CN115169812A - Frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static index - Google Patents
Frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static index Download PDFInfo
- Publication number
- CN115169812A CN115169812A CN202210654753.9A CN202210654753A CN115169812A CN 115169812 A CN115169812 A CN 115169812A CN 202210654753 A CN202210654753 A CN 202210654753A CN 115169812 A CN115169812 A CN 115169812A
- Authority
- CN
- China
- Prior art keywords
- index
- frozen soil
- thaw
- static
- risk
- 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.)
- Pending
Links
- 239000002689 soil Substances 0.000 title claims abstract description 132
- 238000000034 method Methods 0.000 title claims abstract description 63
- 230000003068 static effect Effects 0.000 title claims abstract description 62
- 238000012502 risk assessment Methods 0.000 title claims abstract description 41
- 230000008018 melting Effects 0.000 claims abstract description 7
- 238000002844 melting Methods 0.000 claims abstract description 7
- 238000011160 research Methods 0.000 claims abstract description 3
- 239000011159 matrix material Substances 0.000 claims description 26
- 239000004576 sand Substances 0.000 claims description 16
- 239000004927 clay Substances 0.000 claims description 11
- 238000005516 engineering process Methods 0.000 claims description 9
- 239000011435 rock Substances 0.000 claims description 7
- 239000004575 stone Substances 0.000 claims description 7
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 6
- 239000000155 melt Substances 0.000 claims description 3
- 239000010802 sludge Substances 0.000 claims description 3
- 238000000691 measurement method Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 claims description 2
- 238000013316 zoning Methods 0.000 abstract description 5
- 238000011156 evaluation Methods 0.000 abstract description 3
- 238000004088 simulation Methods 0.000 abstract 1
- 238000010257 thawing Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 3
- 238000012424 Freeze-thaw process Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 108010076282 Factor IX Proteins 0.000 description 1
- 108010023321 Factor VII Proteins 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000008014 freezing Effects 0.000 description 1
- 238000007710 freezing Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 239000013049 sediment Substances 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000010792 warming Methods 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
- G06Q10/06—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
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- 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
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Operations Research (AREA)
- Computational Mathematics (AREA)
- Game Theory and Decision Science (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Quality & Reliability (AREA)
- Algebra (AREA)
- Computing Systems (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)
Abstract
The invention provides a frozen soil thaw settlement risk assessment method and device combining dynamic deformation and a static index. The frozen soil surface deformation information is obtained by means of interferometric synthetic aperture radar (InSAR) inversion, a static index simulation result is obtained through a thaw-sink index, a risk zoning index and an allowable bearing capacity index, and the static index and dynamic deformation are combined through an analytic hierarchy process to obtain a multi-factor index considering the freeze-thaw change state of the frozen soil. The method provided by the invention tries to verify the multi-factor index by using the evaluation result of the existing index and the frozen soil surface deformation data of the research area, and has certain reference significance for evaluation work of permafrost melting and settlement disasters along the infrastructure of the frozen soil area.
Description
Technical Field
The invention relates to the technical field of frozen soil thaw settlement risk assessment, in particular to a frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static indexes.
Background
With global warming, the degradation of permafrost is accelerated by the rise of air temperature, so that geological disasters such as thaw, collapse, lake expansion and the like are caused, and the method has great influence on local hydrology and ecological processes, permafrost engineering stability and global carbon balance. Traditional geodetic means can monitor frozen soil on a point scale, but are limited on a large scale by manpower, material resources and financial resources. A risk map is a spatial representation of risks associated with a particular risk, used to determine current and future risks for a region, and may be used to assess the risk of frozen soil thaw settlement over a large scale.
