CN117409876A - Numerical simulation method of landslide solid-liquid two-phase mixture under extreme climate condition - Google Patents
Numerical simulation method of landslide solid-liquid two-phase mixture under extreme climate condition Download PDFInfo
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Abstract
The invention relates to a numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climate conditions, which simultaneously considers two conditions of early rainfall and short-time extreme rainfall to calculate the surface runoff, and calculates the landslide solid-liquid two-phase mixtureThe assessment is a beneficial supplement. The method comprises the following steps: obtaining a digital elevation model of a landslide body, a soil type, a surface vegetation type, a daily rainfall in a time range of 1 month before landslide occurrence, a daily temperature value, a daily evapotranspiration value and an extreme rainfall value pe for inducing landslide occurrence; calculating a front rainfall infiltration value qa of landslide occurrence and calculating an underground water level ha caused by front rainfall; according to r=ci 3 T c 2 Calculating a surface diameter value R under the combined condition of a early rainfall infiltration value qa of landslide occurrence and an extreme rainfall value pe of landslide occurrence induction; and inputting the surface diameter value R as clear water flow data into FLO-2D software to obtain the flow speed of the landslide solid-liquid mixture and the thickness distribution of the accumulation, and evaluating the landslide risk.
Description
Technical Field
The invention relates to the field of engineering geological research, in particular to a numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climatic conditions.
Background
Landslide is one of the most common natural disaster types worldwide, and in most cases, landslide is closely related to extreme rainfall conditions, and heavy rain and continuous rainfall (extreme climate conditions) for a long time are the most important factors for causing landslide disasters. If the rainfall is small, rainwater infiltrates into the slope body, and the state of landslide movement can be approximately regarded as pure solid; however, under extreme rainfall conditions, a large amount of rainfall cannot infiltrate into the interior of the slope body in time, and part of rainfall forms surface runoff and carries landslide solid stones to move together, so that the state of landslide movement is a solid-liquid two-phase mixture.
For numerical simulation of a solid-liquid two-phase mixture of a landslide, at present, two limitations still exist, namely, firstly, few researches consider the influence of early rainfall, and most of the researches only analyze critical rainfall in a short time before the landslide occurs. For example, zhang (Zhang, etc., numerical simulation analysis of composite landslide solid-liquid coupling process-taking landslide without mountain land as an example) analyzes the coupling process of solid-liquid two phases of landslide by using a smooth particle fluid dynamics (SPH) method, but only considers the heavy rainfall process of inducing landslide, and does not involve early rainfall; in addition, it is important to determine the liquid content of a solid-liquid two-phase mixture, since this determines the degree of viscosity of the mixture and further determines the movement characteristics and the potential hazard of the mixture. However, there have been few studies on quantitative relation between actual rainfall and the liquid content in a solid-liquid mixture. The speed of movement and the thickness of the accumulation of landslide solid-liquid mixture were analyzed using FLO-2D software as in Tang et al (Tang et al Assessing debris flow risk at a catchment scale for an economic decision based on the LiDAR DEM and numerical simulation), but the surface runoff was not calculated from the rainfall. This results in an inability to perform efficient numerical simulation and quantitative assessment of the risk of a landslide solid-liquid two-phase mixture by actual rainfall conditions.
According to the invention, by considering the influence of topography, surface soil type and surface vegetation, the surface runoffs under different early rainfall and extreme rainfall conditions are quantitatively calculated, and then the numerical simulation evaluation of the danger of the solid-liquid two-phase mixture of the landslide is realized by combining FLO-2D software, so that the method has important significance for effectively developing landslide risk evaluation and reasonable early warning.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climate conditions, simultaneously considers early rainfall and critical rainfall conditions, and can quantitatively calculate the transformation of the extreme rainfall conditions and the surface runoff under specific surface soil and vegetation coverage conditions, thereby realizing the numerical simulation of the landslide solid-liquid two-phase mixture, and the whole flow is more reasonable and is close to the actual situation.
