CN111563621B - Method, system, device and storage medium for evaluating danger of regional landslide - Google Patents
Method, system, device and storage medium for evaluating danger of regional landslide Download PDFInfo
- Publication number
- CN111563621B CN111563621B CN202010361760.0A CN202010361760A CN111563621B CN 111563621 B CN111563621 B CN 111563621B CN 202010361760 A CN202010361760 A CN 202010361760A CN 111563621 B CN111563621 B CN 111563621B
- Authority
- CN
- China
- Prior art keywords
- landslide
- rainfall
- data
- research area
- occurrence probability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 107
- 238000011160 research Methods 0.000 claims abstract description 132
- 238000012502 risk assessment Methods 0.000 claims abstract description 42
- 230000008859 change Effects 0.000 claims abstract description 24
- 239000003673 groundwater Substances 0.000 claims abstract description 24
- 230000008595 infiltration Effects 0.000 claims abstract description 11
- 238000001764 infiltration Methods 0.000 claims abstract description 11
- 238000004088 simulation Methods 0.000 claims abstract description 11
- 238000004364 calculation method Methods 0.000 claims description 35
- 238000004458 analytical method Methods 0.000 claims description 17
- 238000012544 monitoring process Methods 0.000 claims description 17
- 238000005553 drilling Methods 0.000 claims description 15
- 238000005259 measurement Methods 0.000 claims description 13
- 238000007476 Maximum Likelihood Methods 0.000 claims description 10
- 239000002689 soil Substances 0.000 claims description 10
- 238000011835 investigation Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 7
- 230000001133 acceleration Effects 0.000 claims description 4
- 230000005484 gravity Effects 0.000 claims description 4
- 230000000877 morphologic effect Effects 0.000 claims description 3
- 239000011435 rock Substances 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 abstract description 21
- 230000015572 biosynthetic process Effects 0.000 abstract description 17
- 238000013058 risk prediction model Methods 0.000 abstract description 6
- 230000009471 action Effects 0.000 description 11
- 238000011156 evaluation Methods 0.000 description 6
- 230000002265 prevention Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000000342 Monte Carlo simulation Methods 0.000 description 4
- 238000011002 quantification Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 241000212384 Bifora Species 0.000 description 1
- 241000508725 Elymus repens Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000008239 natural water Substances 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
- G06Q50/265—Personal security, identity or safety
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Computer Security & Cryptography (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Pit Excavations, Shoring, Fill Or Stabilisation Of Slopes (AREA)
Abstract
The invention relates to a dangerous assessment method, a system, a device and a storage medium for regional landslide, which comprise the steps of obtaining regional basic data of a research region, and obtaining mechanical parameters and rainfall data according to the regional basic data; obtaining groundwater level change data at each moment in the whole rainfall period according to the mechanical parameters and rainfall data by adopting a regional rainfall infiltration numerical simulation method; analyzing the stability of the research area by adopting a limit balance method to obtain landslide occurrence probability and landslide intensity occurrence probability at each moment in a rainfall period; and establishing a dangerous computing formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the dangers of the research area according to the dangerous computing formula. According to the method, a risk prediction model based on a rainfall-induced landslide formation mechanism is established, quantitative expression of landslide intensity in landslide risk assessment is realized, and reliability of regional landslide disaster risk assessment is improved.
Description
Technical Field
The invention relates to the field of landslide risk prediction, in particular to a regional landslide risk assessment method, a regional landslide risk assessment system, a regional landslide risk assessment device and a storage medium.
Background
The landslide hazard risk assessment is the basis of landslide risk research, and is also an important means for realizing landslide hazard prediction and forecast and then making a prevention and control plan.
The existing landslide hazard prediction method generally considers geological landform conditions formed by disasters based on a mathematical model, establishes a statistical relationship model between rainfall and disaster events, further predicts the hazard of regional landslide, and the theoretical framework of the method belongs to the category of statistical prediction. However, the method not only needs a large amount of accurate historical landslide time and rainfall data, but also adopts basic data after landslide occurrence in evaluation and analysis, has strong dependence on historical data, does not fully consider the physical and mechanical mechanism of landslide occurrence, and has certain limitations on application and precision; in addition, the quantification degree of landslide hazard in the method is insufficient, which is unfavorable for specifying a corresponding prevention and control plan.
Disclosure of Invention
Aiming at the defects of the prior art, the technical problem to be solved by the invention is to provide a method, a system, a device and a storage medium for evaluating the risk of regional landslide, which are used for establishing a risk prediction model based on a rainfall-induced landslide formation mechanism, realizing quantitative expression of landslide action intensity in regional landslide disaster risk evaluation, improving the reliability of regional landslide disaster risk evaluation results and having good application prospects.
The technical scheme for solving the technical problems is as follows:
a method for risk assessment of regional landslide, comprising the steps of:
step 1: acquiring regional basic data of a research region, and acquiring mechanical parameters and rainfall data of the research region according to the regional basic data;
step 2: obtaining groundwater level change data of the research area at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method;
step 3: selecting any moment in the rainfall period, and analyzing the stability of the research area at the selected moment by adopting a limit balance method according to the mechanical parameter and the groundwater level change data at the selected moment to obtain the landslide occurrence probability of the research area at the selected moment and a plurality of landslide intensities corresponding to the landslide occurrence probability;
step 4: obtaining the landslide intensity occurrence probability corresponding to the landslide occurrence probability of the research area at one selected time according to the landslide occurrence probability at one selected time and all landslide intensities by adopting a maximum likelihood estimation method;
Step 5: traversing each moment in the rainfall period, and repeating the steps 3 to 4 to obtain landslide occurrence probability and landslide intensity occurrence probability corresponding to the landslide occurrence probability in each moment in the rainfall period;
step 6: establishing a dangerous computing formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the dangers of the research area according to the dangerous computing formula.
According to another aspect of the present invention, there is further provided a risk assessment system for a regional landslide, which is applied to the risk assessment method for a regional landslide in the present invention, including a data acquisition module, a data processing module, a stability analysis module, a probability estimation module, and a risk calculation module;
the data acquisition module is used for acquiring area basic data of a research area and acquiring mechanical parameters and rainfall data of the research area according to the area basic data;
the data processing module is used for obtaining groundwater level change data of the research area at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method;
The stability analysis module is used for selecting any moment in the rainfall period, adopting a limit balance method, and analyzing the stability of the research area at the selected moment according to the mechanical parameter and the groundwater level change data at the selected moment to obtain the landslide occurrence probability of the research area at the selected moment and a plurality of landslide intensities corresponding to the landslide occurrence probability;
the probability estimation module is used for obtaining the landslide intensity occurrence probability corresponding to the landslide occurrence probability of the research area at one selected time according to the landslide occurrence probability at one selected time and all landslide intensities by adopting a maximum likelihood estimation method; the method is also used for obtaining the landslide occurrence probability at each moment in the rainfall period and the landslide intensity occurrence probability corresponding to the landslide occurrence probability;
the risk calculation module is used for establishing a risk calculation formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the risk of the research area according to the risk calculation formula.
