CN108320055A - The determination method of multiple river mouth Storm Surge joint return periods - Google Patents
The determination method of multiple river mouth Storm Surge joint return periods Download PDFInfo
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Abstract
The present invention relates to Marine Sciences and field of ocean engineering, a kind of determination method for combining the return period more particularly to multiple river mouth Storm Surges includes the following steps, S1 was counted in a period of time, the generation frequency of typhoon in institute's survey region establishes the Poisson distributions that the frequency occurs for typhoon；S2 counts the river mouth situation in institute's survey region, establishes each river mouth maximum best one-dimensional edge distribution surged caused by typhoon；S3 establishes the one-dimensional Poisson multiple malformations that the frequency occurs for each river mouth maximum compound typhoon of surging caused by typhoon；S4 establishes the multidimensional Poisson multiple malformation that the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon in institute's survey region；S5 obtains more river mouth Storm Surges and combines the return period.The present invention proposes a kind of more rational joint probability method for calculating the extreme water level in river mouth harbour, and region resource is allocated, it is significant to realize that coastal region engineering is effectively taken precautions against natural calamities.
Description
Technical field
The present invention relates to Marine Sciences and field of ocean engineering, and in particular to a kind of multiple river mouth Storm Surge connection
Close the determination method of return period.
Background technology
Extreme high tide level in coastal engineering design refers to tidal level of the hydraulic structure under abnormal operating conditions, it is
One of the important parameter of structure safe design.China《Harbour hydrology specification》Regulation：Extreme high tide level is in no less than continuous 20a
Highest water level field data on the basis of, using Gumbel distribution calculate 50a mono- meet high water level.This method is measured water level
It is counted as stochastic variable.The year extreme water level being actually observed be not usually merely as caused by Astronomical Factors,
But be composed of the increase and decrease water of the generations such as typhoon, cold wave and astronomical tide.In recent years, there is scholar to start to increase storm tide
Water considers as the principal element of highest water level, and year maximum is surged and carries out probability calculation as sample, is reproduced value
Superposition is on mean high tide, so that it is determined that extreme high tide level.
By the marine site of typhoon influence, occur the path of typhoon every year and number be it is random, the Storm Surge of generation
Number and intensity are also random.Typhoon does not all occur every year, this results in the time that no typhoon occurs, and exists containing zero
, therefore the reproduction value of year extremum method calculating typhoon wave height cannot be used.
For same field typhoon, the Storm events degree in the different river mouths in influence area is different.Have three for one
The region in a river mouth, individually from the point of view of, the Storm events of higher level can occur in each river mouth, but it very big wind occurs simultaneously
Explode water probability it is relatively low, that is, same typhoon influence region difference river mouth Storm events have certain correlation, it is right
Storm events degree in the different river mouths in same field typhoon, influence area is different.Therefore, in practical applications, if
The water level extreme value in each river mouth is selected to count reproduction value, then being ignored as the storm in same typhoon influence region difference river mouth
The correlation surged can cause the waste of resource so that extreme high tide level design value is bigger than normal.
Invention content
There is deviation in the present invention, propose one kind more for extreme high tide level and actual conditions are counted in the prior art
Reasonably to calculate the joint probability method of the extreme water level in river mouth harbour, region resource is allocated, realizes coastal region engineering
It effectively takes precautions against natural calamities significant.
To achieve the goals above, the present invention adopts the following technical scheme that, multiple river mouth Storm Surges combine the return period
Determination method, include the following steps,
S1. it counts in a period of time, the generation frequency of typhoon in institute's survey region, establishes typhoon and the frequency occurs
Poisson is distributed；
S2. the river mouth situation in statistics institute survey region, establish each river mouth caused by typhoon it is maximum surge it is best
One-dimensional edge distribution；
S3. it is compound to establish each river mouth one-dimensional Poisson that the frequency occurs for maximum compound typhoon of surging caused by typhoon
The extreme value distribution；
S4. the multidimensional that the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon in institute's survey region is established
Poisson multiple malformations；
S5. more river mouth Storm Surge joint return periods are obtained.