The technical scheme adopted for solving the technical problems is as follows:
a numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climatic conditions, the method comprising the steps of:
s1: obtaining a Digital Elevation Model (DEM) of a landslide body, a soil type (S), a surface vegetation type (LULC), a daily rainfall (unit mm) in a time range of 1 month before occurrence of the landslide, a daily temperature value (unit ℃ C.), a daily evapotranspiration (unit mm), and an extreme rainfall value (pe, unit mm) for inducing occurrence of the landslide;
s2: inputting the daily rainfall, the daily temperature value and the daily evapotranspiration in the time range of 1 month before landslide occurrence into Eas _Bal software to calculate the early rainfall infiltration value qa of landslide occurrence in mm/d; meanwhile, calculating the ground water level caused by early rainfall and expressing the ground water level by ha;
calculating rainfall intensity I according to formula (6):
wherein I is d Early rainfall infiltration value q for landslide occurrence a Units of mm/d; tc is the water collection time, calculated from equation (7):
wherein L is the longest distance from the watershed to the drainage basin outlet, and j is the average slope angle;
s3: the groundwater level he caused by the extreme rainfall value pe for the induced landslide occurrence is expressed as:
wherein CN is the number of runoff curves, which is only related to vegetation types, and the vegetation types are different, and the CN values are different; n is the porosity of the soil;
calculating a runoff coefficient C by using a formula (2):
wherein Ia is the initial extraction amount calculated from CN, which means that all parts except the generated runoff in rainfall are represented by formula (5),
Ia＝ha+he-z (5)
wherein z is the soil layer thickness;
s4: calculating early rainfall infiltration value qa of landslide occurrence and extreme rainfall value of landslide occurrence according to formula (8)Surface diameter flow value R under pe combination condition, unit m 3 /s：
R＝CI 3 T c 2 (8)；
S5: inputting the surface diameter value R obtained in the step S4 as clear water flow data into FLO-2D software, simulating a historical landslide event by using the FLO-2D software to perform parameter inversion of the solid-liquid mixture, obtaining the flow speed of the landslide solid-liquid mixture and the thickness distribution condition of the accumulation, and determining model parameters consistent with the real condition;
s6: daily meteorological data in a study area for years are obtained, wherein the daily meteorological data comprise actual rainfall, temperature value and evapotranspiration of the atmosphere, and the early rainfall infiltration value qa of each month is obtained by using Eas _Bal software; taking the maximum value of rainfall for 2 consecutive days per month as the extreme rainfall value pe of the month; calculating the effective infiltration quantity qa of early rainfall and the extreme rainfall pe of a research area under different reproduction periods;
s7: taking qa and pe values of different reproduction periods obtained in the step S6 as input, and calculating to obtain a surface diameter value under the reproduction period together with a Digital Elevation Model (DEM), a soil type (S) and a surface vegetation type (LULC) of a research area; and then taking the surface diameter value under the reproduction period as a clear water flow value, inputting the clear water flow value and model parameters which are consistent with the real situation in the step S5 into FLO-2D software, carrying out numerical simulation of a landslide solid-liquid mixture under the future rainfall condition, and evaluating landslide risk according to the landslide flow speed and the accumulation thickness by using numerical simulation results obtained in FLO-2D.
The process for evaluating landslide risk according to landslide flow speed and accumulation thickness is as follows:
the landslide flow speed is divided into three intervals according to whether it is less than 0.5 and whether it is less than 1.0: 0.ltoreq.v <0.5, 0.5.ltoreq.v <1.0, v.ltoreq.1.0, the stack thickness h being divided into three intervals according to whether or not it is smaller than 0.5 and whether or not it is smaller than 2.5: h is more than or equal to 0 and less than or equal to 0.5, h is more than or equal to 0.5 and less than or equal to 2.5, a danger assessment matrix is constructed by taking landslide flow speed as a row and accumulation thickness as a column, and a total zone is divided into a low danger zone, a medium danger zone and a high danger zone by comprehensively considering the common influence of speed and accumulation thickness; wherein v is in m/s and h is in m.
In the step S6, calculating the early-stage rainfall effective infiltration quantity qa and the extreme rainfall quantity pe of the research area under different reproduction periods by adopting a Weibull distribution calculation formula developed by Matlab software;
the formula of the cumulative probability function P (x) for the Weibull distribution is:
wherein P (x) is an accumulated probability function of a variable x, A is a scale parameter of Weibull distribution, k is a scale parameter of Weibull distribution, and the relation between the parameters is as follows:
where Γ is a Gamma function.