The earliest Nelson et al (2001) proposed a thaw index that takes into account the relative changes in frozen earth ice content and active layer thickness; daanen et al (2012) consider four different factors and present a risk compartmentalization index; xu and Wu (2019) propose an allowable bearing capacity index in consideration of the difference in bearing capacity of different soil types in combination with the annual average ground temperature over the soil types. However, these indexes have some disadvantages, such as the thaw index and the allowable bearing capacity index do not take the factors affecting the thaw disaster into consideration, and the judgment process of the risk area index currently lacks the ability to separate ice from sediments, so there may be errors in judging the ice content. Besides, the conventional indexes have large difference in results due to different factors, and most of the indexes are static and do not consider the dynamic change of the freeze-thaw process.
Disclosure of Invention
How to solve the defects of the method is the problem mainly solved by the invention.
The technical scheme adopted by the invention is as follows: the method obtains the surface deformation of the frozen soil by utilizing an InSAR technology, obtains a multi-factor index by combining a traditional risk evaluation index and the surface deformation of the frozen soil through an analytic hierarchy process, considers various frozen soil thawing disaster factors and frozen soil freezing and thawing cycle dynamic changes, and improves the accuracy of risk zoning.
According to one aspect of the invention, the frozen soil thaw settlement risk assessment method combining dynamic deformation and static indexes comprises the following steps:
three static indexes of frozen soil thaw risk assessment are obtained, including: a thaw index, a risk compartmentalization index, and an allowable bearing capacity index;
acquiring the deformation of the earth surface of the frozen soil by utilizing an InSAR technology;
respectively calculating correlation coefficients between the frozen soil surface deformation and the three static indexes;
and listing a judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain weights of the frozen soil surface deformation and the three static indexes, and overlapping according to the weights to obtain the multi-factor index for frozen soil thaw settlement risk assessment.
Preferably, the step of obtaining the thaw index includes:
acquiring annual average ground temperature, gradient, normalized vegetation index and soil type data, obtaining weights of different data through an analytic hierarchy process, and superposing to obtain the volume ice content;
collecting parameter data of soil types and local melting indexes, and obtaining the thickness of the active layer by a Stefan formula, wherein the calculation formula is as follows:
wherein Z is the thickness of the active layer; lambda is the thermal conductivity of the soil; DDT is the melt index; l is latent heat of ice melting; gamma is the dry volume weight of the soil; w is the total water content of the soil when melted; wu is the unfrozen water content in the frozen soil;
and calculating to obtain a thaw settlement index through a thaw settlement formula according to the thickness of the movable layer and the ice content of the frozen soil volume, wherein the calculation formula is as follows:
I s ＝V ice ×ΔALT
wherein, I s Is a thaw index, V ice The ice content, delta, of the frozen soil volumeALT is the relative rate of change of the thickness of the active layer;
classifying the thaw-sinking indices into a low risk zone, a medium risk zone, and a high risk zone according to a nested-means method.
Preferably, the step of obtaining the risk compartment index comprises:
determining whether the surface property is bare rock or a sedimentary basin according to the frozen soil area, if the surface property is bare rock, directly judging the surface property to be a low-risk area, and if the surface property is the sedimentary basin, judging the surface property to be broken stone or sand, or silt or clay;
if the crushed stone or sand is broken stone or sand, judging the ice content, and if the ice content is lower than a preset ice content value, judging the area is a low risk area; if not, the thickness of the active layer is continuously judged, if the thickness of the active layer is larger than the preset value of the thickness of the active layer, the high risk area is judged, otherwise, the medium risk area is judged;
if the ice content is lower than the preset ice content value, judging the area with low risk; and if not, continuously judging whether the thickness of the active layer is larger than the preset value of the thickness of the active layer, if so, judging the active layer to be a high risk area, otherwise, judging the active layer to be a medium risk area.
Preferably, the step of obtaining the allowable load bearing capacity index comprises:
classifying the frozen earth surface into five categories according to the soil property of the frozen earth surface; the first type: crushed gravels, second type: gravel and grit, third type: medium sand, fine sand and silt sand, fourth type: clay, silty clay, and silt, fifth type: an ice layer containing soil;
different soil types correspond to different allowable bearing capacity formulas, which are as follows:
the first type: r f ＝-0.3959MAGT+0.6092
The second type: r f ＝-0.3012MAGT+0.4954
In the third category: r f ＝-0.3012MAGT+0.3454
The fourth type: r f ＝-0.1979MAGT+0.3046
The fifth type: r f ＝-0.1MAGT+0.0500
Wherein the content of the first and second substances,R f the allowable bearing capacity of the frozen soil area, and the MAGT is the annual average ground temperature;
the allowable load bearing index is divided into a low risk zone, a medium risk zone and a high risk zone according to the nested-means method.