Further, the step S2 is specifically included：
S21. the quantity in the river mouth in statistics institute survey region；
S22. each river mouth maximum data surged caused by typhoon are collected；
S23. suitable distribution linetype is selected to be fitted each river mouth maximum caused by typhoon data of surging；
S24. each river mouth maximum best one-dimensional edge distribution surged caused by typhoon is determined.
Further, in the step S23, the distribution is linearly distributed including Pearson-III types, Weibull is distributed,
Generalized extreme value distribution and logarithm normal distribution.
Further, in the step S24, pass through K-S inspections, observation, the sum of squares of deviations of estimated value and AIC information
Criterion determines each river mouth maximum best one-dimensional edge distribution surged caused by typhoon.
Further, the step S4 is specifically included：
S41. surge compound typhoon of all river mouths maximum caused by typhoon is established using suitable Copula functions to occur
The multidimensional Poisson multiple malformation of the frequency；
S42. determine that the best multidimensional Poisson of the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon
Multiple malformation.
Further, in the step S41, the Copula functions include normal state Copula, Frank Copula,
Clayton Copula and Gumbel-Hougaard (G-H) Copula.
Further, in the step S34, determine that all river mouths are drawn by typhoon by K-S inspections and AIC information criterions
The best multidimensional Poisson multiple malformation of the frequency occurs for surge compound typhoon of the maximum risen.
The present invention proposes a kind of joint ensemble more meeting the more river mouth causing disastrous degrees in region under the influence of storm tide, right
Carry out multiple river mouths and combine risk analysis of causing disaster to be of great significance.Simultaneously for same field typhoon, in influence area not
It is different with the Storm events degree in river mouth.The Storm events in river mouth have certain correlation in same influence area, by right
The Storm events joint probability calculation in same typhoon influence region difference river mouth, especially the synchronization Journal of Sex Research of Storm events, can
To determine by the Storm events in each river mouth of same typhoon influence under the fixed rendition phase, there is weight for the engineering protection of this area
Meaning is wanted, can be shot the arrow at the target Regional Disaster mitigation, the high estuary region of Storm Surge Height of Typhoon reinforces engineering protection, it is not necessary to Suo Youhe
Mouthful area is taken precautions against natural calamities goods and materials mean allocation, realizes accurate prevention and control, science decision is provided for preventing and reducing natural disasters for science.
Description of the drawings
Fig. 1 is the Poisson fittings of distribution that the frequency occurs for typhoon；
Fig. 2 is the Storm Surge Height of Typhoon sequence (1980-2004) of NanDown Xi, sulphur small stream and the river mouth of blue yangsi (Jing-River Point,LI 5)；
Fig. 3 is the scatter plot of the Storm Surge Height of Typhoon sequence at the river mouth of three streams；
Wherein, (a) is the scatter plot of Nan Kanxi；(b) it is the scatter plot of sulphur small stream；(c) it is the scatter plot of blue yangsi (Jing-River Point,LI 5)；
Fig. 4 is that the various distribution probability density of Storm Surge Height of Typhoon at the river mouths Kan Xi of south are fitted with cumulative distribution；
Wherein, (a) is Pearson-III fitting results；(b) it is Weibull fitting results；(c) it is GEV fitting results；
(d) it is Lognormal fitting results；
Fig. 5 is that the various distribution probability density of Storm Surge Height of Typhoon at sulphur small stream river mouth are fitted with cumulative distribution；
Wherein, (a) is Pearson-III fitting results；(b) it is Weibull fitting results；(c) it is GEV fitting results；
(d) it is Lognormal fitting results；
Fig. 6 is that the various distribution probability density of Storm Surge Height of Typhoon at blue yangsi (Jing-River Point,LI 5) river mouth are fitted with cumulative distribution；
Wherein, (a) is Pearson-III fitting results；(b) it is Weibull fitting results；(c) it is GEV fitting results；
(d) it is Lognormal fitting results；
Fig. 7 is the joint return period contour surface of three river mouth Storm Surge Height of Typhoon；
Fig. 8 is that three river mouth Storm Surge Height of Typhoon meets Joint Distribution joint probability in 50 years one；
Wherein, (a) is three river mouth Storm Surge Height of Typhoon, 2% joint probability curved surface；(b) it is that NanDown Xi combines generally with the 2% of sulphur small stream
Rate side view；(c) it is NanDown Xi and 2% joint probability side view of orchid yangsi (Jing-River Point,LI 5)；(d) it is that sulphur small stream is combined generally with the 2% of blue yangsi (Jing-River Point,LI 5)
Rate side view.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, right below in conjunction with drawings and examples
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
The determination method of multiple river mouth Storm Surges joint return period of the present invention, includes the following steps,
S1. it counts in a period of time, the generation frequency of typhoon in institute's survey region, establishes typhoon and the frequency occurs
Poisson is distributed；
It now collects in a period of time, generally as unit of year, the quantity situation of typhoon occurs in institute's survey region, establishes platform
The Poisson distributions of the frequency occur for wind.