In step S5, the model parameters include Manning coefficient, yield stress, viscosity coefficient and laminar flow retardation coefficient, the model parameters are assigned according to the research area condition comparison standard manual, and the volume (m 3 ) The unit of the surface diameter flow value is m 3 S, determining the total flow (m) of the surface runoff in combination with the time of the landslide movement 3 )；
Taking the volume of the landslide solid matters/(the total flow of the surface runoff+the volume of the landslide solid matters) as the volume concentration Cv of the landslide solid-liquid mixture; then determining an amplification factor B according to B=1/(1-Cv);
inputting the volume concentration and the amplification factor into FLO-2D, then carrying out numerical simulation on the landslide solid-liquid mixture, and calculating the flow speed of the solid-liquid mixture and the thickness distribution condition of the deposit;
comparing the calculation result with the real situation, and if the calculation result is more consistent with the real situation, indicating that the model parameter assignment is reasonable; if the difference from the actual situation is larger, the model parameters are required to be recalculated after being adjusted until the accuracy requirement is met, and the model parameters which are consistent with the actual situation are obtained.
The ground water level elevation value ha caused by the early rainfall is expressed by a formula (1):
wherein a is the upstream catchment area of a specific place, and is determined by the terrain elevation, b is the size of a cell, K is the soil permeability coefficient, θ is the slope angle, ρ w Is the density, ρ of water s Is the density of the soil layer.
Compared with the prior art, the invention has the beneficial effects that:
(1) Extreme rainfall is extremely easy to induce landslide, and if the rainfall cannot infiltrate into a soil layer in time, surface runoff carrying solid block stones can be formed to move. Surface runoff formed by extreme rainfall has a relation with the actual early soil water content, but few researches at present consider the influence of early rainfall on the surface runoff. The invention simultaneously considers two conditions of early rainfall and short-time extreme rainfall to calculate the surface runoff, and is a beneficial supplement for calculating and evaluating the solid-liquid two-phase mixture of landslide;
(2) For numerical modeling of solid-liquid mixtures, the volume concentration determines the degree of viscosity of the mixture and further determines the magnitude of its potential disaster causing effect. According to the invention, the surface runoff is calculated through rainfall conditions, and the value is input into FLO-2D software as clear water flow data to perform numerical simulation of a landslide solid-liquid two-phase mixture. The quantitative calculation of the surface runoff quantity, the volume concentration and the amplification factor are connected together, so that the movement speed of an object and the thickness of a deposit can be better simulated.
(3) The surface runoff is the part of the rainfall which flows on the surface after infiltration, evaporation, vegetation evaporation and the like are removed. According to rainfall, the influence of early rainfall needs to be considered in calculating the surface runoff, the early rainfall can cause the underground water level to rise ha, and the permeability coefficient and vegetation type of soil need to be considered simultaneously, so that the surface runoff calculation is more accurate, and meanwhile, the accurate surface runoff is used for landslide stability research, so that remarkable progress is achieved.
Drawings
Fig. 1 calculates a tributary area schematic using the D8 algorithm.
FIG. 2 is a graph showing the velocity profile of motion during the parameter calibration of a solid-liquid two-phase mixture for urban North ditch landslide.
FIG. 3 shows a plot of the thickness of the deposit during the parameter calibration of a solid-liquid two-phase mixture for urban North ditch landslide.
And a graph of a motion velocity distribution diagram of a solid-liquid two-phase mixture of urban and north ditch landslide under the rainfall recurrence period of 4100 years.
And a graph of a sediment thickness distribution diagram of a solid-liquid two-phase mixture of urban and north ditch landslide under the rainfall reproduction period of 5100 years.
And (5) a dangerous evaluation result of the solid-liquid two-phase mixture of the urban and north ditch landslide in the rainfall recurrence period of 6100 year.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. Of course, the specific embodiments described herein are for purposes of illustration only and are not intended to limit the invention.