Preferably, the step of obtaining the deformation of the earth surface of the frozen earth by using the InSAR technology includes:
and (3) carrying out interference processing on the plurality of synthetic aperture radar images based on a small baseline set interference measurement method, and determining the earth surface deformation rate of the frozen soil research area.
Preferably, the correlation coefficients between the frozen earth surface deformation and the three static indexes are respectively calculated, and the specific calculation formula is as follows:
wherein R is xy Is a correlation coefficient, x, between the surface deformation and two sample variables of any static index i 、y i Respectively the surface deformation and any static index,
and (3) the average value corresponding to the surface deformation and any static index, n is the number of the sample variables, and i represents the serial number of the sample variables.
Preferably, the step of listing the judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain the weights of the frozen soil surface deformation and the three static indexes, and obtaining the multi-factor index for frozen soil thaw settlement risk assessment according to weight superposition comprises the following steps of:
listing a judgment matrix about frozen earth surface deformation and three static indexes by taking each correlation coefficient as a reference basis;
carrying out consistency check on the judgment matrix, if the consistency ratio is less than 0.1, meeting the requirement, and if the consistency ratio is not less than 0.1, revising the importance of the relationship between the frozen soil surface deformation and the three static indexes in the judgment matrix until the requirement is met;
and superposing the frozen soil surface deformation and the three static indexes according to the weight obtained by judging the matrix to obtain a multi-factor index, wherein the multi-factor index is used for frozen soil thaw settlement risk assessment.
Wherein the consistency check process comprises the following steps:
wherein, CI is consistency index, lambda is maximum characteristic root of the judgment matrix, m is order number of the judgment matrix, RI is random consistency index, and CR is consistency ratio.
According to another aspect of the invention, the frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static indexes comprises the following modules:
the static index acquisition module is used for acquiring three static indexes of frozen soil thaw settlement risk assessment, and the static index acquisition module comprises: a thaw index, a risk compartmentalization index, and an allowable bearing capacity index;
the dynamic deformation acquisition module is used for acquiring the deformation of the earth surface of the frozen soil by utilizing an InSAR technology;
the correlation calculation module is used for calculating correlation coefficients between the frozen soil surface deformation and the three static indexes respectively;
and the multi-factor index acquisition module is used for listing the judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain the weights of the frozen soil surface deformation and the three static indexes, and obtaining the multi-factor index for frozen soil thaw settlement risk assessment according to weight superposition.
The technical scheme provided by the invention has the following beneficial effects: according to the invention, a traditional static index frozen soil thaw risk assessment method is combined with deformation data considering a dynamic frozen soil freeze-thaw process by an analytic hierarchy process to obtain a multi-factor index combining multiple disaster influence factors, and the frozen soil thaw risk is assessed by the index, so that the accuracy of frozen soil thaw risk zoning results is improved.