S2. the river mouth situation in statistics institute survey region, establish each river mouth caused by typhoon it is maximum surge it is best
One-dimensional edge distribution；The step S2 is specifically included：
S21. the quantity in the river mouth in statistics institute survey region；
S22. each river mouth maximum data surged caused by typhoon are collected；
S23. suitable distribution linetype is selected to be fitted each river mouth maximum caused by typhoon data of surging；It is described
Distribution includes linearly the distribution of Pearson-III types, Weibull distributions, generalized extreme value distribution and logarithm normal distribution.
S24. each river mouth maximum best one-dimensional edge distribution surged caused by typhoon is determined；It examined, seen by K-S
Measured value, the sum of squares of deviations of estimated value and AIC information criterions determine best one-dimensional edge distribution.
S3. it is compound to establish each river mouth one-dimensional Poisson that the frequency occurs for maximum compound typhoon of surging caused by typhoon
The extreme value distribution；
If the etesian typhoon n in somewhere is a discrete random variable, and the extreme value wave in Typhoon Process every time
Height is set as ξ, and the Extreme Wave in no typhoon time is set as η.Assuming that ξ is covariance matrix of sample, probability-distribution function is G (x).
If ξ i are the ith observation of ξ, n is the stochastic variable with the independent value nonnegative integers of ξ, and distribution function is denoted as：
It is assumed that random vector：
Then F0 (x) is referred to as one-dimensional multiple malformation：
Assuming that λ indicates the average time that annual typhoon occurs, if Typhoon Process frequency of occurrence n meets Poisson distributions：
It can be obtained by formula (3)：
In formula, G (x) if Pearson-III types be distributed, Weibull distribution, generalized extreme value (GEV) distribution or logarithm just
State (lognormal) is distributed, and substitutes into formula (5), you can obtains Poisson-Pearson III distributions, Poisson-Weibull
Distribution, Poisson-GEV distributions or Poisson-lognormal distributed models.
S4. the multidimensional that the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon in institute's survey region is established
Poisson multiple malformations；
S41. surge compound typhoon of all river mouths maximum caused by typhoon is established using suitable Copula functions to occur
The multidimensional Poisson multiple malformation of the frequency；
The process of shifting onto is：
Assuming that N number of marine environment stochastic variable in Typhoon Process is (ξ every time1,ξ2,···,ξN), no typhoon time
In extreme value marine environment stochastic variable be (ζ1,ζ2,···,ζN).With G (x1,x2,···,xN) and g (x1,
x2,···,xN) stochastic variable (ξ is indicated respectively1, ξ2,···,ξN) joint distribution function and joint probability density letter
Number, Q (x1,x2,···,xN) indicate stochastic variable (ζ1,ζ2,···,ζN) joint distribution function.With (ξ1i,ξ2i,
ξ3i,···,ξNi) it is respectively the ith observation of N number of stochastic variable, then indicated and the independent value nonnegative integers of ξ with n
Stochastic variable, probability-distribution function is denoted as formula (1).Now define a stochastic variable (X1,X2,···, XN)：
Then (X1,X2,···,XN) joint distribution function be：
In formula, multiple random variables (X1,X2,···,XN) joint distribution function and probability density function be respectively G
(x1,x2,···,xN) and g (x1,x2,···,xN)；GX1(u1) it is G (x1,x2,···,xN) marginal distribution function, i.e.,
GX1(u1)=G (u1,+∞,…,+∞) (8)
Assuming that frequency n, which occurs, for annual typhoon obeys Poisson distributions (formula (4)), formula (7) can turn to：
Formula (9) is the multidimensional Poisson multiple malformation function of stochastic variable (X1, X2, XN).