The invention discloses a numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climate conditions, which comprises the following steps:
s1: obtaining a Digital Elevation Model (DEM) of a landslide body, a soil type (S), a surface vegetation type (LULC), a daily rainfall (unit mm) in a time range of 1 month before occurrence of the landslide, a daily temperature value (unit ℃ C.), a daily evapotranspiration (unit mm), and an extreme rainfall value (pe, unit mm) for inducing occurrence of the landslide;
the daily rainfall, the daily temperature value and the daily evapotranspiration in the time range of 1 month before landslide occurrence are input into Eas _Bal software to calculate the early rainfall infiltration value qa (unit mm/d) of landslide occurrence. Then calculating the surface diameter value R (unit m) under the combined condition of the early rainfall infiltration value qa of landslide occurrence and the extreme rainfall value pe of induced landslide occurrence by using a runoff Curve Number (CN) method 3 /s)。
According to the formula (1), the groundwater level elevation value ha caused by early rainfall can be calculated:
wherein a is the upstream catchment area of a specific place, which is determined by the terrain elevation, a is the tributary area calculated in ArcGIS by using a standard D8 algorithm (shown in figure 1); b is the size of a cell, K is the permeability coefficient of soil, θ is the slope angle, ρ w Is the density, ρ of water s Is the density of the soil layer.
A runoff Curve Number (CN) method is used to determine the surface runoff for a given extreme rainfall condition, requiring the use of rainfall intensity and runoff coefficients.
Calculating a runoff coefficient C using formula (2):
where pe is the extreme rainfall inducing landslide, I a Is the initial extraction (in mm, all parts excluding the produced runoff in rainfall, including infiltration, evapotranspiration, etc.) calculated from CN.
The groundwater level caused by early rainfall is ha, and at this time, the thickness hn of the soil layer which is not infiltrated by groundwater can be calculated as follows by the formula (3):
hn＝z-ha (3)
wherein z is the original soil layer thickness;
the groundwater level he caused by the extreme rainfall value pe for the induced landslide occurrence is expressed as:
wherein CN is the number of runoff curves, which is only related to vegetation types, and the vegetation types are different, and the CN values are different; n is the porosity of the soil. Since the thickness of the slope soil layer is constant, the maximum value of he cannot be greater than hn. Ia is the sum of ha and he over the soil layer thickness:
Ia＝ha+he-z (5)
rainfall intensity I is calculated using a rainfall intensity-duration frequency curve:
wherein I is d Early rainfall infiltration value q for landslide occurrence a Units of mm/d; tc is the water collection time, calculated from the formula:
where L is the longest distance from the watershed to the watershed outlet and j is the average slope angle.
Calculating the surface diameter flow value R in unit m under the combined condition of the early rainfall infiltration value qa of landslide occurrence and the extreme rainfall value pe of landslide occurrence according to the formula (8) 3 /s：
R＝CI 3 T c 2 (8)。
In the above, the formula (8) is a surface runoff model, and the surface runoff model is used to calculate the surface runoff value under the given rainfall condition.
S2: inputting the surface diameter value R obtained in the step S1 as clear water flow data into FLO-2D software, simulating a historical landslide event by using the FLO-2D software to perform parameter inversion of the solid-liquid mixture, obtaining the flow speed of the landslide solid-liquid mixture and the thickness distribution condition of the accumulation, and determining model parameters consistent with the real condition; specifically, the method comprises the following steps:
inputting the surface diameter value R obtained in the step S1 as clear water flow data into FLO-2D software, assigning model parameters such as Manning coefficient, yield stress, viscosity coefficient, laminar flow retardation coefficient and the like according to a research area condition comparison standard manual, and taking the surface diameter value as liquid, wherein the unit of the surface diameter value is m 3 And/s, the total flow (m) of the surface runoff can be determined by combining the time of landslide movement 3 ) By engineering investigation meansDetermination of the volume (m) 3 ) Taking the volume of the landslide solid matters/(the total flow of the surface runoff+the volume of the landslide solid matters) as the volume concentration Cv of the landslide solid-liquid mixture; then determining an amplification factor B according to a formula (9);
B＝1/(1-Cv) (9)
inputting the volume concentration and the amplification factor into FLO-2D, then carrying out numerical simulation on the landslide solid-liquid mixture, and calculating the flow speed of the solid-liquid mixture and the thickness distribution condition of the deposit;
comparing the calculation result with the real situation, and if the calculation result is more consistent with the real situation, indicating that the model parameter assignment is reasonable; if the difference from the actual situation is larger, the model parameters are required to be recalculated after being adjusted until the accuracy requirement is met, and the model parameters which are consistent with the actual situation are obtained.