According to another aspect of the present invention there is provided a risk assessment apparatus for regional landslide comprising a processor, a memory and a computer program stored in the memory and operable on the processor, the computer program when run effecting the steps in a risk assessment method for regional landslide of the present invention.
According to another aspect of the present invention, there is provided a computer storage medium including: at least one instruction, when executed, implements the steps in a method for risk assessment of regional landslide of the invention.
The method, the system, the device and the storage medium for evaluating the risk of the regional landslide have the beneficial effects that: according to the obtained basic data of the research area, the mechanical parameters and rainfall data corresponding to the research area are obtained, then, a regional rainfall infiltration numerical simulation method is adopted, and the groundwater level change data at each moment in the whole rainfall period is obtained according to the mechanical parameters and the rainfall data, so that the dependence on historical data is greatly reduced in the traditional technology only depending on historical landslide data or data after landslide has occurred, the subsequent analysis is carried out based on the mechanical parameters, the physical and mechanical mechanism of landslide occurrence is fully considered, and the accuracy of risk assessment on the landslide of the research area is ensured; by analyzing the stability of a research area, the landslide occurrence probability and a plurality of landslide intensities corresponding to the landslide occurrence probability are obtained, then a landslide disaster risk calculation formula is established to calculate the risk, the problem that the landslide intensity quantification degree is insufficient in the existing landslide risk analysis is solved, the quantitative expression of the regional landslide disaster action intensity is promoted, the risk prediction model based on the rainfall-induced landslide formation mechanism is established, the quantitative expression of the landslide action intensity in regional landslide disaster risk assessment is realized, the reliability of the regional landslide disaster risk assessment result is improved, and the method can be used for regional risk assessment of all rainfall-type soil landslide and has strong operability and good application prospect.
Drawings
FIG. 1 is a flow chart of a method for risk assessment of regional landslide in accordance with a first embodiment of the present invention;
fig. 2 is a schematic flow chart of obtaining groundwater level change data at each moment in the first embodiment of the invention;
FIG. 3 is a schematic flow chart of the risk of obtaining a study area in accordance with the first embodiment of the present invention;
FIG. 4 is a flow chart of another method for risk assessment of regional landslide in accordance with the first embodiment of the present invention;
FIG. 5 is a schematic diagram of a risk assessment system for regional landslide in a second embodiment of the present invention;
fig. 6 is a schematic structural diagram of another system for risk assessment of regional landslide in the second embodiment of the invention.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
The present invention will be described below with reference to the accompanying drawings.
In a first embodiment, as shown in fig. 1, a method for evaluating risk of a regional landslide includes the following steps:
s1: acquiring regional basic data of a research region, and acquiring mechanical parameters and rainfall data of the research region according to the regional basic data;
s2: obtaining groundwater level change data of the research area at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method;
S3: selecting any moment in the rainfall period, and analyzing the stability of the research area at the selected moment by adopting a limit balance method according to the mechanical parameter and the groundwater level change data at the selected moment to obtain the landslide occurrence probability of the research area at the selected moment and a plurality of landslide intensities corresponding to the landslide occurrence probability;
s4: obtaining the landslide intensity occurrence probability corresponding to the landslide occurrence probability of the research area at one selected time according to the landslide occurrence probability at one selected time and all landslide intensities by adopting a maximum likelihood estimation method;
s5: traversing each moment in the rainfall period, and repeating S3 to S4 to obtain landslide occurrence probability and landslide intensity occurrence probability corresponding to the landslide occurrence probability in each moment in the rainfall period;
s6: establishing a dangerous computing formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the dangers of the research area according to the dangerous computing formula.
According to the obtained basic data of the research area, the mechanical parameters and rainfall data corresponding to the research area are obtained, then, a regional rainfall infiltration numerical simulation method is adopted, and the groundwater level change data at each moment in the whole rainfall period is obtained according to the mechanical parameters and the rainfall data, so that the dependence on historical data is greatly reduced in the traditional technology only depending on historical landslide data or data after landslide has occurred, the subsequent analysis is carried out based on the mechanical parameters, the physical and mechanical mechanism of landslide occurrence is fully considered, and the accuracy of risk assessment on the landslide of the research area is ensured; the stability of the research area is analyzed to obtain landslide occurrence probability and a plurality of landslide intensities corresponding to the landslide occurrence probability, and then a dangerous calculation formula of landslide disasters is established to calculate the harmfulness, so that the problem that the quantification degree of the landslide intensities is insufficient in the existing landslide dangerous analysis is solved, and the quantitative expression of the action intensity of the landslide disasters in the area is promoted;
According to the embodiment, the risk prediction model based on the rainfall-induced landslide formation mechanism is established, quantitative expression of landslide action intensity in regional landslide disaster risk assessment is realized, reliability of regional landslide disaster risk assessment results is improved, and the method can be used for regional risk assessment of all rainfall-induced landslide, is high in operability and has good application prospects.
Specifically, the specific operation steps of the regional rainfall infiltration numerical simulation method in the embodiment S2 are the prior art, and specific details are not described here again.
Preferably, the zone base data includes geological environment data, geomorphology data, and drilling measurement data, and also includes historical rainfall data and/or rainfall monitoring data.
Preferably, in S1, the specific step of obtaining the area base data includes:
acquiring the geological environment data and the historical rainfall data of the research area by using a big data acquisition method;
acquiring the morphological data of the research area by using a low-altitude photography method;
acquiring the drilling measurement data of the investigation region using a drilling investigation method;
and acquiring the rainfall monitoring data of the research area by using rainfall monitoring equipment.
The regional basic data comprising the geological environment data, the landform data, the drilling measurement data and the historical rainfall data and/or the rainfall monitoring data avoid the dependence on the historical landslide data or the data after landslide occurrence in the traditional technology, greatly reduce the dependence on the historical data, and facilitate the subsequent acquisition of the mechanical parameters and the rainfall data of a research area, thereby facilitating the establishment of a dangerous prediction model based on the rainfall-induced landslide formation mechanism from the consideration of the physical and mechanical mechanism of landslide occurrence.