Drawings
The invention will be further described with reference to the following drawings and examples, wherein:
fig. 1 is a flowchart of a frozen soil thaw settlement risk assessment method combining dynamic deformation and a static index according to an embodiment of the present invention;
FIG. 2 is a situation of risk assessment of thawing and sinking of frozen soil near the Qinghai-Tibet railway by a multi-factor index proposed by an embodiment of the present invention;
fig. 3 is a structural diagram of a frozen soil thaw risk assessment apparatus combining dynamic deformation and a static index according to an embodiment of the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The first embodiment is as follows:
referring to fig. 1, the present embodiment provides a frozen soil thaw settlement risk assessment method combining dynamic deformation and static index, including the following steps:
s1: three static indexes of frozen soil thaw settlement risk assessment are obtained, including: a thaw index, a risk compartmentalization index, and an allowable bearing capacity index;
in this embodiment, S1 specifically includes:
s1.1: acquiring data related to the thickness of the calculated movable layer and the ice content of the frozen soil volume, and calculating to obtain a thaw-settlement index through a thaw-settlement formula, wherein the specific operation steps are as follows:
s1.1.1: acquiring annual average ground temperature, gradient, normalized vegetation index and soil type data, obtaining weights of different data through an analytic hierarchy process, and superposing to obtain the volume ice content;
s1.1.2: collecting parameter data of soil types and local melting indexes, and obtaining the thickness of the active layer by a Stefan formula, wherein the calculation formula is as follows:
wherein Z is the thickness (m) of the active layer; λ is the thermal conductivity of soil (W/(m ℃)); DDT is the melt index; l is latent heat of melting of ice (3.3X 10) 5 J/kg); gamma is the dry volume weight (kg/m) of the soil 3 ) (ii) a W is the total water content (%) of the soil when melted; wu is the unfrozen water content (%) in the frozen soil;
s1.1.3: and after the thickness of the movable layer and the ice content of the frozen soil volume are obtained, calculating to obtain a thaw-settlement index through a thaw-settlement formula, wherein the formula is as follows:
I s ＝V ice ×ΔALT
wherein, I s Is a thaw index, V ice The volume of frozen soil contains ice, and the delta ALT is the relative change rate of the thickness of the movable layer;
s1.1.4: and classifying the obtained thaw index according to a nested-means method, wherein the obtained thaw index is a low risk area, a medium risk area and a high risk area.
S1.2: the method comprises the following steps of obtaining exposed bare rock distribution conditions, soil sedimentary basin types, frozen soil ice content and active layer thickness data, and obtaining a risk zoning index according to a risk zoning process, wherein the specific steps are as follows:
s1.2.1: determining whether the surface property is bare rock or a sedimentary basin according to the frozen soil area, if the surface property is bare rock, directly judging the surface property to be a low-risk area, and if the surface property is the sedimentary basin, judging the surface property to be broken stone/sand or silt/clay;
s1.2.2: if the crushed stone or sand is the crushed stone or sand, judging the ice content (the ice content is higher than 20 percent, and the ice content is lower than 20 percent), and if the ice content is lower, directly judging the low risk area. If the ice content is high, continuously judging the thickness of the active layer, if the thickness of the active layer is more than 2.5 meters, judging the active layer is a high risk area, and if the thickness of the active layer is less than 2.5 meters, judging the active layer is a medium risk area;
s1.2.3: and if the sludge or the clay is the sludge or the clay, judging the ice content in the same way, and if the ice content is low, directly judging the area as the low-risk area. If the ice content is high and the thickness of the movable layer is more than 2.5 meters, the area is judged to be a high risk area, otherwise the area is judged to be a middle risk area.
S1.3: acquiring annual average ground temperature data and soil type classification data, and calculating different types of soil according to an allowable bearing capacity model, wherein the method comprises the following specific steps:
s1.3.1: classifying the frozen earth surface into five categories according to the soil property of the frozen earth surface; the first type: crushed gravels, second type: gravel and grit, third type: medium sand, fine sand and silt sand, fourth type: clay, silty clay, and silt, fifth type: an ice layer containing soil;
s1.3.2: different soil types correspond to different allowable bearing capacity formulas, which are as follows:
the first type: r f ＝-0.3959MAGT+0.6092
The second type: r f ＝-0.3012MAGT+0.4954
The third type: r is f ＝-0.3012MAGT+0.3454
The fourth type: r f ＝-0.1979MAGT+0.3046
The fifth type: r f ＝-0.1MAGT+0.0500
Wherein R is f The allowable bearing capacity of the frozen soil area, and the MAGT is the annual average ground temperature;
s1.3.3: the allowable load bearing index is divided into a low risk zone, a medium risk zone and a high risk zone according to the nested-means method.
