CN106803223B - A kind of mountain flood risk evaluating method based on system polymorphic theory - Google Patents
A kind of mountain flood risk evaluating method based on system polymorphic theory Download PDFInfo
- Publication number
- CN106803223B CN106803223B CN201710030039.1A CN201710030039A CN106803223B CN 106803223 B CN106803223 B CN 106803223B CN 201710030039 A CN201710030039 A CN 201710030039A CN 106803223 B CN106803223 B CN 106803223B
- Authority
- CN
- China
- Prior art keywords
- risk
- flood
- mountain
- mountain flood
- state
- 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 41
- 238000011835 investigation Methods 0.000 claims abstract description 7
- 238000013480 data collection Methods 0.000 claims abstract description 5
- 238000011160 research Methods 0.000 claims description 15
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 12
- 239000002689 soil Substances 0.000 claims description 12
- 238000012502 risk assessment Methods 0.000 claims description 8
- 238000013210 evaluation model Methods 0.000 claims description 7
- 230000001939 inductive effect Effects 0.000 claims description 6
- 229910052742 iron Inorganic materials 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 6
- 230000015572 biosynthetic process Effects 0.000 claims description 4
- 238000005192 partition Methods 0.000 claims description 3
- 230000008093 supporting effect Effects 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 abstract description 8
- 230000002265 prevention Effects 0.000 abstract description 4
- 238000011161 development Methods 0.000 abstract description 3
- 238000003556 assay Methods 0.000 abstract description 2
- 238000009826 distribution Methods 0.000 abstract description 2
- 238000012876 topography Methods 0.000 abstract description 2
- 238000011156 evaluation Methods 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 238000000205 computational method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 238000013481 data capture Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/40—Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping
Landscapes
- Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Computer Security & Cryptography (AREA)
- Human Resources & Organizations (AREA)
- Educational Administration (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to a kind of mountain flood risk evaluating methods based on system polymorphic theory.Including：Data collection；Mountain flood on-site investigation；To influence factor divided rank；Establish model；Determine different risk class.By compiling the hydrology using small watershed as unit, the basic informations such as topography and geomorphology, fully use GIS, satellite remote sensing, the technological means such as hydrological analysis calculating, extract related data, in conjunction with mountain flood field investigation data, carry out Storm flood of small basins analysis, it evaluates mountain torrents and threatens residential block mountain flood present situation defence capability, science divides village danger area along the river, and pass through assay, mountain flood danger area Storm flood of small basins essential characteristic and personnel and property distribution situation are grasped more comprehensive and accurately, analyze heavy rain, relationship between mountain torrents and disaster, analyze village along the river, the possibility in market town and cities and towns leads to the Critical Rainfall that mountain flood occurs, support is provided to further increase mountain flood prevention ability and social economy's sustainable development.
Description
Technical field
It is a kind of to prevent and reduce natural disasters the present invention relates to a kind of mountain flood risk evaluating method based on system polymorphic theory
Hydrology evaluating method.
Background technology
Mountain flood refer to due to rainfall rising suddenly and sharply of causing of Mountain Area break flood and caused by mountain torrents mud-rock flow, mountain
Body landslide, avalanche etc. cause national economy and people's lives and properties the disaster of heavy losses.China's massif area is big, naturally
Quality looks complicated condition adds the influence of mankind's activity, causes mountain flood frequently to occur, seriously restrict mountain area economy
Development.Due to mountain flood prevention area of China vast area, type is various, complex genesis, and mountain flood prevention needs to hold not
The characteristics of with region, formulates measures against flood disaster to adaptation to local conditions.
Present many scholars carry out qualitative, quantitative point using technologies such as GIS and RS to the danger and vulnerability of studying area
Analysis, to obtain Regional Torrent Risk Zonation figure.But due to the limitation for studying area's data, each impact factor in Index grading and
There is also the influences of human factor in terms of weight determination, in the accuracy for affecting evaluation result to a certain degree.
Invention content
In order to overcome problem of the prior art, the present invention to propose a kind of mountain flood risk based on system polymorphic theory
Evaluation method.The method is by the various data in various studied areas, especially rainfall data, as the impact probability factor,
And each impact probability factor is calculated, determine the different risk class of each survey region.