Specifically, in geological environment data including geological map, topographic map, etc., the topographic form data is DEM (Digital Elevation Model) data, which mainly describes the spatial distribution of regional topographic form, and is formed by performing data acquisition (including sampling and measurement) through contour lines or similar stereo models and then performing data interpolation; the DEM is a virtual representation of the morphology of the landform, can derive information such as contour lines, gradient maps and the like, and can be overlapped with DOM or other thematic data for analysis application related to the landform; drilling measurements include overburden thickness and initial groundwater level, etc.; the rainfall monitoring data comprise real-time rainfall time, real-time rainfall intensity, real-time rainfall type and the like.
Preferably, in S1, the specific step of obtaining the mechanical parameters and the rainfall data of the investigation region comprises:
obtaining the rainfall data of the research area according to the historical rainfall data and/or the rainfall monitoring data; wherein the rainfall data comprises rainfall duration, rainfall intensity and rainfall pattern;
obtaining the mechanical parameters of the research area according to the geological environment data, the geomorphic data and the drilling measurement data; wherein the mechanical parameters comprise physical mechanical parameters and hydraulic parameters of the rock and soil mass.
The historical rainfall data and/or rainfall monitoring data are used for predicting the duration, the rainfall intensity and the rainfall type of the rainfall to be researched, so that data support is provided for a subsequent dangerous prediction model for establishing a rainfall-induced landslide formation mechanism according to mechanical parameters; the rainfall-induced landslide formation mechanism is closely related to the mechanical parameters of the research area, so that the landslide risk assessment model established based on the mechanical parameters is more reliable in the assessment of the landslide risk.
Specifically, the mechanical parameters comprise physical and mechanical parameters of a rock-soil body, wherein the physical and mechanical parameters of the rock-soil body comprise saturation weight, natural weight, shear strength (the shear strength depends on cohesive force and internal friction angle), thickness of a covering layer, dynamic friction coefficient and the like, and the hydraulic parameters comprise permeability coefficient, natural water content, saturated water content and the like; the rainfall rain types in the rainfall data comprise real-time rainfall difference rain types, historical extremum rainfall uniformity rain types and the like.
Preferably, as shown in fig. 2, S3 specifically includes:
s31: selecting any moment in the rainfall period according to the rainfall duration, taking the mechanical parameter as a random variable, and adopting a random method to obtain a plurality of random variable parameter values of the research area at a selected moment according to the random variable and groundwater level change data at the selected moment;
s32: calculating according to each random variable parameter value by adopting the limit balance method to obtain a stability coefficient corresponding to each random variable parameter value of the research area at a selected moment;
s33: calculating to obtain landslide occurrence probability of the research area at a selected moment according to all the stability coefficients, and calculating to obtain a plurality of landslide intensities of the research area corresponding to the landslide occurrence probability at the selected moment according to each stability coefficient;
the formula for calculating the landslide occurrence probability of the research area at the t-th moment is specifically as follows:
wherein P is fst For the probability of landslide occurrence of the study area at the t-th time, F st For the stability coefficient of the research area at the t-th time, N is the total number of the stability coefficients of the research area at the t-th time, M is the stability coefficient of the research area at the t-th time to satisfy F st The number is less than or equal to 1;
the formula for calculating the ith landslide intensity corresponding to the landslide occurrence probability of the research area at the t-th time is specifically as follows:
wherein I is i (t)Probability of occurrence of landslide P at t-th time for the study area fst Corresponding ith landslide intensity, F i (t) satisfying F for the study area at time t st Residual sliding force between sliding force and anti-sliding force corresponding to ith stability coefficient less than or equal to 1, g is gravity acceleration, h i 、f i 、m i (t) and alpha i Respectively, the research areas satisfy F at the t-th moment st The sliding height of the landslide, the sliding friction coefficient of the landslide, the mass of the sliding body and the slope of the landslide which are corresponding to the ith stability coefficient which is less than or equal to 1.
At time t, using mechanical parameters as random variables, adopting a random method to generate N random variable parameter values meeting probability distribution, and adopting a limit balance method to calculate N corresponding stability coefficients F st At the N stability factors F st In (1), F can be counted st Less than or equal to 1 (i.e. F st The number M is less than or equal to 1), and the stability coefficient of the research area at the t-th moment can be obtained to meet F st Probability of < 1, i.e.P (F) st Not more than 1); due to stability factor F st Is determined by anti-skid/anti-skid force if F st If the sliding force is smaller than 1, the sliding force is larger than the anti-sliding force, that is, the sliding slope is required to slide downwards, namely unstable, and F st Equal to 1 is in a limit equilibrium state, so that the stability factor of the investigation region at the t-th time satisfies F st The probability less than or equal to 1 is the landslide occurrence probability at the corresponding moment; due to F st Less than or equal to 1 (i.e. F st The number of less than or equal to 1) is M, so that corresponding landslide intensities with M different intensities can be generated under the occurrence probability of the landslide.
The landslide intensity refers to the energy released in the occurrence process of landslide event, and the visual expression form is the movement speed characteristic after the landslide is deformed and unstably, and mainly comprises the following steps: landslide movement speed, landslide movement distance, etc. From the angle of energy, if the change of the energy in the landslide body is not considered in the movement process of the landslide, the work of the rest sliding force is considered to be completely converted into the kinetic energy of the landslide body, and the released energy can be converted into the landslide body to overcome the work of the rest sliding force. Therefore, by the deduction of the formula, the quantitative relation between the landslide deformation motion characteristic and the residual sliding force of the landslide can be established.
According to the mechanical parameters and the groundwater level change data, the stability coefficient with higher accuracy can be conveniently obtained, the stability of a research area at a certain moment is further analyzed, and the landslide occurrence probability at a certain moment and the landslide intensity corresponding to each stability coefficient at the moment can be accurately judged based on the stability coefficient, wherein the landslide intensities are landslide intensity sets corresponding to the landslide occurrence probability; by calculating the landslide occurrence probability and the landslide intensities, a quantitative relation model between the landslide action intensity and the parameter sets of each internal and external environment influence factor of deformation instability is conveniently built later, so that the landslide risk is accurately estimated, and the reliability is high.
Specifically, in the embodiment S31, the shear strength (or cohesion and internal friction angle) of the mechanical parameters is taken as a random variable, and the random variable parameter value obtained by the random method including but not limited to the Monte Carlo method or the point estimation method is the shear strength parameter value; in the present embodiment S32, the limit balance method employed includes, but is not limited to, an infinite slope calculation method, a simplified Bishop method, a Janbu method, and a Sarma method; the specific operation steps of the random method and the limit balance method are all the prior art, and specific details are not repeated here.