In step S1, the heaving index and the allowable bearing capacity index are divided into a low risk area, a medium risk area and a high risk area according to a nested-means method, so as to be unified with the risk area index and facilitate subsequent calculation.
S2: acquiring the deformation of the earth surface of the frozen soil by utilizing an InSAR technology;
in this embodiment, S2 specifically is: the method comprises the following steps of obtaining Sentinel-1AVV polarization data, and obtaining frozen soil surface deformation based on a Small base line set Interferometric Synthetic Aperture Radar (SBAS-InSAR) method, wherein the method comprises the following specific steps:
s2.1: dividing the plurality of synthetic aperture radar images into a plurality of small baseline sets based on a space baseline threshold value and a time baseline threshold value, wherein the small wiring sets comprise a plurality of synthetic aperture radar image pairs;
s2.2: determining a deformation time sequence of each synthetic aperture radar image pair in the plurality of synthetic aperture radar image pairs based on a least square method;
s2.3: and obtaining the surface deformation quantity and the deformation rate of the closed mining area within a preset time period based on a singular value decomposition method and the deformation time sequence.
S3: respectively calculating correlation coefficients between the frozen soil surface deformation and the three static indexes;
in S3, the correlation coefficient is used for analyzing the correlation between the frozen soil surface deformation and the three static indexes, and specifically the calculation formula is as follows:
wherein R is xy Is a correlation coefficient, x, between two sample variables of surface deformation and any static index i 、y i Respectively the surface deformation and any static index,
and (3) the average value corresponding to the surface deformation and any static index, n is the number of the sample variables, and i represents the serial number of the sample variables.
S4: and listing a judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain weights of the frozen soil surface deformation and the three static indexes, and superposing the weights to obtain the multi-factor index for frozen soil thaw settlement risk assessment.
In this embodiment, step S4 specifically includes:
s4.1: and (3) assigning the three static indexes and the dynamic earth surface deformation by using the obtained correlation coefficient as a reference basis and utilizing scales in the table 1 to construct a judgment matrix:
TABLE 11-9 Scale methodological implications
| Scale | Means of |
| 1 | Showing the same importance of the two factors compared |
| 3 | Indicating that one factor is slightly more important than the other factor when compared to the other factor |
| 5 | Indicating that one factor is significantly more important than the other factor when compared to the other factor |
| 7 | Indicating that one factor is more important than the other factor |
| 9 | Indicating that one factor is extremely important compared to the |
| 2、4、6、8 | The median value of the above two adjacent judgment values |
| Reciprocal of the | If the scale of A and B is 3, then B and A are 1/3 |
S4.2: solving the characteristic vector of the judgment matrix, namely the weight of each index;
s4.3: carrying out consistency check on the judgment matrix, and if the consistency ratio is less than 0.1, meeting the requirement; if the consistency ratio is not less than 0.1, revising and judging the importance of the relationship between the frozen earth surface deformation and the three static indexes in the matrix until the requirements are met;
the steps of the consistency check are as follows:
wherein, CI is consistency index, lambda is maximum characteristic root of the judgment matrix, m is order number of the judgment matrix, RI is random consistency index, and CR is consistency ratio.
S4.4: and after the consistency test is carried out, superposing the frozen earth surface deformation and the three static indexes according to the weight to obtain the multi-factor index.
In order to verify the risk assessment effect of the multi-factor index in the embodiment, the multi-factor index is used for assessing the frozen soil thaw-sinking risk near the Qinghai-Tibet railway, referring to fig. 2, five regions with concentrated high risk areas, namely, tanggula, northern foot river, tuo river and five-track Liang Hexi beach, in these regions, attention needs to be paid to strengthening protection measures, and the frozen soil thaw-sinking state is monitored in real time. In addition, in the tangula section, the multi-factor index is divided into a low-risk area, the comprehensive index calculated by Ni (2021) and the like divides the section into a high-risk area, and the An Duozhi tangula section has the surface change mainly of frozen soil lifting rather than thawing and sinking by combining the result of local deformation data, so that the multi-factor index provided by the embodiment judges the risk of frozen soil thawing and sinking of the tangula section to be the low-risk area more reasonably.