The object of the present invention is achieved like this：A kind of mountain flood risk evaluating method based on system polymorphic theory,
The method includes the following steps：
The step of data collection：For to research area's Research on partition unit, collect each research unit hydrometeorology,
Topographic and geologic, soil vegetative cover, River, the various aspects situation of social economy and rainfall, DEM, soil types, soil profit
With, each item data of demographic data, socio-economic indicator, the especially collection of rainfall data；
The step of mountain flood on-site investigation：For being investigated further to the mountain flood present situation for being studied area, adjust
The reason of this area's mountain flood occurs is looked into, and mountain flood feature is analyzed；
The step of to influence factor divided rank：For according to the survey region mountain flood origin cause of formation, each influence factor to be drawn
It is divided into different brackets；
The step of establishing model：For according to system polymorphic theory, establishing mountain flood risk evaluation model；To cause calamity because
Each factor serial or parallel connection of sub and pregnant calamity environment, forms hazard assessment, at the same by each factor of supporting body it is in parallel or
Series connection forms vulnerability assessment, and hazard assessment and vulnerability assessment are connected later, carries out dangerous and vulnerability probability meter
It calculates, calculation formula is as follows：
For bykA probability is unequalM+1（M=3）The train of state element composition, the probability of different precarious positions
ForR s , calculated by formula：
（1）
For bykA probability is unequalM+1（M=3）The parallel system of state element composition, the probability of different precarious positions
ForR p , calculated by formula：
（2）
In formula：R p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3It is indicated at system respectively for Risk-Assessment Model
In the probability of high precarious position, high-risk state, moderate risk state, low precarious position；Vulnerability assessment model is come
It says and indicates that system is in high loss state, high loss state, moderate losses' state, low loss shape probability of state respectively；
Wherein, the area ratio under different elements different conditionsq i It can be calculated with formula：
q i = S i / S（3）
In formula：i=0,1,2,3；S i For the area of element status,STo study the area of unit；
The step of determining different risk class：For the result of calculation according to risk probability, each survey region is determined not
Same risk class.
Further, the rainfall data are collected as：
Practical rainfall data can be used for the abundant area of rainfall data, heavy rain atlas is used for Cross Some Region Without Data
One of method, regional heavy rain empirical formula method, " the iron First Academy " method.
Further, the mode of the different risk class of each survey region of the determination is as follows：
It is eachR p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Result of calculation list；
It finds in listsR p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Maximum value；
With the ranking where maximum value, determine that risk is main state value；
Using the small person of the value of principal states as high risk state, using the big person of the value of principal states as low-risk state.
The beneficial effect comprise that：By compiling using small watershed as bases such as the hydrology of unit, topography and geomorphologies
Plinth information fully uses the technological means such as GIS, satellite remote sensing, hydrological analysis calculating, related data is extracted, in conjunction with mountain flood
Field investigation data carries out Storm flood of small basins analysis, evaluation is threatened present situation defence capability, the section of residential block by mountain flood
It learns and divides village along the river（Containing cities and towns, market town）Danger area；And by assay, mountain flood is grasped more comprehensive and accurately
Danger area Storm flood of small basins essential characteristic and personnel and property distribution situation, between analysis heavy rain, mountain torrents and disaster
Relationship analyzes the Critical Rainfall that the possibility in village, market town and cities and towns along the river causes mountain flood to occur, to further increase mountain torrents
Diaster prevention and control ability and social economy's sustainable development provide support.
Compared with prior art, the present invention has the following advantages：
（1）Existing mountain flood assessment technique is affected by human factors larger during determining each index weights.And
The present invention excludes the interference of human factor to a certain extent, keeps evaluation result more accurate.
（2）Existing mountain flood evaluation study region is concentrated mainly on large scale, abundant information area.This research is suitable for
Mountain area Cross Some Region Without Data.
（3）The technology makes full use of ArcGis correlation analysis functions, solves data to a certain extent and obtains difficult ask
Topic.
Description of the drawings
The invention will be further described with reference to the accompanying drawings and examples.
Fig. 1 is the flow chart of one the method for the embodiment of the present invention；
Fig. 2 is the mountain torrents evaluation model schematic diagram in specific example described in the embodiment of the present invention one.
Specific implementation mode
Embodiment one：
The present embodiment is a kind of mountain flood risk evaluating method based on system polymorphic theory, and flow is as shown in Figure 1.This
Method described in embodiment includes the following steps：
（One）The step of data collection：For to research area's Research on partition unit, collecting the hydrology of each research unit
Meteorology, topographic and geologic, soil vegetative cover, River, the various aspects situation of social economy and rainfall, DEM, soil types, soil
Ground utilization, demographic data, socio-economic indicator each item data, the especially collection of rainfall data.