Preferably, as shown in fig. 3, S6 specifically includes:
s61: selecting the maximum landslide occurrence probability of all landslide occurrence probabilities in the rainfall period, determining the landslide intensity occurrence probability corresponding to the maximum landslide occurrence probability as the maximum landslide intensity occurrence probability, and establishing the dangerous calculation formula according to the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability;
the dangerous computing formula specifically comprises the following steps:
H＝P fs max ×P Ipfs max ×P T ；
wherein H is the risk, P fsmax For the maximum landslide occurrence probability, P Ipfsmax P is the probability of occurrence of the maximum landslide intensity T For the occurrence probability of specific rainfall event obtained according to the rainfall data, the method satisfies the following conditions 
T rp A rainfall recurrence period in the rainfall data;
s62: and obtaining the dangers of the research area according to the danger calculation formula.
In the embodiment S4, since there are M landslide intensities with different intensities under the occurrence probability of a landslide at a certain moment, each landslide intensity has a corresponding occurrence probability under the occurrence probability of the landslide, and the probability of one of the most likely generated landslide intensities under the occurrence probability of the landslide can be obtained by the maximum likelihood estimation method, namely the occurrence probability of the landslide intensity; for example, a landslide generates 1000 cohesion and internal friction angles by probability distribution function, and 1000F are obtained st Suppose there are 400F' s st Less than or equal to 1, the landslide occurrence probability of the landslide is 400/1000=40%, and at the same time, the 400F are st In the case that there are 400 landslide intensities, and assuming that 100 landslide intensities are between 5 and 8, the most probable landslide intensity after occurrence of the landslide is between 5 and 8, the occurrence probability of the landslide is 100/400=25%, that is, the landslide has a probability of 40%, and the landslide has a probability of 25% after occurrence is between 5 and 8.
Through the maximum likelihood estimation method of S4, the probability of landslide generation (namely landslide occurrence probability) at each moment and the probability of the most likely landslide intensity after landslide generation (landslide intensity occurrence probability) can be obtained, so that the subsequent quantitative expression and accurate assessment of the risk based on the landslide intensity are facilitated. The specific operation steps of the maximum likelihood estimation method are in the prior art, and specific details are not described herein.
The landslide hazard is the possibility of occurrence of a landslide of a certain scale in a certain time period of a certain area, is a comprehensive concept of space position, landslide scale, sliding speed and occurrence frequency, so that the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability of the maximum landslide occurrence probability are found out according to all the landslide occurrence probabilities and all the landslide intensity occurrence probabilities, and then a hazard calculation formula based on the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability is adopted, so that factors such as the landslide space probability, the time probability and the intensity probability can be comprehensively considered, the hazard of landslide disasters is comprehensively evaluated from the landslide formation mechanism, the reliability of hazard evaluation is greatly improved, the actual situation of landslide formation is more met, the method is applicable to regional hazard evaluation of all rainfall type soil landslide, and the method has strong operability and good application prospect.
Specifically, in the present embodiment, the risk calculation formula includes the spatial probability of landslide (i.e., the maximum landslide occurrence probability P fsmax ) Time probability (i.e. probability of occurrence of a particular rainfall event P T ) Intensity probability (i.e. maximum landslide intensity occurrence probability P Ipfsmax )；
1) For time probability (i.e. probability of occurrence of a particular rainfall event P T ) The calculation process is described as follows:
specific rainfall events consider two cases: the actual rainfall is the extreme rainfall. For actual rainfall, according to the actual hour rainfall calculation, the occurrence probability P of the actual rainfall is considered T 1 is shown in the specification; for extreme rainfall, in regional landslide hazard risk research, regional rainfall is generally calculated according to various statistical analysis methods, namely, a certain probability distribution model is utilized to calculate any rainfall recurrence period T in a research area rp And predicting the rainfall extremum in the water. The probability distribution model for calculating rainfall extremum mainly comprises the following steps: (1) pearson (Pearson) type iii distribution; (2) logarithmic P-III type distribution; (3) a log-normal distribution; (4) generalized extremum distribution (GEV); (5) geng Beier (gummel) distribution, etc. In the embodiment, a Gumbel distribution function is adopted to calculate rainfall extremum.
2) For the spatial probability of landslide (i.e. the maximum probability of occurrence of landslide P fsmax ) Calculation ofThe process is described as follows:
the probability of a landslide occurring at a certain location can be understood as the probability of the landslide being unstable under certain external conditions and for a period of time. Since landslide stability conditions are governed by a variety of factors or variables that have uncertainty, randomness, a functional model can be constructed using these random variables to describe its stability state. The Monte Carlo simulation method is adopted to calculate the space probability of landslide occurrence, and the concrete calculation method is introduced as follows:
selecting landslide body cohesive force and internal friction angle as random variables, selecting adaptive probability distribution, generating N groups of random numbers conforming to parameter variable probability distribution by using Monte Carlo method, and calculating by using limit balance method to obtain N stability results. When N is sufficiently large, the frequency at this time is approximate to the probability as known by the law of large numbers, and if M of the N stability results are less than or equal to 1, the probability of landslide occurrence can be obtained:
3) For intensity probability (i.e. maximum landslide intensity occurrence probability P Ipfsmax ) The calculation process is described as follows:
the landslide intensity is a quantitative depiction of the energy release capacity of the landslide after the occurrence of the landslide, M unstable results obtained by the Monte Carlo method are calculated, the landslide intensities corresponding to M landslide events are calculated respectively through an established landslide intensity calculation formula, and then the probability of occurrence of the landslide intensity when the landslide is most likely to occur is calculated and obtained through a maximum likelihood estimation method.
Preferably, as shown in fig. 4, the method further comprises the steps of:
s7: and establishing a landslide hazard classification standard table, and inquiring the landslide hazard classification standard table according to the hazard of the research area to obtain the hazard class of the research area.
Through the established landslide hazard classification standard table, the hazard level corresponding to the hazard is conveniently inquired, the hazard degree of landslide hazard can be more intuitively and clearly known, and the corresponding prevention and control plan can be conveniently and accurately adopted for prevention and control in time.
Preferably, in S7, the specific implementation of establishing the landslide risk classification standard table is as follows:
according to the preset dangerous threshold ranges of the preset quantity, establishing dangerous levels corresponding to the preset dangerous threshold ranges one by one, and according to all the preset dangerous threshold ranges and all the dangerous levels, establishing the landslide dangerous classification standard table.
The risk levels of different degrees are conveniently divided by selecting the preset risk threshold ranges of the preset quantity, so that corresponding risk levels can be conveniently and accurately inquired in the landslide risk classification standard table according to the risk calculated in the step S6.