Example two:
referring to fig. 3, the frozen soil thaw settlement risk assessment apparatus combining dynamic deformation and static index provided in this embodiment includes the following modules:
the static index acquisition module 1 is configured to acquire three static indexes of frozen soil thaw settlement risk assessment, including: a thaw index, a risk compartmentalization index, and an allowable bearing capacity index;
the dynamic deformation acquisition module 2 is used for acquiring the deformation of the earth surface of the frozen soil by utilizing an InSAR technology;
the correlation calculation module 3 is used for calculating correlation coefficients between the frozen earth surface deformation and the three static indexes respectively;
and the multi-factor index acquisition module 4 is used for listing the judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain the weights of the frozen soil surface deformation and the three static indexes, and obtaining the multi-factor index for frozen soil thaw settlement risk assessment according to weight superposition.
Each module of the frozen soil thaw settlement risk assessment device is used for implementing each step of the frozen soil thaw settlement risk assessment method embodiment, and the same technical effect can be achieved.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means can be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order, but rather the words first, second, etc. are to be interpreted as indicating.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. A frozen soil thaw settlement risk assessment method combining dynamic deformation and static indexes is characterized by comprising the following steps:
three static indexes of frozen soil thaw settlement risk assessment are obtained, including: a thaw index, a risk compartmentalization index, and an allowable bearing capacity index;
obtaining the deformation of the earth surface of the frozen soil by utilizing an InSAR technology;
respectively calculating correlation coefficients between the frozen soil surface deformation and the three static indexes;
and listing a judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain weights of the frozen soil surface deformation and the three static indexes, and superposing the weights to obtain the multi-factor index for frozen soil thaw settlement risk assessment.
2. The frozen soil thaw risk assessment method according to claim 1, wherein the step of obtaining the thaw index comprises:
acquiring annual average ground temperature, gradient, normalized vegetation index and soil type data, obtaining weights of different data through an analytic hierarchy process, and overlapping to obtain the ice content of the frozen soil volume;
collecting parameter data of soil types and local melting indexes, and obtaining the thickness of the active layer by a Stefan formula, wherein the calculation formula is as follows:
wherein Z is the thickness of the active layer; lambda is the thermal conductivity of the soil; DDT is the melt index; l is latent heat of ice melting; gamma is the dry volume weight of the soil; w is the total water content of the soil when melted; wu is the unfrozen water content in the frozen soil;
and calculating to obtain a thaw settlement index through a thaw settlement formula according to the thickness of the movable layer and the ice content of the frozen soil volume, wherein the calculation formula is as follows:
I s ＝V ice ×ΔALT
wherein, I s Is a thaw index, V ice The volume of frozen soil contains ice, and the delta ALT is the relative change rate of the thickness of the movable layer;
classifying the thaw-sinking indices into a low risk zone, a medium risk zone, and a high risk zone according to a nested-means method.
3. The frozen soil thaw risk assessment method according to claim 1, wherein the step of obtaining the risk compartmentalization index comprises:
determining whether the surface property is bare rock or a sedimentary basin aiming at the frozen soil area, if the surface property is bare rock, determining the surface property is a low-risk area, and if the surface property is the sedimentary basin, continuously determining the surface property is broken stone or sand or sludge or clay;
if the ice content is lower than the preset ice content value, judging the ice content is a low risk area; if not, the thickness of the active layer is continuously judged, if the thickness of the active layer is larger than the preset value of the thickness of the active layer, the high risk area is judged, otherwise, the medium risk area is judged;
if the ice content is lower than the preset ice content value, judging the area with low risk; and if not, continuously judging whether the thickness of the active layer is larger than the preset value of the thickness of the active layer, if so, judging the active layer to be a high risk area, otherwise, judging the active layer to be a medium risk area.