About the collection of rainfall data, practical rainfall data can be used for the abundant area of rainfall data, for no money
The methods of heavy rain atlas method, regional heavy rain empirical formula method, " the iron First Academy " method can be used in material area.It is provided with specific reference to survey region
Material, determines computational methods.The complexity that other factors can be obtained according to purpose, independence, reliability, representativeness and data
Equal correlation principles determine.
The present embodiment by taking the counties B of A provinces as an example, is research unit with each small towns, collects rainfall, DEM, soil class by certain research area
Type, land use, demographic data, socio-economic indicator（GDP）Deng.For the index in addition to rainfall, according to correlation principle come really
It is fixed.For rain factor, because the counties B are located in no observed flood data area, therefore using by design storm Derivation Design
The method of flood.It is main to use " the iron First Academy " method, and its result is checked with regional heavy rain empirical formula method.And for not
With soil water-containing situation, determines the preparation transfer early warning rainfall of survey region and shift early warning rainfall immediately.The present invention is with immediately
Early warning rainfall is shifted as interception rainfall index.
（Two）The step of mountain flood on-site investigation：For carrying out going deep into tune to the mountain flood present situation for being studied area
It looks into, investigates the reason of this area's mountain flood occurs, and analyze mountain flood feature.
The characteristics of the reason of each survey region is formed there is different mountain torrents and disaster, the progress that cannot treat different things as the same
Analysis and research, it is necessary to go deep into this area, the characteristics of according to factors, especially rainfall such as landform geomorphologic characteristics, vegetations, to mountain
The reason of disaster occurs, and the characteristics of production stream, made a concrete analysis of.
（Three）The step of to influence factor divided rank：For according to the survey region mountain flood origin cause of formation, by each influence because
Element is divided into different brackets.Classification declaration is carried out by taking rain factor as an example, rainfall is bigger within a certain period of time, easier initiation
Mountain flood, determining danger classes are higher.Rainfall is smaller, is less susceptible to cause mountain flood, determining danger classes is just
It is lower.It is specific to divide range, it can be depending on the concrete condition in research area.
Mountain flood will be formed by it with the relevant factor of mountain flood risk assessment in the practical citing of the present embodiment
It effect degree and disaster occurs causes damages the difference of degree, be divided into：0 grade（It is high）, 1 grade（It is high）, 2 grades（It is medium）, 3 grades
（It is low）4 kinds of states.
（Four）The step of establishing model：For according to system polymorphic theory, establishing mountain flood risk evaluation model.According to
The train and parallel system of mountain flood risk assessment system polymorphic are established in research to system polymorphic Series-parallel Systems
The computation model of different conditions probability.
Using rain factor as the Flood inducing factors of mountain flood risk assessment, pregnant calamity environmental exact details system by height difference, the gradient,
The related elements parallel connection such as slope aspect, soil types is constituted, and Flood inducing factors are in series with pregnant calamity environmental exact details system and constitute mountain flood
Risk-Assessment Model.By population, economic indicator（GDP）, that the related elements parallel connection such as land use pattern constitutes mountain flood is easy
Damage property evaluation model.It is in series by Risk-Assessment Model and vulnerability assessment model and constitutes mountain flood risk evaluation model.
Each factor serial or parallel connection of Flood inducing factors and pregnant calamity environment is formed dangerous based on system polymorphic theory
Evaluation, while in parallel or series by each factor of supporting body, vulnerability assessment is formed, later by hazard assessment and vulnerability
Evaluation series connection, carries out dangerous and vulnerability probability calculation, and calculation formula is as follows：
For bykA probability is unequalM+1（M=3）The train of state element composition, the probability of different precarious positions
ForR s , calculated by formula：
（1）
For bykA probability is unequalM+1（M=3）The parallel system of state element composition, the probability of different precarious positions
ForR p , calculated by formula：
（2）
In formula：R p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3It is indicated at system respectively for Risk-Assessment Model
In the probability of high precarious position, high-risk state, moderate risk state, low precarious position；Vulnerability assessment model is come
It says and indicates that system is in high loss state, high loss state, moderate losses' state, low loss shape probability of state respectively；
Wherein, the area ratio under different elements different conditionsq i It can be calculated with formula：
q i = S i / S（3）
In formula：i=0,1,2,3；S i For the area of element status,STo study the area of unit.