Specifically, in this embodiment, the preset number is 5, and the corresponding 5 preset risk threshold ranges are respectively: [0,0.15], (0,0.35 ], (0.35,0.55 ], (0.55,0.75) and (0.75,1 ], the risk grades comprise 5 grades, which are respectively high risk, moderate risk, low risk and low risk, so that the corresponding relationship between the preset risk threshold range and the risk grade in the landslide risk classification standard table is as follows:
(1) H is E [0,0.15], and the danger grade of landslide disasters is low danger;
(2) h epsilon (0,0.35), the danger grade of landslide hazard is lower danger;
(3) h epsilon (0.35,0.55), wherein the danger grade of landslide hazard is moderate danger;
(4) h epsilon (0.55,0.75), the dangerous grade of landslide hazard is higher danger;
(5) h epsilon (0.75,1), the dangerous grade of landslide hazard is high dangerous.
In a second embodiment, as shown in fig. 5, a risk assessment system for a regional landslide is applied to the risk assessment method for a regional landslide in the first embodiment, and includes a data acquisition module, a data processing module, a stability analysis module, a probability estimation module and a risk calculation module;
the data acquisition module is used for acquiring area basic data of a research area and acquiring mechanical parameters and rainfall data of the research area according to the area basic data;
the data processing module is used for obtaining groundwater level change data of the research area at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method;
the stability analysis module is used for selecting any moment in the rainfall period, adopting a limit balance method, and analyzing the stability of the research area at the selected moment according to the mechanical parameter and the groundwater level change data at the selected moment to obtain the landslide occurrence probability of the research area at the selected moment and a plurality of landslide intensities corresponding to the landslide occurrence probability;
The probability estimation module is used for obtaining the landslide intensity occurrence probability corresponding to the landslide occurrence probability of the research area at one selected time according to the landslide occurrence probability at one selected time and all landslide intensities by adopting a maximum likelihood estimation method; the method is also used for obtaining the landslide occurrence probability at each moment in the rainfall period and the landslide intensity occurrence probability corresponding to the landslide occurrence probability;
the risk calculation module is used for establishing a risk calculation formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the risk of the research area according to the risk calculation formula.
According to the regional landslide risk assessment system, the data acquisition module is used for acquiring mechanical parameters and rainfall data corresponding to a research region according to the acquired basic data of the research region, then the data processing module is used for acquiring groundwater level change data at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method, on one hand, the situation that the traditional technology only depends on historical landslide data or data after landslide occurrence is avoided, the dependency on the historical data is greatly reduced, on the other hand, the subsequent analysis is carried out based on the mechanical parameters, the physical and mechanical mechanism of landslide occurrence is fully considered, and the risk assessment precision of the landslide of the research region is ensured; the stability analysis module is used for analyzing the stability of a research area to obtain landslide occurrence probability and a plurality of landslide intensities corresponding to the landslide occurrence probability, then a probability estimation module and a risk calculation module are used for establishing a risk calculation formula of landslide disasters to calculate the risk, the problem that the quantification degree of the landslide intensities in the existing landslide risk analysis is insufficient is solved, the quantitative expression of the action intensity of the regional landslide disasters is promoted, the risk prediction model based on a rainfall-induced landslide formation mechanism is established, the quantitative expression of the action intensity of the regional landslide disasters in the regional landslide disaster risk assessment is realized, the reliability of the regional landslide disaster risk assessment result is improved, and the method can be used for regional risk assessment of all rainfall-type soil landslide and has strong operability and good application prospect.
Preferably, the zone base data includes geological environment data, geomorphic data and drilling measurement data, and also includes historical rainfall data and/or rainfall monitoring data;
the data acquisition module is specifically configured to:
acquiring the geological environment data and the historical rainfall data of the research area by using a big data acquisition method;
acquiring the morphological data of the research area by using a low-altitude photography method;
acquiring the drilling measurement data of the investigation region using a drilling investigation method;
and acquiring the rainfall monitoring data of the research area by using rainfall monitoring equipment.
The regional basic data comprising the geological environment data, the landform data, the drilling measurement data and the historical rainfall data and/or the rainfall monitoring data avoid the dependence on the historical landslide data or the data after landslide occurrence in the traditional technology, greatly reduce the dependence on the historical data, and facilitate the subsequent acquisition of the mechanical parameters and the rainfall data of a research area, thereby facilitating the establishment of a dangerous prediction model based on the rainfall-induced landslide formation mechanism from the consideration of the physical and mechanical mechanism of landslide occurrence.
Preferably, the data acquisition module is further specifically configured to:
Obtaining the rainfall data of the research area according to the historical rainfall data and/or the rainfall monitoring data; wherein the rainfall data comprises rainfall duration, rainfall intensity and rainfall pattern;
obtaining the mechanical parameters of the research area according to the geological environment data, the geomorphic data and the drilling measurement data; wherein the mechanical parameters comprise physical mechanical parameters and hydraulic parameters of the rock and soil mass.
The historical rainfall data and/or the rainfall monitoring data are used for conveniently predicting the rainfall duration, the rainfall intensity and the rainfall type of the research, and providing data support for a subsequent stability analysis module to establish a risk prediction model of a rainfall-induced landslide formation mechanism according to mechanical parameters; the rainfall-induced landslide formation mechanism is closely related to the mechanical parameters of the research area, so that the landslide risk assessment model established based on the mechanical parameters is more reliable in the assessment of the landslide risk.
Preferably, the stability analysis module is specifically configured to:
selecting any moment in the rainfall period according to the rainfall duration, taking the mechanical parameter as a random variable, and adopting a random method to obtain a plurality of random variable parameter values of the research area at a selected moment according to the random variable and groundwater level change data at the selected moment;
Calculating according to each random variable parameter value by adopting the limit balance method to obtain a stability coefficient corresponding to each random variable parameter value of the research area at a selected moment;
calculating to obtain landslide occurrence probability of the research area at a selected moment according to all the stability coefficients, and calculating to obtain a plurality of landslide intensities of the research area corresponding to the landslide occurrence probability at the selected moment according to each stability coefficient;
the formula for calculating the landslide occurrence probability of the research area at the t-th moment is specifically as follows:
wherein P is fst For the probability of landslide occurrence of the study area at the t-th time, F st For the stability coefficient of the research area at the t-th time, N is the total number of the stability coefficients of the research area at the t-th time, M is the stability coefficient of the research area at the t-th time to satisfy F st The number is less than or equal to 1;
the formula for calculating the ith landslide intensity corresponding to the landslide occurrence probability of the research area at the t-th time is specifically as follows:
wherein I is i (t) probability of occurrence of landslide P at t-th time for the study area fst Corresponding ith landslide intensity, F i (t) satisfying F for the study area at time t st Residual sliding force between sliding force and anti-sliding force corresponding to ith stability coefficient less than or equal to 1, g is gravity acceleration, h i 、f i 、m i (t) and alpha i Respectively, the research areas satisfy F at the t-th moment st The sliding height of the landslide, the sliding friction coefficient of the landslide, the mass of the sliding body and the slope of the landslide which are corresponding to the ith stability coefficient which is less than or equal to 1.