4. The frozen soil thaw risk assessment method according to claim 1, wherein the step of obtaining the allowable bearing capacity index comprises:
classifying the frozen earth surface into five categories according to the soil property of the frozen earth surface; the first type: crushed gravels, second type: gravel and grit, third type: medium sand, fine sand and silt sand, fourth type: clay, silty clay, and silt, fifth type: an ice layer containing soil;
different soil types correspond to different allowable bearing capacity formulas, which are as follows:
the first type is: r f ＝-0.3959MAGT+0.6092
The second type: r f ＝-0.3012MAGT+0.4954
In the third category: r is f ＝-0.3012MAGT+0.3454
The fourth type: r is f ＝-0.1979MAGT+0.3046
The fifth type: r f ＝-0.1MAGT+0.0500
Wherein R is f The allowable bearing capacity of the frozen soil area, and the MAGT is the annual average ground temperature;
the allowable load bearing index is divided into a low risk zone, a medium risk zone and a high risk zone according to the nested-means method.
5. The frozen soil thaw risk assessment method according to claim 1, wherein the step of obtaining frozen soil surface deformation by InSAR technology comprises:
and (3) carrying out interference processing on the plurality of synthetic aperture radar images based on a small baseline set interference measurement method, and determining the earth surface deformation rate of the frozen soil research area.
6. The frozen soil thaw settlement risk assessment method according to claim 1, wherein the correlation coefficients between the frozen soil surface deformation and the three static indexes are calculated respectively, and the specific calculation formula is as follows:
wherein R is xy Is a correlation coefficient, x, between two sample variables of surface deformation and any static index i 、y i Respectively the surface deformation and any static index,
and (3) the average value corresponding to the surface deformation and any static index, n is the number of the sample variables, and i represents the serial number of the sample variables.
7. The frozen soil thaw settlement risk assessment method according to claim 1, wherein the step of obtaining weights of the frozen soil surface deformation and the three static indexes by listing a judgment matrix through an analytic hierarchy process according to each correlation coefficient, and obtaining a multi-factor index for frozen soil thaw settlement risk assessment by stacking the weights comprises:
listing a judgment matrix about frozen earth surface deformation and three static indexes by taking each correlation coefficient as a reference basis;
carrying out consistency check on the judgment matrix, if the consistency ratio is less than 0.1, meeting the requirement, and if the consistency ratio is not less than 0.1, revising the importance of the relationship between the frozen soil surface deformation and the three static indexes in the judgment matrix until the requirement is met;
and superposing the frozen soil surface deformation and the three static indexes according to the weight obtained by the judgment matrix to obtain a multi-factor index, wherein the multi-factor index is used for frozen soil thaw settlement risk assessment.
8. The frozen soil thaw risk assessment method according to claim 7, wherein the consistency check is performed by the following process:
wherein, CI is consistency index, lambda is maximum characteristic root of the judgment matrix, m is order number of the judgment matrix, RI is random consistency index, and CR is consistency ratio.