S3: daily meteorological data (actual rainfall, temperature value and evapotranspiration) in a study area for years are obtained, and a Eas _Bal software is utilized to obtain a early rainfall infiltration value qa of each month; the maximum value of rainfall every month for 2 consecutive days is taken as the extreme rainfall value pe for that month. And calculating the early rainfall infiltration value qa and the extreme rainfall pe of the research area under different reproduction periods by adopting a Weibull distribution calculation formula developed by Matlab software.
In the S3, the formula of the cumulative probability function P (x) of the Weibull distribution is as follows:
wherein P (x) is the cumulative probability function of the variable x, A is the scale parameter of Weibull distribution, k is the scale parameter of Weibull distribution, and the relationship between them is as follows:
where Γ is a Gamma function.
The method specifically comprises the following steps: setting the duration of the reproduction period, taking the obtained early rainfall infiltration value of each month as input, obtaining the early rainfall infiltration value of the research area under the reproduction period, and taking the extreme rainfall of each month as input, obtaining the extreme rainfall of the research area under the reproduction period; the recurring period is the influence of rainfall event probability, different recurring periods refer to 5 years first, 20 years first or 100 years first, and the like, the probability of 5 years first is 1/5=0.2, and the probability of 20 years first is 1/20=0.05.
S4: and (3) taking qa and pe values of different reproduction periods obtained in the step (S3) as input, and calculating to obtain the surface diameter value under the reproduction period together with a Digital Elevation Model (DEM), a soil type (S) and a surface vegetation type (LULC) of the research area. The volume concentration Cv and the amplification factor of the landslide solid-liquid mixture at this time were calculated again using the surface diameter flow value at the reproduction period as a liquid.
And (3) taking the surface diameter value under the reproduction period as a clear water flow value, inputting the clear water flow value, the model parameters which are consistent with the real conditions in the step S2, the volume concentration Cv of the landslide solid-liquid mixture obtained in the step S4 and the amplification factor into FLO-2D software, carrying out numerical simulation of the landslide solid-liquid mixture under the future rainfall condition, and obtaining a distribution map of the landslide flow speed and the accumulation thickness, wherein the numerical simulation result obtained in the FLO-2D comprises the landslide flow speed and the accumulation thickness.
S5: according to the landslide flow speed and the accumulation thickness data of the whole area obtained in the step S4, the landslide flow speed is divided into three sections according to whether the landslide flow speed is smaller than 0.5 and smaller than 1.0: 0.ltoreq.v <0.5, 0.5.ltoreq.v <1.0, v.ltoreq.1.0, the stack thickness h being divided into three intervals according to whether or not it is smaller than 0.5 and whether or not it is smaller than 2.5: h is more than or equal to 0 and less than or equal to 0.5, h is more than or equal to 0.5 and less than or equal to 2.5, a danger assessment matrix is constructed by taking landslide flow speed as a row and accumulation thickness as a column (shown in table 1), and the total area is divided into a low danger area, a medium danger area and a high danger area by comprehensively considering the common influence of speed and accumulation thickness.
TABLE 1 solid-liquid two-phase mixture hazard matrix for landslide
The landslide hazard class of a specific site is determined based on the combined relationship of the landslide flow speed and the stack thickness calculated in table 1, and is divided into a low hazard zone, a medium hazard zone and a high hazard zone.
Examples
1. And calculating a front rainfall infiltration value 1 month before the embodiment occurs based on Eas _Bal software, acquiring rainfall data of the DEM, the land utilization, the soil type and the landslide occurrence, and calculating the surface diameter value under the rainfall condition.