The practical citing of the present embodiment will select rainfall as Flood inducing factors in the counties B mountain flood risk evaluation indexes,
Pregnant calamity environmental factor is made of 4 relative relief, the gradient, slope aspect, soil types element in parallel.Vulnerability assessment index is by people
Mouth, economic indicator（GDP）, 3 each element in parallel of land use pattern constitute.Therefore, by Flood inducing factors, pregnant calamity environment, hazard-affected body
It is in series and constitutes the counties B mountain flood risk evaluation model, as shown in Figure 2.
Each different risk probability is calculated by model above.
（Five）The step of determining different risk class：For the result of calculation according to risk probability, each survey region is determined
Different risk class.
The result of calculation of application risk probability carry out risk class assessment can there are many modes, such as：Tabulating method, it is public
Formula method, curve method etc..
Tabulating method is taken in the practical citing of the present embodiment.Each small towns difference wind in the gained counties B is calculated according to above-mentioned correlation step
Dangerous level results, are shown in Table 1.
Each small towns mountain flood risk class in 1 counties B of table
Embodiment two：
The present embodiment is the improvement of embodiment one, is embodiment about rainfall method of data capture.Described in the present embodiment
Rainfall data are collected as：
Practical rainfall data can be used for the abundant area of rainfall data, heavy rain atlas can be used for Cross Some Region Without Data
The methods of method, regional heavy rain empirical formula method, " the iron First Academy " method.
Wherein, " the iron First Academy " method is to be suitable for catchment area in 100km2Storm flood of small basins computational methods below,
The method has considered three production stream, slope concentration and concentration of river network factors, and calculating achievement precision is higher.Regional heavy rain experience
Equation is a kind of provincialism empirical equation for having considered heavy rain and underlying surface factor as a whole, is chiefly used in calculating other methods
The calculation and check of synthesis design flow.
Embodiment three：
The present embodiment is the improvement of above-described embodiment, is different risks etc. of the above-described embodiment about each survey region of determination
The refinement of grade mode.The mode of the different risk class of each survey region of determination described in the present embodiment is as follows：
It is eachR p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Result of calculation list；
It finds in listsR p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Maximum value；
With the ranking where maximum value, determine that risk is main state value；
Using the small person of the value of principal states as high risk state, using the big person of the value of principal states as low-risk state.
By taking table 1 as an example：Row is the risk probability and loss probability in a township, and file is each township or town（Study unit）
Title.The maximum value of the risk probability in the townshiies Biao Zhong C is：0.5860, it is 3 grades, it is determined that principal states value is 3.Compare main
State value can be obtained to draw a conclusion：
The townshiies N are in high risk status；The towns F, the townshiies G, the townshiies J are in high risk state；The townshiies D, the towns H, the townshiies I, the townshiies K, the townshiies P are in
Medium risk state；The townshiies C, the townshiies E, the towns L, the towns M are in low-risk state.
Finally it should be noted that above be merely illustrative of the technical solution of the present invention and it is unrestricted, although with reference to preferable cloth
The scheme of setting describes the invention in detail, it will be understood by those of ordinary skill in the art that, it can be to the technology of the present invention
Scheme（Such as the mode of data collection, the selection of formula, utilization, step sequencing etc.）It modifies or equally replaces
It changes, without departing from the spirit of the technical scheme of the invention and range.