9. A frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static indexes is characterized by comprising the following modules:
the static index acquisition module is used for acquiring three static indexes of frozen soil thaw settlement risk assessment, and the static index acquisition module comprises: a thaw index, a risk compartmentalization index, and an allowable bearing capacity index;
the dynamic deformation acquisition module is used for acquiring the deformation of the earth surface of the frozen soil by utilizing an InSAR technology;
the correlation calculation module is used for calculating correlation coefficients between the frozen earth surface deformation and the three static indexes respectively;
and the multi-factor index acquisition module is used for listing the judgment matrix through an analytic hierarchy process according to each correlation coefficient to obtain the weights of the frozen soil surface deformation and the three static indexes, and obtaining the multi-factor index for frozen soil thaw settlement risk assessment according to weight superposition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210654753.9A CN115169812A (en) | 2022-06-10 | 2022-06-10 | Frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static index |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210654753.9A CN115169812A (en) | 2022-06-10 | 2022-06-10 | Frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static index |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115169812A true CN115169812A (en) | 2022-10-11 |
Family
ID=83484449
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210654753.9A Pending CN115169812A (en) | 2022-06-10 | 2022-06-10 | Frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static index |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115169812A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117574493A (en) * | 2023-11-13 | 2024-02-20 | 中国公路工程咨询集团有限公司 | Highway frozen soil range deformation identification method and system in permafrost region |
-
2022
- 2022-06-10 CN CN202210654753.9A patent/CN115169812A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117574493A (en) * | 2023-11-13 | 2024-02-20 | 中国公路工程咨询集团有限公司 | Highway frozen soil range deformation identification method and system in permafrost region |
| CN117574493B (en) * | 2023-11-13 | 2024-05-28 | 中国公路工程咨询集团有限公司 | Highway frozen soil range deformation identification method and system in permafrost region |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Duvillard et al. | Three‐dimensional electrical conductivity and induced polarization tomography of a rock glacier | |
| Kumar et al. | Appraising the accuracy of GIS-based multi-criteria decision making technique for delineation of groundwater potential zones | |
| Quinton et al. | Permafrost‐thaw‐induced land‐cover change in the Canadian subarctic: Implications for water resources | |
| Mhaske et al. | GIS-based soil liquefaction susceptibility map of Mumbai city for earthquake events | |
| Sharma et al. | Influence of Shannon’s entropy on landslide-causing parameters for vulnerability study and zonation—a case study in Sikkim, India | |
| Asadi et al. | Vulnerability assessment of urban groundwater resources to nitrate: the case study of Mashhad, Iran | |
| Arulrajah et al. | Characteristics of Singapore marine clay at Changi | |
| Pullman et al. | Thaw settlement in soils of the Arctic Coastal Plain, Alaska | |
| CN115169812A (en) | Frozen soil thaw settlement risk assessment method and device combining dynamic deformation and static index | |
| Li et al. | Effects of needle ice on peat erosion processes during overland flow events | |
| Ewea et al. | Modeling of IDF curves for stormwater design in Makkah Al Mukarramah region, The Kingdom of Saudi Arabia | |
| Barclay et al. | Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale | |
| Yilmaz et al. | Liquefaction potential and susceptibility mapping in the city of Yalova, Turkey | |
| Zhu et al. | Spatial variation in the frequency and magnitude of mass movement in a semiarid, complex‐terrain agricultural watershed on the L oess P lateau of C hina | |
| Sadeghi et al. | Assessing the vulnerability of Iran to subsidence hazard using a hierarchical FUCOM-GIS framework | |
| Wang et al. | Factors influencing thermokarst lake development in Beiluhe basin, the Qinghai–Tibet Plateau | |
| Song et al. | Evaluation of geologic bearing capacity of coastal zones taking coastal area of Laizhou Bay as an example | |
| Saha et al. | Multivariate geophysical index-based prediction of the compression index of fine-grained soil through nonlinear regression | |
| Chiasson et al. | Thermal contraction crack polygons in Nunavik (northern Quebec): Distribution and development of polygonal patterned ground | |
| Wang et al. | Research on the eco-geological environment carrying capacity in pingwu county after the wenchuan earthquake based on the modified AHP | |
| Okeke et al. | An integrated assessment of land use impact, riparian vegetation and lithologic variation on streambank stability in a peri-urban watershed (Nigeria) | |
| Yanting et al. | Risk assessment of rain-induced debris flow in the lower reaches of Yajiang River based on GIS and CF coupling models | |
| Cao et al. | Land subsidence in Beijing’s sub-administrative center and its relationship with urban expansion inferred from Sentinel-1/2 observations | |
| Farzam et al. | Susceptibility modelling of seismically induced effects (landslides and rock falls) integrated to rapid scoring procedures for bridges using GIS tools for the Lowlands of the Saint-Lawrence Valley | |
| Sandhyavitri et al. | Identification and prioritization of coastal vulnerability areas based on coastal vulnerability indexes (CVI) and analytical hierarchy process (AHP) |
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 |