Its corresponding probability density function is：
G (x in formula (10)1,x2,,xN) indicate not considering that the original of the multiple random variables in the case of the frequency occurs for typhoon
Joint probability density function establishes the original Joint Distribution model of multiple random variables, g (x according to copula functions1,x2,,
xN) can be according to the following formula：
g(x1,x2,…,xN)=c (x1,x2,…,xN)·f(x1)·f(x2)·…·f(xN) (11)
C (x in formula (11)1,x2,,xN) be copula functions probability density function, f (xi) indicate univariate probability
Density function.
According to the multidimensional Poisson multiple malformation of formula (9) and formula (10), two-dimentional Poisson Compound Extreme Values can be obtained
The probability density function and probability-distribution function of distribution and three-dimensional Poisson multiple malformations are shown in Table 2.
2 two and three dimensions Poisson multiple malformation models of table
Finally bring suitable Copula functions into, including normal state Copula, Frank Copula, Clayton Copula and
Gumbel-Hougaard (G-H) Copula is fitted.
S42. determine that the best multidimensional Poisson of the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon
Multiple malformation.It is examined by K-S and AIC information criterions is surged composite bench to determine all river mouths maximum caused by typhoon
The best multidimensional Poisson multiple malformation of the frequency occurs for wind.
S5. more river mouth Storm Surge joint return periods are obtained.
Poisson multidimensional probability of recombination models are established to the Storm Surge Height of Typhoon sequence in multiple river mouths, you can draw fixed weight
Current joint probability contour surface.The joint return period under multiple river mouth difference Storm Surge Height of Typhoon can be obtained simultaneously.
In order to verify the reliability of the method for the present invention, the present invention has chosen the related data of TaiWan, China North zone to this
The method of invention is verified.
One, calculating process
1, it counts in a period of time, the generation frequency of typhoon in institute's survey region, establishes the Poisson that the frequency occurs for typhoon
Distribution；
The history typhoon of 1980-2004 to influencing TaiWan, China the north is reported after carrying out.Select the typhoon condition calculated
For：Typhoon track is no more than 250km at a distance from TaiWan, China.By statistics, TaiWan, China the north is total in 1980-2004
36 typhoons occur, etesian number statistics is shown in Table 1.Poisson distributions are selected to be fitted the typhoon year frequency, parameter
The estimated value of λ is 1.44.The Fitness Test of Poisson distributions is shown in Table 2, and fitting result is shown in that Fig. 1, fitting effect are fine.Cause
This, the frequency determines that obeying the Poisson that parameter is 1.44 is distributed.
1 1980-2004 of table influences the typhoon number statistics in three streams river mouth
According to table 1, the Poisson distribution test statistics of typhoon frequency is χ 2=1.8241, is less than the level of signifiance 0.05
When hypothesis testing critical valueIllustrate that typhoon frequency meets the Poisson of λ=36/25=1.44
Distribution.
The statistical check of the frequency occurs for 2 typhoon of table
2, the river mouth situation in statistics institute survey region establishes each river mouth maximum best one to surge caused by typhoon
Tie up edge distribution；It is compound to establish each river mouth one-dimensional Poisson that the frequency occurs for maximum compound typhoon of surging caused by typhoon
The extreme value distribution acquires reproduction value by one-dimensional Poisson multiple malformations.