The examples are located in the northern ditch of city, ji county, fence, shanxi province, lv Liang mountain area of the east of China loess plateau. On the 3 th 7 th 2013, the region records a heavy rainfall event with a cumulative value of more than 100mm, and the maximum rainfall is 54.6mm. After rain, the rainwater is mixed with soil particles, broken stone and stones and moves along the downstream of the ditch, so that courtyard and resident houses are damaged. This time the event observed in the urban north ditch is considered to be a landslide caused by extreme rainfall. Long-term monitoring data of the survey area weather station was obtained from the local weather department for 20 years in 2001-2020. Inputting daily atmospheric rainfall, daily temperature average value and daily evapotranspiration amount of 1 month before landslide occurrence into EASY_BAL software, and calculating a early rainfall infiltration value of the 1 month time to obtain an accumulated early rainfall infiltration value of 0.15mm/d. The DEM of the research area is derived from the geospatial data cloudhttps:// www.gscloud.cn/) The method comprises the steps of carrying out a first treatment on the surface of the Land use types include 4 types, respectively, woodland, shrub, grassland, and village; the soil types mainly comprise 3 types, namely fourth-line loess, red soil and brown soil; the early rainfall infiltration value adopts a calculated numerical value result, and the whole area adopts a unified value; the rainfall grid file for inducing landslide of urban and north furrows is adopted for extreme rainfall, and the road surface diameter value under the rainfall condition is obtained by using a road curve number method to be 710m 3 /s。
2. And calculating the volume concentration and the amplification factor of the urban and north ditch landslide solid-liquid mixture by using the surface diameter value, simulating in FLO-2D software, comparing a simulation output result (speed and deposit thickness) with actual conditions, and calibrating and calculating model parameters, wherein the adjusted model parameter result is used as a basic parameter when FLO-2D is applied in the subsequent steps.
After the surface diameter value when landslide occurs is obtained, the volume concentration and the amplification factor of the urban and north ditch landslide solid-liquid mixture are calculated. In the FLO-2D confluence model, the junction of the two branches of the upstream region is taken as the water collection point. And (3) taking the obtained surface diameter value as clear water flow data and importing the clear water flow data into a grid where the water collecting point is positioned in a HYD mode. And assigning parameters such as a Manning coefficient, a yield stress, a viscosity coefficient, a laminar flow retardation coefficient and the like according to a condition comparison standard manual table lookup of a research area, and setting rainfall duration similar to that of a real event. The FLO-2D software then simulates the course of motion of a urban northern ditch landslide. The calculated speed distribution and the thickness of the piled up solid-liquid mixture of the landslide are respectively shown in fig. 2 and 3, which are in accordance with the actual situation, and the model parameters are accurate. Therefore, the model parameters such as the Manning coefficient, the yield stress, the viscosity coefficient, the laminar flow retardation coefficient and the like used at the moment are also used as the subsequent model parameters for numerical simulation.
3. And calculating the early rainfall infiltration value and the extreme rainfall of the research area under different reproduction periods by adopting a Weibull distribution calculation formula developed by Matlab software.
The early rainfall infiltration value qa of the study area 2001-2020 is calculated by EASY_BAL software and meteorological site monitoring data, and meanwhile, the maximum value of the rainfall of 2 days in a month in the period is counted, and the maximum rainfall is regarded as the short-term extreme rainfall of the month. Then use q for 20 years as described above a And p e Time series (480 q) a Data, 480 p e Data), the early rainfall infiltration value (qa) and the extreme rainfall (pe) of the research area under the reproduction period of 2-100 years are respectively calculated through the Weibull distribution calculation codes developed by Matlab software. The results showed that the early rainfall infiltration value was 4.2mm/d and the extreme rainfall was 306mm when the recurrence period was 100 years.
4. Calculating the surface runoff in the case again by using the rainfall data under the 100 calculated period, wherein the surface runoff is 908m 3 And/s. And then the volume concentration and the amplification factor of the landslide solid-liquid two-phase mixture at the moment are recalculated. Taking the surface diameter value as clear water flow data, and simultaneously calculating the slip during 100 years of reproduction period in FLO-2D along with the calibrated calculation parametersThe slope flow velocity profile and the stack thickness are shown in fig. 4 and 5, respectively.
5. The risk level is determined by using a risk matrix by comprehensively considering the speed distribution and the thickness of the deposit of the solid-liquid mixture.
According to Table 1, the landslide flow speed v is divided into 3 grades of 0.ltoreq.v <0.5, 0.5.ltoreq.v <1.0, v.gtoreq.1.0; the thickness h of the deposit is divided into 3 grades of 0.ltoreq.h <0.5, 0.5.ltoreq.h <2.5 and h.gtoreq.2.5. Then, according to table 1, the final landslide hazard partition map is calculated in ArcGIS according to the logical relationship of the grids, as shown in fig. 6. Wherein levels 1, 2, 3 represent low, medium, and high risk zones, respectively. Figure 6 can indicate which places are dangerous and which places are safer.
