic data comprises a landslide body gradient, a landslide body area and a catchment area on the upper side of the landslide body;

the first calculating module 302 is configured to calculate a terrain factor of the landslide body to be measured according to the terrain data;

a rainfall segmentation module 303 for obtaining real-time rainfall data of the loess area, performing rainfall segmentation on the real-time rainfall data to obtain first rainfall data for exciting shallow loess landslide,

the second calculation module 304 is used for calculating a landslide early warning value according to the terrain factor and the first rainfall data;

the early warning module 305 is configured to output an early warning signal according to a comparison result between the landslide early warning value and a preset landslide early warning critical value.

In one embodiment, the rainfall partitioning module 303 includes:

the first acquisition submodule is used for acquiring meteorological data of the loess area and determining a rainfall critical value and a rainfall intensity critical value according to the meteorological data;

the second acquisition submodule is used for acquiring and accumulating the real-time rainfall of the loess area to obtain a second real-time rainfall total value, and accumulating the acquisition time of the real-time rainfall to obtain a second rainfall duration;

the first judgment sub-module is used for judging whether the second rainfall duration is longer than a second preset duration or not when the second real-time rainfall total value reaches the rainfall critical value, and if not, triggering the second judgment sub-module; if so, clearing the second real-time rainfall total value and the second rainfall duration, and re-triggering the second acquisition submodule;

and the second judgment submodule is used for calculating second rainfall intensity according to the second rainfall duration and the second real-time rainfall total value, outputting the second real-time rainfall total value and the second rainfall duration as first rainfall data of the excitation of the shallow loess landslide when the second rainfall intensity is smaller than the rainfall intensity critical value, clearing the second real-time rainfall total value and the second rainfall duration, and re-triggering the second acquisition submodule.

In a specific embodiment, the second determining submodule is further configured to calculate a second rainfall intensity according to the second rainfall duration and the second total real-time rainfall, output the second total real-time rainfall and the second rainfall duration as the first rainfall data of the current excitation of the shallow loess landslide when the second rainfall intensity is smaller than the rainfall intensity critical value, clear the second total real-time rainfall and the second rainfall duration, and re-trigger the second acquiring submodule.

In a specific embodiment, the first calculation module 302 includes:

the first calculation submodule is used for calculating to obtain first rainfall intensity according to the first real-time rainfall total value and the first rainfall duration;

and the second calculation submodule is used for calculating a landslide early warning value according to the terrain factor, the first rainfall intensity and the first rainfall duration.

In a specific embodiment, the first obtaining sub-module further includes:

the third calculation submodule is used for calculating a rainfall critical value according to the annual average rainfall;

and the fourth calculation submodule is used for calculating the rainfall intensity critical value according to the average value of the rainfall intensity when the year is maximum and minimum.

In a particular embodiment, the early warning module 305 includes:

a first grade pre-warning module 305, configured to output a first grade pre-warning signal when the landslide pre-warning value is smaller than a first landslide pre-warning critical value;

a second grade pre-warning module 305, configured to output a second grade pre-warning signal when the landslide pre-warning value is greater than or equal to the first landslide pre-warning threshold value and is less than the second landslide pre-warning threshold value;

a third grade pre-warning module 305, configured to output a third grade pre-warning signal when the landslide pre-warning value is greater than or equal to the second landslide pre-warning threshold value and is less than a third landslide pre-warning threshold value;

and a fourth grade pre-warning module 305, configured to output a fourth grade pre-warning signal when the landslide pre-warning value is greater than or equal to the third landslide pre-warning threshold value.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated into one processing unit, or each functional unit may exist alone physically, or two or more functional units are integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.

Finally, it should also be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A shallow loess landslide early warning method is characterized by comprising the following steps:

calculating according to the terrain data to obtain a terrain factor of the landslide body to be detected;

2. The method of claim 1, wherein the obtaining of the real-time rainfall data of the loess area and the rainfall segmentation of the real-time rainfall data to obtain the first rainfall data for exciting the shallow loess landslide comprises:

s3: when the second real-time rainfall total value reaches a rainfall critical value, judging whether the duration of the second rainfall is greater than a second preset time, and if not, executing S4; if so, clearing the second real-time rainfall total value and the second rainfall duration, and executing S2 again;

s4: and calculating second rainfall intensity according to the second rainfall duration and the second real-time rainfall total value, outputting the second real-time rainfall total value and the second rainfall duration as first rainfall data of the excitation of the shallow loess landslide at this time when the second rainfall intensity is smaller than the rainfall intensity critical value, and then clearing the second real-time rainfall total value and the second rainfall duration and re-executing S2.

3. The method according to claim 2, wherein the step S4 further comprises:

4. The method of claim 1, wherein the first rainfall data comprises a first total amount of real-time rainfall and a first duration of rainfall, and wherein calculating a landslide warning value based on the terrain factor and the first rainfall data comprises:

Cr＝T(I/IM)(D/Dd) ^0.45

5. The method of claim 3, wherein the meteorological data comprises an average annual rainfall and an average annual maximum minimum rainfall; the step of determining a rainfall threshold value and a rainfall intensity threshold value according to the meteorological data comprises:

calculating a rainfall critical value according to the annual average rainfall;

6. The method of claim 5, wherein the rainfall threshold is calculated by the formula:

R*＝0.1RN

7. The method of claim 5, wherein the threshold rainfall intensity is calculated by the formula:

I*＝0.02IM

8. The method according to claim 1, wherein the calculation formula for calculating the terrain factor of the landslide body to be tested according to the terrain data is as follows:

T＝tana+1.25U＝(1+1.25Au/A)tana

9. The method of claim 1, wherein outputting an early warning signal according to the comparison result between the landslide early warning value and a preset landslide early warning threshold value comprises:

when the landslide early warning value is larger than or equal to the first landslide early warning critical value and smaller than the second landslide early warning critical value, outputting a second-level early warning signal;

and when the landslide early warning value is larger than or equal to a third landslide early warning critical value, outputting a fourth grade early warning signal.

10. The utility model provides a shallow loess landslide early warning device which characterized in that, the device includes:

the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring topographic data of a landslide body to be detected in a loess region, and the topographic data comprises a landslide body gradient, a landslide body area and a catchment area on the upper side of the landslide body;