TaiWan, China the north, which is divided into, is furnished with 3 each river mouths, is NanDown Xi (Nang-Kang), sulphur small stream (Huang) and orchid sun respectively
Small stream (Lan-Yang).NanDown Xi (Nang-Kang), sulphur small stream (Huang) and blue yangsi (Jing-River Point,LI 5) (Lan-Yang) is calculated in report afterwards
Storm Surge Height of Typhoon sequence of the river mouth in 1980-2004 is as shown in Figure 2.
What the maximum in the NanDown Xi, sulphur small stream and blue three streams of the yangsi (Jing-River Point,LI 5) river mouth that are obtained from 36 storm Typhoon Process was surged
Scatter plot is shown in Fig. 3 respectively.
Select the distribution of Pearson-III types, three-parameter weibull distribution, GEV distributions and Log-normal distributions right respectively
Three surging for sequence are fitted.
A. the fitting extremely surged at southern down small stream river mouth
Storm Surge Height of Typhoon sequence at the southern river mouths Kan Xi is fitted, parameter estimation result such as table 3.Matched curve is respectively such as
Fig. 4.
The parameter Estimation of Storm Surge Height of Typhoon fitting of distribution at the 3 south river mouths Kan Xi of table
Note：PA, PB and PC indicate position, scale and the form parameter of each distribution respectively.
Due to not accounting for the number of typhoon generation, the recurrent frequency in Fig. 3 described in abscissa, and the non-corresponding return period
Inverse, it is merely meant that the recurrent frequency in data.Other are such similar to the abscissa meaning of fitted figure.
4 kinds of distributions pair are compared using K-S inspections, observation, the sum of squares of deviations of estimated value and AIC information criterions simultaneously
The fit solution of extreme sequence of surging.Under the conditions of confidence alpha=0.05, the statistic D^n and deviation square RMSE and AIC of K-S
Result of calculation such as table 4.Fitting result show the distribution of Pearson-III types, three-parameter weibull distribution, GEV distribution and
Log-normal distributions have all passed through statistical check, and wherein GEV fittings of distribution are optimal, and the distribution of Pearson-III types is taken second place.It utilizes
One-dimensional Poisson Compound Distributions acquire reproduction value such as table 5.The result shows that reproduction value obtained by Weibull is minimum, Pearson-
III takes second place.
The K-S of Storm Surge Height of Typhoon fitting of distribution at the 4 south river mouths Kan Xi of table is examined and sum of squares of deviations
The reproduction value (m) that Storm Surge Height of Typhoon Poisson Compound Distributions at the 5 south river mouths Kan Xi of table calculate
B. the fitting extremely surged at sulphur small stream river mouth
Storm Surge Height of Typhoon sequence at sulphur small stream river mouth is fitted, matched curve is respectively such as Fig. 5 parameter estimation results such as table
6.Fitting result shows that fitting result shows the distribution of Pearson-III types, three-parameter weibull distribution, GEV distributions and Log-
Normal distributions have all passed through statistical check, and wherein Pearson-III types fitting of distribution is optimal, and Weibull distributions are taken second place.
The parameter Estimation of Storm Surge Height of Typhoon fitting of distribution at 6 sulphur small stream river mouth of table
Note：PA, PB and PC indicate position, scale and the form parameter of each distribution respectively.
4 kinds of distributions pair are compared using K-S inspections, observation, the sum of squares of deviations of estimated value and AIC information criterions simultaneously
The fit solution of extreme sequence of surging.Under the conditions of confidence alpha=0.05, the statistic D^n and deviation square RMSE and AIC of K-S
Result of calculation such as table 7.The result shows that the distribution of Pearson-III types, three-parameter weibull distribution, GEV distributions and Log-
Normal distributions have all passed through statistical check, and the wherein fitting of Pearson-III is optimal, and Weibull takes second place.Using one-dimensional
Poisson Compound Distributions acquire reproduction value such as table 8.The result shows that reproduction value obtained by Weibull is minimum, Pearson-III times
It.