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.
The invention is applicable to the prior art where it is not described.
Claims (6)
1. A numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climate conditions, characterized by comprising the following steps:
s1: obtaining a Digital Elevation Model (DEM) of a landslide body, a soil type (S), a surface vegetation type (LULC), a daily rainfall (unit mm) in a time range of 1 month before occurrence of the landslide, a daily temperature value (unit ℃ C.), a daily evapotranspiration (unit mm), and an extreme rainfall value (pe, unit mm) for inducing occurrence of the landslide;
s2: inputting the daily rainfall, the daily temperature value and the daily evapotranspiration in the time range of 1 month before landslide occurrence into Eas _Bal software to calculate the early rainfall infiltration value qa of landslide occurrence in mm/d; meanwhile, calculating the ground water level caused by early rainfall and expressing the ground water level by ha;
calculating rainfall intensity I according to formula (6):
wherein I is d Early rainfall infiltration value q for landslide occurrence a Units of mm/d; tc is the water collection time, calculated from equation (7):
wherein L is the longest distance from the watershed to the drainage basin outlet, and j is the average slope angle;
s3: the groundwater level he caused by the extreme rainfall value pe for the induced landslide occurrence is expressed as:
wherein CN is the number of runoff curves, which is only related to vegetation types, and the vegetation types are different, and the CN values are different; n is the porosity of the soil;
calculating a runoff coefficient C by using a formula (2):
wherein Ia is the initial extraction amount calculated from CN, which means that all parts except the generated runoff in rainfall are represented by formula (5),
Ia＝ha+he-z (5)
wherein z is the soil layer thickness;
s4: calculating the surface diameter flow value R in unit m under the combined condition of the early rainfall infiltration value qa of landslide occurrence and the extreme rainfall value pe of landslide occurrence according to the formula (8) 3 /s：
R＝CI 3 T c 2 (8)；
S5: inputting the surface diameter value R obtained in the step S4 as clear water flow data into FLO-2D software, simulating a historical landslide event by using the FLO-2D software to perform parameter inversion of the solid-liquid mixture, obtaining the flow speed of the landslide solid-liquid mixture and the thickness distribution condition of the accumulation, and determining model parameters consistent with the real condition;
s6: daily meteorological data in a study area for years are obtained, wherein the daily meteorological data comprise actual rainfall, temperature value and evapotranspiration of the atmosphere, and the early rainfall infiltration value qa of each month is obtained by using Eas _Bal software; taking the maximum value of rainfall for 2 consecutive days per month as the extreme rainfall value pe of the month; calculating the effective infiltration quantity qa of early rainfall and the extreme rainfall pe of a research area under different reproduction periods;
s7: taking qa and pe values of different reproduction periods obtained in the step S6 as input, and calculating to obtain a surface diameter value under the reproduction period together with a Digital Elevation Model (DEM), a soil type (S) and a surface vegetation type (LULC) of a research area; and then taking the surface diameter value under the reproduction period as a clear water flow value, inputting the clear water flow value and model parameters which are consistent with the real situation in the step S5 into FLO-2D software, carrying out numerical simulation of a landslide solid-liquid mixture under the future rainfall condition, and evaluating landslide risk according to the landslide flow speed and the accumulation thickness by using numerical simulation results obtained in FLO-2D.
2. The numerical simulation method according to claim 1, wherein the process of estimating landslide risk from landslide flow speed, deposit thickness is:
the landslide flow speed is divided into three intervals according to whether it is less than 0.5 and whether it is less than 1.0: 0.ltoreq.v <0.5, 0.5.ltoreq.v <1.0, v.ltoreq.1.0, the stack thickness h being divided into three intervals according to whether or not it is smaller than 0.5 and whether or not it is smaller than 2.5: h is more than or equal to 0 and less than or equal to 0.5, h is more than or equal to 0.5 and less than or equal to 2.5, a danger assessment matrix is constructed by taking landslide flow speed as a row and accumulation thickness as a column, and a total zone is divided into a low danger zone, a medium danger zone and a high danger zone by comprehensively considering the common influence of speed and accumulation thickness; wherein v is in m/s and h is in m.