Claims (3)
1. a kind of mountain flood risk evaluating method based on system polymorphic theory, which is characterized in that the method includes such as
Lower step：
The step of data collection：For to research area's Research on partition unit, collecting hydrometeorology, the landform of each research unit
Geology, soil vegetative cover, River, the various aspects situation of social economy and rainfall, DEM, soil types, land use, people
Each item data of mouth data, socio-economic indicator；
The step of mountain flood on-site investigation：For being investigated further to the mountain flood present situation for being studied area, investigation should
The reason of regional mountain flood occurs, and mountain flood feature is analyzed；
The step of to influence factor divided rank：For according to the survey region mountain flood origin cause of formation, each influence factor to be divided into
Different brackets；
The step of establishing model：For according to system polymorphic theory, establishing mountain flood risk evaluation model；To Flood inducing factors and
Each factor serial or parallel connection of pregnant calamity environment forms hazard assessment, while in parallel or series by each factor of supporting body,
Vulnerability assessment is formed, hazard assessment and vulnerability assessment are connected later, carries out dangerous and vulnerability probability calculation, meter
It is as follows to calculate formula：
For bykA probability is unequalM+The train of 1 state element composition, wherein：M=3, the probability of different precarious positions
ForR s , calculated by formula：
（1）
For bykA probability is unequalMThe parallel system of+1 state element composition, wherein：M=3, the probability of different precarious positions
ForR p , calculated by formula：
（2）
In formula：R p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Indicate that system is in high respectively for Risk-Assessment Model
The probability of precarious position, high-risk state, moderate risk state, low precarious position；For vulnerability assessment model respectively
Expression system is in high loss state, high loss state, moderate losses' state, low loss shape probability of state；
Wherein, the area ratio under different elements different conditionsq i It can be calculated with formula：
q i = S i / S（3）
In formula：i=0,1,2,3；S i For the area of element status,STo study the area of unit；
The step of determining different risk class：For the result of calculation according to risk probability, the different wind of each survey region are determined
Dangerous grade.
2. according to the method described in claim 1, it is characterized in that, the rainfall data are collected as：
Practical rainfall data can be used for the abundant area of rainfall data, for Cross Some Region Without Data using heavy rain atlas method,
One of area's heavy rain empirical formula method, " the iron First Academy " method.
3. method according to claim 1 or 2, which is characterized in that the different risks etc. of each survey region of the determination
The mode of grade is as follows：
It is eachR p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Result of calculation list；
It finds in listsR p0 、R p1 、R p2 、R p3WithR s0 、R s1 、R s2 、R s3Maximum value；
With the ranking where maximum value, determine that risk is main state value；
Using the small person of the value of principal states as high risk state, using the big person of the value of principal states as low-risk state.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710030039.1A CN106803223B (en) | 2017-01-17 | 2017-01-17 | A kind of mountain flood risk evaluating method based on system polymorphic theory |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710030039.1A CN106803223B (en) | 2017-01-17 | 2017-01-17 | A kind of mountain flood risk evaluating method based on system polymorphic theory |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106803223A CN106803223A (en) | 2017-06-06 |
| CN106803223B true CN106803223B (en) | 2018-08-24 |
Family
ID=58984675
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710030039.1A Active CN106803223B (en) | 2017-01-17 | 2017-01-17 | A kind of mountain flood risk evaluating method based on system polymorphic theory |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106803223B (en) |
Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108022053B (en) * | 2017-12-19 | 2020-02-11 | 中国水利水电科学研究院 | Flood risk assessment method and device |
| CN108109347A (en) * | 2017-12-26 | 2018-06-01 | 李文清 | A kind of accurate disaster of mountain massif coast monitoring and warning system of early warning |
| CN107993027A (en) * | 2017-12-26 | 2018-05-04 | 潘永森 | One kind evaluates accurate Study On Flood Disaster Risx Assessment system |
| CN110428586B (en) * | 2019-07-08 | 2021-01-05 | 大连理工大学 | Early warning method for rural basal flood based on early rainfall and upstream and downstream topological relation |
| CN112380662B (en) * | 2019-07-29 | 2021-09-17 | 北京师范大学 | Construction method and application of mountain torrent disaster population loss assessment model |
| CN110570107A (en) * | 2019-08-28 | 2019-12-13 | 浙江仁欣环科院有限责任公司 | mountain torrent disaster risk assessment method based on DEM |
| CN111027810A (en) * | 2019-11-18 | 2020-04-17 | 天津大学 | Mountain torrent disaster distribution driving force evaluation method in super-large area |