The K-S of Storm Surge Height of Typhoon fitting of distribution at 7 sulphur small stream river mouth of table is examined and sum of squares of deviations
The reproduction value (m) that Storm Surge Height of Typhoon Poisson Compound Distributions at 8 sulphur small stream river mouth of table calculate
C. the fitting extremely surged at blue yangsi (Jing-River Point,LI 5) river mouth
Storm Surge Height of Typhoon sequence at blue yangsi (Jing-River Point,LI 5) river mouth is fitted, matched curve is respectively such as Fig. 6, and parameter estimation result is such as
9 fitting result of table shows the distribution of Pearson-III types, three-parameter weibull distribution, GEV distributions and Log-normal distributions
Statistical check is all passed through, wherein Pearson-III types fitting of distribution is optimal, and Lognormal distributions are taken second place.
The parameter Estimation of Storm Surge Height of Typhoon fitting of distribution at 9 sulphur small stream river mouth of table
Note：PA, PB and PC indicate position, scale and the form parameter of each distribution respectively.
4 kinds of distributions pair are compared using K-S inspections, observation, the sum of squares of deviations of estimated value and AIC information criterions simultaneously
The fit solution of extreme sequence of surging.Under the conditions of confidence alpha=0.05, the statistic D^n and deviation square RMSE and AIC of K-S
Result of calculation such as table 10.The result shows that the fitting of Pearson-III is optimal, Log-normal takes second place.Using one-dimensional
Poisson Compound Distributions acquire reproduction value such as table 11.The result shows that reproduction value obtained by Weibull is minimum, GEV takes second place.
The K-S of Storm Surge Height of Typhoon fitting of distribution at 10 sulphur small stream river mouth of table is examined and sum of squares of deviations
The reproduction value (m) that Storm Surge Height of Typhoon Poisson Compound Distributions at 11 sulphur small stream river mouth of table calculate
3, the multidimensional that the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon in institute's survey region is established
Poisson multiple malformations；
When constructing the probability correlation model of Nan Kanxi, sulphur small stream and blue three streams of yangsi (Jing-River Point,LI 5) river mouth Storm Surge Height of Typhoon, edge point
Cloth is all selected as Pearson-III distributions, and joint probability distribution is according to Sklar theorems, using 4 kinds of common ternary Copula letters
Number：Clayton Copula, Frank Copula and Gumbel-Hougaard (G-H) Copula.It is examined using K-S, AIC methods
The applicability of model is evaluated, optimal three-dimensional joint ensemble is chosen.
In table 12, cumulative frequency sum of squares of deviations RMES and the AIC value of ternary G-H models are minimum, Frank Copula moulds
Type takes second place.Therefore, it is based on ternary G-H, Poisson three-dimensionals P3-P3-P3 is established to the Storm Surge Height of Typhoon sequence in three river mouths herein
Probability of recombination distributed model, is denoted as P-GH-TriP3.NanDown Xi, the meeting for 5 years one of sulphur small stream and blue three river mouth Storm Surge Height of Typhoon of yangsi (Jing-River Point,LI 5),
10 years one chances, 20 years chances, 50 years chances, 100 years chances and 200 years one joint probability contour surface such as Fig. 7 met.In order to more
The probability contour surface of different reoccurrence is intuitively observed, three side views that it is 50 years the return period that Fig. 8, which gives, indicate three respectively
The side view in the river mouth two-by-two when a river mouth joint probability is 2%, i.e. joint probability isopleth.
The ternary Copula models of 12 3 river mouth Storm Surge Height of Typhoon of table are preferentially
13 3 river mouth 1980-2004 Storm Surge Height of Typhoon of table combines the return period
Table 14 gave under the return period, and each river mouth is surged design value
According to P-GH-TriP3 models, the joint return period of three river mouth history Storm Surge Height of Typhoon is estimated, such as table 13.By in table
As can be seen that in the three river mouth Storm Surge Height of Typhoon combinations that P-GH-TriP3 is obtained, in all 36 typhoons, only 4 typhoons cause
Joint return period surged in three river mouths be more than 10 years, wherein Herb (1996) is maximum intensity typhoon, combines the return period
Reach 66 years.Other 3 typhoons are Nockten (2004), Doug (1994) and Brenda (1985), joint return period point successively
It Wei not be 18 years, 16 years and 12 years.Meanwhile obtaining the Storm events in fixed rendition phase lower three river mouths, the storm in three river mouths
It surges with certain difference.By establishing the multiple river mouth Storm Surge joint ensembles in Taiwan, it can be seen that platform
Wind is little in the risk that the west in TaiWan, China the north, north, three face of east are caused disaster simultaneously, i.e., the model can be unified into more Hekou Areas
Calamity risk is analyzed.Meanwhile the Storm events for obtaining Typhoon Process difference river mouth under the joint return period are surged referring to table 14
Higher estuary region reinforces protection, for disaster area difference estuary region prevent and reduce natural disasters goods and materials allotment provide science according to
According to.