The stability analysis module can conveniently obtain stability coefficients with higher accuracy according to the mechanical parameters and the groundwater level change data, so that the stability of a research area at a certain moment is analyzed, and the landslide occurrence probability at the certain moment and the landslide intensity corresponding to each stability coefficient at the moment can be accurately judged based on the stability coefficients, wherein the landslide intensities are landslide intensity sets corresponding to the landslide occurrence probability; by calculating the landslide occurrence probability and the landslide intensities, a quantitative relation model between the landslide action intensity and the parameter sets of each internal and external environment influence factor of deformation instability is conveniently built later, so that the landslide risk is accurately estimated, and the reliability is high.
Preferably, the risk calculation module is specifically configured to:
selecting the maximum landslide occurrence probability of all landslide occurrence probabilities in the rainfall period, determining the landslide intensity occurrence probability corresponding to the maximum landslide occurrence probability as the maximum landslide intensity occurrence probability, and establishing the dangerous calculation formula according to the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability;
The dangerous computing formula specifically comprises the following steps:
H＝P fs max ×P Ipfs max ×P T ；
wherein H is the risk, P fsmax For the maximum landslide occurrence probability, P Ipfsmax For maximum landslide intensity occurrence probability, P T For the occurrence probability of specific rainfall event obtained according to the rainfall data, the method satisfies the following conditions
T rp A rainfall recurrence period in the rainfall data;
and obtaining the dangers of the research area according to the danger calculation formula.
According to the risk calculation module, the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability are found out according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities, and then the risk calculation formula based on the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability is adopted, so that the factors such as the landslide space probability, the time probability and the intensity probability can be comprehensively considered, the risk of landslide disasters can be comprehensively evaluated from a landslide formation mechanism, the reliability of risk evaluation is greatly improved, the actual situation of landslide formation is more met, the regional risk assessment method is applicable to regional risk assessment of all rainfall soil landslide, the operability is strong, and good application prospects are realized.
Preferably, as shown in fig. 6, the system further comprises a risk level query module;
The risk level inquiry module is used for establishing a landslide risk classification standard table, inquiring the landslide risk classification standard table according to the risk of the research area, and obtaining the risk level of the research area.
The landslide hazard classification standard table established by the hazard level inquiry module is convenient for inquiring the hazard level corresponding to the hazard, can more intuitively and clearly know the hazard level of landslide hazard, and is convenient for timely and accurately adopting the corresponding prevention and control plan for prevention and control.
Preferably, the risk level query module is specifically configured to:
according to the preset dangerous threshold ranges of the preset quantity, establishing dangerous levels corresponding to the preset dangerous threshold ranges one by one, and according to all the preset dangerous threshold ranges and all the dangerous levels, establishing the landslide dangerous classification standard table.
When the risk level inquiry module establishes the landslide risk classification standard table, the risk levels of different degrees can be conveniently divided by selecting the preset risk threshold range of the preset quantity, so that the corresponding risk levels can be accurately inquired in the landslide risk classification standard table according to the risk calculated by the risk calculation module.
The third embodiment, based on the first embodiment and the second embodiment, further discloses a risk assessment device for a regional landslide, which comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program realizes the specific steps S1 to S6 shown in fig. 1 when running.
The method realizes the regional landslide hazard assessment by the computer program stored in the memory and running on the processor, reduces the dependence on historical data, establishes a hazard prediction model based on a rainfall-induced landslide formation mechanism, realizes the quantitative expression of landslide action intensity in regional landslide hazard assessment, greatly improves the reliability of regional landslide hazard assessment results, can be used for regional hazard assessment of all rainfall-induced landslide, has strong operability and good application prospect.
The present embodiment also provides a computer storage medium having at least one instruction stored thereon, which when executed, implements the specific steps of S1 to S6.
By executing the computer storage medium containing at least one instruction, the regional landslide hazard assessment method provided by the invention has the advantages that the dependence on historical data is reduced, the hazard prediction model based on the rainfall-induced landslide formation mechanism is established, the quantitative expression of the landslide action intensity in the regional landslide hazard assessment is realized, the reliability of the regional landslide hazard assessment result is greatly improved, the regional landslide hazard assessment method can be used for regional hazard assessment of all rainfall-induced soil landslide, the operability is strong, and the application prospect is good.
In this embodiment, details of S1 to S6 are not fully described in the first embodiment and the detailed descriptions of fig. 1 to 4, and are not repeated here.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (9)
1. A method for assessing the risk of a regional landslide, comprising the steps of:
step 1: acquiring regional basic data of a research area, and acquiring mechanical parameters and rainfall data of the research area according to the regional basic data, wherein the rainfall data comprises rainfall duration;
step 2: obtaining groundwater level change data of the research area at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method;
step 3: selecting any moment in the rainfall period, and analyzing the stability of the research area at the selected moment by adopting a limit balance method according to the mechanical parameter and the groundwater level change data at the selected moment to obtain the landslide occurrence probability of the research area at the selected moment and a plurality of landslide intensities corresponding to the landslide occurrence probability;
Step 4: obtaining the landslide intensity occurrence probability corresponding to the landslide occurrence probability of the research area at one selected time according to the landslide occurrence probability at one selected time and all landslide intensities by adopting a maximum likelihood estimation method;
step 5: traversing each moment in the rainfall period, and repeating the steps 3 to 4 to obtain landslide occurrence probability and landslide intensity occurrence probability corresponding to the landslide occurrence probability in each moment in the rainfall period;
step 6: establishing a dangerous computing formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the dangers of the research area according to the dangerous computing formula;
wherein, the step 3 specifically includes:
step 31: selecting any moment in the rainfall period according to the rainfall duration, taking the mechanical parameter as a random variable, and adopting a random method to obtain a plurality of random variable parameter values of the research area at a selected moment according to the random variable and groundwater level change data at the selected moment;
step 32: calculating according to each random variable parameter value by adopting the limit balance method to obtain a stability coefficient corresponding to each random variable parameter value of the research area at a selected moment;
Step 33: calculating to obtain landslide occurrence probability of the research area at a selected moment according to all the stability coefficients, and calculating to obtain a plurality of landslide intensities of the research area corresponding to the landslide occurrence probability at the selected moment according to each stability coefficient;
the formula for calculating the landslide occurrence probability of the research area at the t-th moment is specifically as follows:
wherein P is fst For the probability of landslide occurrence of the study area at the t-th time, F st For the stability coefficient of the research area at the t-th time, N is the total number of the stability coefficients of the research area at the t-th time, M is the stability coefficient of the research area at the t-th time to satisfy F st The number is less than or equal to 1;
the formula for calculating the ith landslide intensity corresponding to the landslide occurrence probability of the research area at the t-th time is specifically as follows:
wherein I is i (t) probability of occurrence of landslide P at t-th time for the study area fst Corresponding ith landslide intensity, F i (t) satisfying F for the study area at time t st Residual sliding force between sliding force and anti-sliding force corresponding to ith stability coefficient less than or equal to 1, g is gravity acceleration, h i 、f i 、m i (t) and alpha i Respectively, the research areas satisfy F at the t-th moment st The sliding height of the landslide, the sliding friction coefficient of the landslide, the mass of the sliding body and the slope of the landslide which are corresponding to the ith stability coefficient which is less than or equal to 1.