| CN112116200B (en) * | 2020-08-10 | 2023-07-21 | 郑州大学 | Construction method of urban flood loss function of disaster missing information based on dynamic proportion substitution and hierarchical Bayes |
| CN112132341B (en) * | 2020-09-22 | 2021-10-12 | 西安理工大学 | Flood risk prediction method based on rainstorm process |
| CN112526104A (en) * | 2020-11-06 | 2021-03-19 | 马鞍山矿山研究总院股份有限公司 | Slope stability monitoring and early warning method, system and medium |
| CN113793038B (en) * | 2021-09-16 | 2023-12-22 | 贵阳市城市轨道交通集团有限公司 | Karst mountain area subway tunnel engineering disaster partitioning method under multi-factor coupling |
| CN115423157B (en) * | 2022-08-15 | 2023-04-28 | 中国水利水电科学研究院 | Dynamic early warning method and device for mountain torrent disaster risk |
| CN115456463A (en) * | 2022-09-30 | 2022-12-09 | 河南省科达水利勘测设计有限公司 | Risk grade classification method and system for mountain torrent disaster dangerous area |
| CN116070793B (en) * | 2023-03-28 | 2023-06-27 | 浙江水文新技术开发经营公司 | Hydrologic disaster prediction system based on data processing |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105653863A (en) * | 2015-12-29 | 2016-06-08 | 张豫 | Subtropical medium and small basin mountain torrent disaster nonlinear multi-field coupling early warning model |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006002687A2 (en) * | 2004-06-30 | 2006-01-12 | Swiss Reinsurance Company | Method and system for automated location-dependent recognition of flood risks |
| JP2006127156A (en) * | 2004-10-28 | 2006-05-18 | Japan Weather Association | Method and system for evaluating flooding risk, basin database, its preparation program, and method and program for simulating flooding |
-
2017
- 2017-01-17 CN CN201710030039.1A patent/CN106803223B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105653863A (en) * | 2015-12-29 | 2016-06-08 | 张豫 | Subtropical medium and small basin mountain torrent disaster nonlinear multi-field coupling early warning model |
Non-Patent Citations (3)
| Title |
|---|
| 地质灾害危险性区划的多态系统可靠性分析方法;李秀珍等;《灾害学》;20090630;第24卷(第2期);第1-5页 * |
| 基于多态系统理论的地震滑坡危险性评价模型;田述军;《山西建筑》;20130930;第39卷(第26期);第63-64页 * |
| 贵州省地质灾害危险性区划的多态系统可靠性分析;彭小平等;《施工技术》;20080630;第37卷;第436-438页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106803223A (en) | 2017-06-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106803223B (en) | A kind of mountain flood risk evaluating method based on system polymorphic theory | |
| Manfreda et al. | A digital elevation model based method for a rapid estimation of flood inundation depth | |
| CN109584510B (en) | Road high slope landslide hazard early warning method based on evaluation function training | |
| Li et al. | The influence of land urbanization on landslides: An empirical estimation based on Chinese provincial panel data | |
| CN102999694B (en) | A kind of mountain region disaster takes place frequently district's Risk Evaluation of Debris Flow method | |
| CN107463991A (en) | A kind of Regional Landslide method for evaluating hazard based on slopes unit and machine learning | |
| CN107220754B (en) | County scale mountain torrent disaster risk assessment method | |
| CN107341586A (en) | A kind of computational methods of the geological disaster occurrence frequency based on rainfall | |
| CN103559775A (en) | Urban flood disaster early warning system and method | |
| de Oliveira et al. | Geomorphological and stratigraphic analysis applied to coastal management | |
| CN104252556A (en) | River classification system | |
| CN106021290A (en) | Method for social network association excavation based on multi-scale geographic information | |
| CN106971510A (en) | A kind of double mode mountain torrents pre-alarming control system and method | |
| CN103088803A (en) | Method of distinguishing collapse causing factors of karst collapse | |
| Bajirao et al. | Application of remote sensing and GIS for morphometric analysis of watershed: A Review | |
| Zhou et al. | Ecosystem health assessment in debris flow-prone areas: A case study of Bailong River Basin in China | |
| Lai et al. | Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: a case study of an urban storm in Beijing | |
| Xu et al. | Comparative study on landslide susceptibility mapping based on different ratios of training samples and testing samples by using RF and FR-RF models | |
| Hu et al. | Debris flow susceptibility analysis based on the combined impacts of antecedent earthquakes and droughts: a case study for cascade hydropower stations in the upper Yangtze River, China | |
| Singh et al. | Hypsometric analysis of the lesser Himalayan watersheds using geographical information system | |
| CN108828332A (en) | A method of calculating lightning location system detection efficient | |
| Zini et al. | The RUSLE erosion index as a proxy indicator for debris flow susceptibility | |
| Shakirzanova et al. | Territorial long-term forecasting of hydrological characteristics of spring floods of lowland rivers | |
| Yudhicara et al. | Geomorphic Analysis in Determining Tectonic Activity Affected by Sumatra Fault in Liwa Region and Its Surrounding Area, Lampung, Indonesia | |
| Guizien | Spatial variability of wave conditions in the Gulf of Lions (NW Mediterranean Sea) |
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 |