It should be understood that for those of ordinary skills, it can be modified or changed according to the above description,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (7)
- The determination method of a river mouth Storm Surge joint return period more than 1., which is characterized in that include the following steps,S1. it counts in a period of time, the generation frequency of typhoon in institute's survey region, establishes Poisson points that the frequency occurs for typhoon Cloth；S2. the river mouth situation in statistics institute survey region, establish each river mouth caused by typhoon it is maximum surge it is best one-dimensional Edge distribution；S3. the one-dimensional Poisson Compound Extreme Values that the frequency occurs for each river mouth maximum compound typhoon of surging caused by typhoon are established Distribution；S4. the multidimensional that the frequency occurs for all river mouths maximum compound typhoon of surging caused by typhoon in institute's survey region is established Poisson multiple malformations；S5. more river mouth Storm Surge joint return periods are obtained.
- 2. the determination method of multiple river mouth Storm Surge joint return periods according to claim 1, which is characterized in that institute Step S2 is stated to specifically include：S21. the quantity in the river mouth in statistics institute survey region；S22. each river mouth maximum data surged caused by typhoon are collected；S23. suitable distribution linetype is selected to be fitted each river mouth maximum caused by typhoon data of surging；S24. each river mouth maximum best one-dimensional edge distribution surged caused by typhoon is determined.
- 3. the determination method of multiple river mouth Storm Surge joint return periods according to claim 2, which is characterized in that institute It states in step S23, the distribution includes linearly the distribution of Pearson-III types, Weibull distributions, generalized extreme value distribution and logarithm Normal distribution.
- 4. the determination method of multiple river mouth Storm Surge joint return periods according to claim 2, which is characterized in that institute It states in step S24, each river mouth is determined by K-S inspections, observation, the sum of squares of deviations of estimated value and AIC information criterions The maximum best one-dimensional edge distribution surged caused by typhoon.
- 5. the determination method of multiple river mouth Storm Surge joint return periods according to claim 1, which is characterized in that institute Step S4 is stated to specifically include：S41. maximum caused by typhoon surge compound typhoon in all river mouths is established using suitable Copula functions and the frequency occurs Multidimensional Poisson multiple malformation；S42. determine that all river mouths best multidimensional Poisson that the frequency occurs for maximum compound typhoon of surging caused by typhoon is compound The extreme value distribution.
- 6. the joint probability method according to claim 5 for calculating the extreme water level in river mouth harbour, which is characterized in that the step In rapid S41, the Copula functions include normal state Copula, Frank Copula, Clayton Copula and Gumbel- Hougaard(G-H)Copula。
- 7. the joint probability method according to claim 5 for calculating the extreme water level in river mouth harbour, which is characterized in that the step In rapid S34, is examined by K-S and AIC information criterions determine that maximum caused by typhoon compound typhoon of surging in all river mouths is sent out The best multidimensional Poisson multiple malformation of the raw frequency.
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| CN117634325A (en) * | 2024-01-26 | 2024-03-01 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for identifying extremum event of data-limited estuary area and researching composite flood disasters |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115952690A (en) * | 2023-03-10 | 2023-04-11 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for constructing typhoon wind field with long recurrence period |
| CN117634325A (en) * | 2024-01-26 | 2024-03-01 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for identifying extremum event of data-limited estuary area and researching composite flood disasters |
| CN117634325B (en) * | 2024-01-26 | 2024-04-02 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for identifying extremum event of data-limited estuary area and analyzing composite flood disasters |
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