2. The regional landslide hazard assessment method of claim 1 wherein the regional base data comprises geologic environment data, topographical morphology data, and drilling measurement data, further comprising historical rainfall data and/or rainfall monitoring data;
in the step 1, the specific step of obtaining the region basic data includes:
acquiring the geological environment data and the historical rainfall data of the research area by using a big data acquisition method;
acquiring the morphological data of the research area by using a low-altitude photography method;
acquiring the drilling measurement data of the investigation region using a drilling investigation method;
and acquiring the rainfall monitoring data of the research area by using rainfall monitoring equipment.
3. The method for evaluating the risk of a regional landslide according to claim 2, wherein in the step 1, the specific step of obtaining the mechanical parameters and the rainfall data of the investigation region includes:
obtaining the rainfall data of the research area according to the historical rainfall data and/or the rainfall monitoring data; wherein the rainfall data comprises rainfall duration, rainfall intensity and rainfall pattern;
Obtaining the mechanical parameters of the research area according to the geological environment data, the geomorphic data and the drilling measurement data; wherein the mechanical parameters comprise physical mechanical parameters and hydraulic parameters of the rock and soil mass.
4. The method for assessing the risk of a regional landslide of claim 1, wherein said step 6 comprises:
step 61: selecting the maximum landslide occurrence probability of all landslide occurrence probabilities in the rainfall period, determining the landslide intensity occurrence probability corresponding to the maximum landslide occurrence probability as the maximum landslide intensity occurrence probability, and establishing the dangerous calculation formula according to the maximum landslide occurrence probability and the maximum landslide intensity occurrence probability;
the dangerous computing formula specifically comprises the following steps:
H＝P fsmax ×P Ipfsmax ×P T ；
wherein H is the risk, P fsmax For the maximum slipProbability of occurrence of slope, P Ipfsmax P is the probability of occurrence of the maximum landslide intensity T For the occurrence probability of specific rainfall event obtained according to the rainfall data, the method satisfies the following conditions
T rp A rainfall recurrence period in the rainfall data;
step 62: and obtaining the dangers of the research area according to the danger calculation formula.
5. The risk assessment method for regional landslide of any one of claims 1 to 4 further comprising the steps of:
Step 7: and establishing a landslide hazard classification standard table, and inquiring the landslide hazard classification standard table according to the hazard of the research area to obtain the hazard class of the research area.
6. The method for evaluating the risk of a regional landslide of claim 5, wherein in step 7, the step of creating the landslide risk classification criterion table is implemented as follows:
according to the preset dangerous threshold ranges of the preset quantity, establishing dangerous levels corresponding to the preset dangerous threshold ranges one by one, and according to all the preset dangerous threshold ranges and all the dangerous levels, establishing the landslide dangerous classification standard table.
7. A risk assessment system for regional landslide, which is characterized by being applied to the risk assessment method for regional landslide according to any one of claims 1 to 6, and comprising a data acquisition module, a data processing module, a stability analysis module, a probability estimation module and a risk calculation module;
the data acquisition module is used for acquiring area basic data of a research area, and acquiring mechanical parameters and rainfall data of the research area according to the area basic data, wherein the rainfall data comprises rainfall duration;
The data processing module is used for obtaining groundwater level change data of the research area at each moment in the whole rainfall period according to the mechanical parameters and the rainfall data by adopting a regional rainfall infiltration numerical simulation method;
the stability analysis module is used for selecting any moment in the rainfall period, adopting a limit balance method, and analyzing the stability of the research area at the selected moment according to the mechanical parameter and the groundwater level change data at the selected moment to obtain the landslide occurrence probability of the research area at the selected moment and a plurality of landslide intensities corresponding to the landslide occurrence probability;
the probability estimation module is used for obtaining the landslide intensity occurrence probability corresponding to the landslide occurrence probability of the research area at one selected time according to the landslide occurrence probability at one selected time and all landslide intensities by adopting a maximum likelihood estimation method; the method is also used for obtaining the landslide occurrence probability at each moment in the rainfall period and the landslide intensity occurrence probability corresponding to the landslide occurrence probability;
the risk calculation module is used for establishing a risk calculation formula of landslide disasters according to all landslide occurrence probabilities and all landslide intensity occurrence probabilities in the rainfall period, and obtaining the risk of the research area according to the risk calculation formula;
The stability analysis module is specifically configured to:
selecting any moment in the rainfall period according to the rainfall duration, taking the mechanical parameter as a random variable, and adopting a random method to obtain a plurality of random variable parameter values of the research area at a selected moment according to the random variable and groundwater level change data at the selected moment;
calculating according to each random variable parameter value by adopting the limit balance method to obtain a stability coefficient corresponding to each random variable parameter value of the research area at a selected moment;
calculating to obtain landslide occurrence probability of the research area at a selected moment according to all the stability coefficients, and calculating to obtain a plurality of landslide intensities of the research area corresponding to the landslide occurrence probability at the selected moment according to each stability coefficient;
the formula for calculating the landslide occurrence probability of the research area at the t-th moment is specifically as follows:
wherein P is fst For the probability of landslide occurrence of the study area at the t-th time, F st For the stability coefficient of the research area at the t-th time, N is the total number of the stability coefficients of the research area at the t-th time, M is the stability coefficient of the research area at the t-th time to satisfy F st The number is less than or equal to 1;
the formula for calculating the ith landslide intensity corresponding to the landslide occurrence probability of the research area at the t-th time is specifically as follows:
wherein I is i (t) probability of occurrence of landslide P at t-th time for the study area fst Corresponding ith landslide intensity, F i (t) satisfying F for the study area at time t st Residual sliding force between sliding force and anti-sliding force corresponding to ith stability coefficient less than or equal to 1, g is gravity acceleration, h i 、f i 、m i (t) and alpha i Respectively, the research areas satisfy F at the t-th moment st The sliding height of the landslide, the sliding friction coefficient of the landslide, the mass of the sliding body and the slope of the landslide which are corresponding to the ith stability coefficient which is less than or equal to 1.