3. The numerical simulation method according to claim 1, wherein in step S6, a calculation formula of Weibull distribution developed by Matlab software is adopted to calculate the early rainfall effective infiltration amount qa and the extreme rainfall amount pe of the research area under different reproduction periods;
the formula of the cumulative probability function P (x) for the Weibull distribution is:
wherein P (x) is an accumulated probability function of a variable x, A is a scale parameter of Weibull distribution, k is a scale parameter of Weibull distribution, and the relation between the parameters is as follows:
where Γ is a Gamma function.
4. The numerical simulation method according to claim 1, wherein in step S5, the model parameters include a manning coefficient, a yield stress, a viscosity coefficient, and a laminar flow retardation coefficient, the model parameters are assigned according to a manual of research area condition comparison specifications, and the volume (m 3 ) The unit of the surface diameter flow value is m 3 S, determining the total flow (m) of the surface runoff in combination with the time of the landslide movement 3 )；
Taking the volume of the landslide solid matters/(the total flow of the surface runoff+the volume of the landslide solid matters) as the volume concentration Cv of the landslide solid-liquid mixture; then determining an amplification factor B according to B=1/(1-Cv);
inputting the volume concentration and the amplification factor into FLO-2D, then carrying out numerical simulation on the landslide solid-liquid mixture, and calculating the flow speed of the solid-liquid mixture and the thickness distribution condition of the deposit;
comparing the calculation result with the real situation, and if the calculation result is more consistent with the real situation, indicating that the model parameter assignment is reasonable; if the difference from the actual situation is larger, the model parameters are required to be recalculated after being adjusted until the accuracy requirement is met, and the model parameters which are consistent with the actual situation are obtained.
5. The numerical simulation method according to claim 1, wherein the elevation value ha of the groundwater level caused by the early rainfall is expressed by formula (1):
wherein a is the upstream catchment area of a specific place, and is determined by the terrain elevation, b is the size of a cell, K is the soil permeability coefficient, θ is the slope angle, ρ w Is the density, ρ of water s Is the density of the soil layer.
6. A numerical simulation method of a landslide solid-liquid two-phase mixture under extreme climate conditions, characterized by comprising the following steps:
s1: obtaining a Digital Elevation Model (DEM) of a landslide body, a soil type (S), a surface vegetation type (LULC), a daily rainfall (unit mm) in a time range of 1 month before occurrence of the landslide, a daily temperature value (unit ℃ C.), a daily evapotranspiration (unit mm), and an extreme rainfall value (pe, unit mm) for inducing occurrence of the landslide;
s2: inputting the daily rainfall, the daily temperature value and the daily evapotranspiration in the time range of 1 month before landslide occurrence into Eas _Bal software to calculate the early rainfall infiltration value qa of landslide occurrence in mm/d; meanwhile, calculating the ground water level caused by early rainfall and expressing the ground water level by ha;
calculating rainfall intensity I according to formula (6):
wherein I is d Early rainfall infiltration value q for landslide occurrence a Units of mm/d;tc is the water collection time, calculated from equation (7):
wherein L is the longest distance from the watershed to the drainage basin outlet, and j is the average slope angle;
s3: the groundwater level he caused by the extreme rainfall value pe for the induced landslide occurrence is expressed as:
wherein CN is the number of runoff curves, which is only related to vegetation types, and the vegetation types are different, and the CN values are different; n is the porosity of the soil;
calculating a runoff coefficient C by using a formula (2):
wherein Ia is the initial extraction amount calculated from CN, which means that all parts except the generated runoff in rainfall are represented by formula (5),
Ia＝ha+he-z (5)
wherein z is the soil layer thickness;
s4: calculating the surface diameter flow value R in unit m under the combined condition of the early rainfall infiltration value qa of landslide occurrence and the extreme rainfall value pe of landslide occurrence according to the formula (8) 3 /s：
R＝CI 3 T c 2 (8)；
S5: and (3) inputting the surface diameter value R obtained in the step (S4) as clear water flow data into FLO-2D software, and performing parameter inversion of the solid-liquid mixture by simulating a historical landslide event by using the FLO-2D software to obtain the flow speed of the landslide solid-liquid mixture and the thickness distribution condition of the accumulation.
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