8. A risk assessment device for a regional landslide, comprising a processor, a memory and a computer program stored in the memory and executable on the processor, the computer program when run implementing the method steps of any one of claims 1 to 6.
9. A computer storage medium, the computer storage medium comprising: at least one instruction which, when executed, implements the method steps of any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010361760.0A CN111563621B (en) | 2020-04-30 | 2020-04-30 | Method, system, device and storage medium for evaluating danger of regional landslide |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010361760.0A CN111563621B (en) | 2020-04-30 | 2020-04-30 | Method, system, device and storage medium for evaluating danger of regional landslide |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111563621A CN111563621A (en) | 2020-08-21 |
| CN111563621B true CN111563621B (en) | 2023-05-30 |
Family
ID=72070765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010361760.0A Active CN111563621B (en) | 2020-04-30 | 2020-04-30 | Method, system, device and storage medium for evaluating danger of regional landslide |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111563621B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112907073B (en) * | 2021-02-20 | 2021-08-13 | 北方工业大学 | Rainstorm induced muck landslide risk identification method and system |
| CN113326756B (en) * | 2021-05-25 | 2023-05-16 | 中国地质调查局武汉地质调查中心 | Reservoir potential landslide hidden danger identification method based on rock mass degradation characteristics |
| CN113536659B (en) * | 2021-06-09 | 2022-11-04 | 上海交通大学 | Method, system and storage medium for rapidly predicting post-earthquake road disaster area |
| CN113780741B (en) * | 2021-08-11 | 2024-01-23 | 中国地质调查局武汉地质调查中心 | Landslide risk evaluation method, system and storage medium based on slope characteristics |
| CN113469587A (en) * | 2021-09-03 | 2021-10-01 | 南京信息工程大学 | Method and device for evaluating space-time influence of climate change on regional landslide |
| CN114123169A (en) * | 2021-11-12 | 2022-03-01 | 国家电网有限公司 | Power distribution network fault recovery method based on energy storage type flexible switch |
| CN114236095B (en) * | 2021-12-02 | 2024-03-19 | 山东高速集团四川乐宜公路有限公司 | Regional grading early warning method for rainfall induced landslide along mountain expressway |
| CN115345511B (en) * | 2022-08-29 | 2023-06-06 | 中咨数据有限公司 | Dynamic evaluation method, evaluation system and equipment for road corridor landslide hazard |
| CN116108759B (en) * | 2023-04-11 | 2023-06-30 | 湖北省地质环境总站 | Landslide hazard evaluation method based on characteristic coupling |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003281664A (en) * | 2002-03-26 | 2003-10-03 | Fujitsu Ltd | Disaster occurrence prediction method and disaster occurrence prediction device |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004060311A (en) * | 2002-07-30 | 2004-02-26 | Pasuko:Kk | Landslide monitoring method and system |
| JP2006195650A (en) * | 2005-01-12 | 2006-07-27 | Chuo Kaihatsu Kk | Slope collapse monitoring/prediction system |
| CN101630347A (en) * | 2009-08-20 | 2010-01-20 | 同济大学 | Mountainous area highway landslide risk evaluation model |
| CN103150871B (en) * | 2013-01-31 | 2015-08-05 | 青岛理工大学 | Utilize the Prediction of Landslide of underground water table and real-time displacement monitoring |
| CN109785584A (en) * | 2019-01-29 | 2019-05-21 | 青岛理工大学 | Compound hydrodynamic force reservoir stability stability prediction method |
-
2020
- 2020-04-30 CN CN202010361760.0A patent/CN111563621B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003281664A (en) * | 2002-03-26 | 2003-10-03 | Fujitsu Ltd | Disaster occurrence prediction method and disaster occurrence prediction device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111563621A (en) | 2020-08-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111563621B (en) | Method, system, device and storage medium for evaluating danger of regional landslide | |
| KR101843007B1 (en) | Wireless sensor network measurring system and method for forcasting landslide | |
| KR102242977B1 (en) | Early warning method and system for landslide integrated with weather forecasting information | |
| Gao | Impact of sampling intervals on the reliability of topographic variables mapped from grid DEMs at a micro-scale | |
| Pradhan et al. | Application and comparison of shallow landslide susceptibility models in weathered granite soil under extreme rainfall events | |
| Vaezi et al. | Spatial variability of soil erodibility factor (K) of the USLE in North West of Iran | |
| CN113283802A (en) | Landslide risk assessment method for complex and difficult mountain area | |
| CN112200478B (en) | Method and system for processing frost heaving risk information of cohesive soil field | |
| CN112686522A (en) | Newmark correction model earthquake landslide risk assessment method | |
| CN113780741B (en) | Landslide risk evaluation method, system and storage medium based on slope characteristics | |
| JP2019085712A (en) | Slope stability determination assistance system | |
| CN113720639B (en) | Method for investigating and supplementing sampling of polluted site | |
| CN115100819A (en) | Landslide hazard early warning method and device based on big data analysis and electronic equipment | |
| CN117057508A (en) | Mountain torrent mud-rock flow disaster risk identification method, device, terminal and medium | |
| CN116863651A (en) | Landslide weather early warning method based on rainfall event early warning response dynamic optimization | |
| Salah | Geostatistical analysis of groundwater levels in the south Al Jabal Al Akhdar area using GIS | |
| Ji et al. | A GIS-based tool for probabilistic physical modelling and prediction of landslides: improved GIS-TRIGRS-FORM landslide prediction | |
| CN113175949A (en) | Method and system for inverting water release coefficient by combining surface deformation and water level information | |
| CN107015289A (en) | Trap evaluation stock number determines method and device | |
| Mohanty et al. | Pedotransfer functions for estimating water content at field capacity and wilting point of Indian soils using particle size distribution and bulk density | |
| Huang et al. | Multi-factor building deformation analysis and prediction model based on multi-source date | |
| CN110909467A (en) | Three-dimensional soil field water capacity prediction method and system | |
| RASKAR-PHULE et al. | Spatial Variability mapping of N-Value of soils of Mumbai City using ARCGIS | |
| Ulmer et al. | Optimum grid spacing for simplified performance-based liquefaction and lateral spread displacement parameter maps | |
| Lizárraga et al. | Flowslide Triggering in Volcanic Soils: Role of Stratigraphy and Bedrock Exfiltration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |