CN106202788A - A kind of tide flood combined probability analysis method based on Copula function and application thereof - Google Patents
A kind of tide flood combined probability analysis method based on Copula function and application thereof Download PDFInfo
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Abstract
The present invention relates to a kind of tide flood combined probability analysis method based on Copula function and application thereof, the purpose of this tide flood analysis method is to provide the flood-control construction foundation of tidal reach, by setting up " tidal level ", " rainfall peak value " and the joint probability distribution function of " single storm ", can reflect that affecting flood facility crosses the function of stream and Regulation capacity characteristic quantity, provides reliable basis for flood-control construction.
Description
Technical field
The present invention relates to combined probability analysis field, especially relate to a kind of tide flood joint probability based on Copula function
Analysis method and application thereof.
Background technology
Sea outfall section is referred to as tidal reach, and so-called tidal reach refers to be pushed up by tide at the lower exit of section
Torr, flow and water level are by the section of tidal effect.Upstream, basin is affected relatively big by Basin Rainfall, and downstream should be held and be let out upstream flood
Water enters river, is affected by the jacking of tidal level again, causes the flood that basin suffers not only to have relation with internal heavy rain, also with
The tidal level met with mutually is closely related.Therefore, in order to reasonably analyze the flood risk in basin, sudden and violent in understanding basin
The probability risk rule that rain meets with tidal level, in research basin, heavy rain just seems particularly significant with the combination of the experience of tidal level.
Tidal reach river complicated movement, and interference factor is numerous, but main by upstream flood and downstream tidal level the two
The impact of factor.To simplify the analysis, the probabilistic risk analysis of experience is mainly with the Joint Distribution of basin heavy rain and flood level as base
Plinth, and they simply have certain contact, dependency is not very strong, and its Joint Distribution can not be simple by marginal distribution phase
Multiplied arriving, this is accomplished by a kind of more perfect theory and analyzes and researches.Copula is theoretical is building multivariate experience event associating
The flexibility advantage possessed during distribution, the flood risk for research tidal reach provides a great convenience, and expands new research
Means.
The method carrying out tidal level and flood combined probability analysis at present has limitation.First, current analysis method is only
It is analyzed only for the water level of upstream and the tidal level in downstream, does not consider the factors such as rainfall duration, only by two dimension
Copula function not can completely analyzes the relation of flood meeting with tide；Secondly, current analysis method first chooses simulation often
Preferably marginal distribution function, carries out combined probability analysis showing preferable marginal distribution by two series, and in fact
Marginal distribution performance well might not determine the optimality of Joint Distribution.
Summary of the invention
The present invention devises a kind of tide flood combined probability analysis method based on Copula function and application thereof, and it solves
Technical problem is that and lack characterizing the single storm of characteristics of rainfall and the comprehensive of rainfall peak value in terms of tide flood combinative analysis at present
Considering, the method simultaneously choosing marginal distribution has limitation, and the best marginal distribution differs and joined the most accurately
Close distribution.In order to solve the technical problem of above-mentioned existence, present invention employs below scheme:
A kind of tide flood combined probability analysis method based on Copula function, comprises the following steps:
Tidal level station that step 1, Analysis on Selecting section are representative and precipitation station, representational tidal level station should be at section
At estuary and obtain its tidal level series materials；Representational precipitation station is positioned to be analyzed the basin, downstream of section and obtains its rainfall
Data；
Step 2, step 1 gained tidal level series materials is carried out consistent correction；
Step 3, each representational precipitation station selected by step 1, use rainfall intensity method, by continuous print rainfall
Time series is divided into catchment, carries out rainfall data segmentation, precipitation time series is divided into different rainfall plays, enters
And add up " single storm " and " rainfall peak value " two characteristic variables characterizing rainfall pattern；
Step 3 gained " single storm " and " rainfall peak value " are sampled by step 4, employing annual maximum design flood: according to not
Same provincial characteristics, as a example by design lasts 720min (i.e. 12h) or 360min (i.e. 6h) or N min, N is natural number, and sampling is every
" single storm " numerical value sample maximum in 1 year and " rainfall peak value " numerical value sample；
Step 5, for maximum " single storm " the numerical value sample in step 4 and " rainfall peak value " numerical value sample, use Thailand
Gloomy polygon method calculates face, basin " single storm " and " rainfall peak value " two characteristic variables；
Step 6, for single storm, rainfall peak value and tidal level series, calculate the marginal probability distribution of each series respectively,
The multiple distribution linetype being chosen in hydrologic(al) frequency analysis carries out curve to " tidal level ", " rainfall peak value " and " single storm " respectively
Matching；
Step 7, use Probability Point according to related-coefficient test method (PPCC), intend excellent sum-of-squares criterion method (RMSE) and plan excellent absolutely
Three kinds of goodness-of-fit test methods of value Criterion Method (MAE) are determined the two kind limits best with each variable data series fit effect
Edge distribution linetype；
Step 8, employing archimedes type Copula family apply wide Frank Copula and AMH Copula
Function builds the joint probability distribution of characteristics of rainfall variable respectively；
Step 9, selection AIC information criterion method (AIC) and sum of deviation square minimum criteria method (OLS) are to Copula function
The goodness of fit is evaluated, and chooses optimal joint probability distribution.
Further, the order of step 2 and step 3 can be replaced, and does not affect the evaluation result in step 9.
Further, the multiple distribution linetype in the hydrologic(al) frequency analysis in step 6 is respectively as follows: P-III type distribution curve
(P3), Lognormal distribution curve (LN2) and generalized extreme value distribution curve (GEV).
Further, due to the two kinds of linear simulations of each variable data series in step 8, so for each
Plant Copula function to need to calculate 8 times.
A kind of application using above-mentioned modification method reduction tide gauge, it is characterised in that: eliminate change by correction
The environment impact on data, reduces the concordance of tide gauge, it is ensured that use tide gauge to carry out hydrologic(al) frequency analysis
Reliability, the tide gauge using revised moon yardstick is that urban flood defence provides reliable foundation.
The present invention can apply on the flood forecasting of tidal reach, and tidal reach refers to the estuary section in river,
The water level of these sections is not only affected by upland water, is also affected by downstream tidal level simultaneously, and the present invention can provide
To the effective reference information of tidal reach flood forecasting.Specifically, on the premise of determining rainfall peak value, calculate time fall
Rainfall more than some numerical value and tidal level more than the simultaneous probability of some tidal level, or on the premise of single storm determines,
Rainfall peak value is more than the simultaneous probability of a certain tidal level more than a certain numerical value and tidal level, and construction and flood for flood control works are pre-
Report provides foundation.
Should tide flood combined probability analysis method based on Copula function have the advantages that
(1) purpose of tide flood of the present invention analysis method is to provide the flood-control construction foundation of tidal reach, by setting up " tide
Position ", " rainfall peak value " and the joint probability distribution function of " single storm ", can reflect affect flood facility cross flow and regulate and store
The function of ability characteristics amount, provides reliable basis for flood-control construction.
(2) present invention sets up three-dimensional Copula function not only for evaluating preferable marginal distribution, but in marginal distribution
Have chosen preferable two kinds of distribution linetypes, set up multiple joint probability distribution by different combinations, further preferably behave oneself best
Construction method, can avoid the shortcoming that preferred marginal distribution cannot obtain good Joint Distribution.
Detailed description of the invention
Below in conjunction with embodiment, the present invention will be further described:
Step 1, representativeness tidal level station, Analysis on Selecting section and precipitation station, tidal level station should be at section estuary and tidal level money
Material is complete；Representative water precipitation station in appropriate basin, the rainfall series length of different precipitation stations is chosen according to basin, downstream size
Should be essentially identical；
Step 2, tide gauge is carried out consistent correction；
Step 3, for each selected precipitation station, use rainfall intensity method, continuous print precipitation time series split
Become catchment, such as the standard according to " rainfall intensity is less than 0.1mm/h, and the persistent period is more than 10h ", carry out rainfall data and divide
Cut, precipitation time series is divided into different rainfall plays, and then 2 features of statistics " single storm " and " rainfall peak value " become
Amount；
Step 4, employing annual maximum design flood are sampled. according to zones of different feature, last 720min (i.e. 12h) with design
Or as a example by 360min (i.e. 6h) etc., sample sample；
Step 5, utilization Thiessen polygon method calculate face, basin " single storm " and " rainfall peak value " 2 characteristic variables；
Step 6, for single storm, rainfall peak value and tidal level series, calculate the marginal probability distribution of each series respectively,
Choose 3 kinds of distribution linetype (P-III type distribution curve (P3), Lognormal distribution curves conventional in hydrologic(al) frequency analysis
(LN2) and generalized extreme value distribution curve (GEV)) respectively " tidal level ", " rainfall peak value " and " single storm " is carried out curve fitting；
Step 7, use Probability Point according to related-coefficient test method (PPCC), intend excellent sum-of-squares criterion method (RMSE) and plan excellent absolutely
3 kinds of goodness-of-fit test methods of value Criterion Method (MAE) are determined the 2 kind edges best with each variable data series fit effect
Distribution linetype；
Assume that optimizing check is as follows:
Probability Point according to related-coefficient test method (PPCC), intend excellent sum-of-squares criterion method (R MSE) and intend excellent absolute value criterion
Method (MAE) all can have a numerical value to the inspection of each matching, and comprehensive analysis is selected for each project fitting degree
Two kinds of good approximating methods.
Such as the tidal level project in the example above, PPCC test value is the bigger the better, RMSE and MAE is the smaller the better.So selecting
LN2 and GEV is as approximating method.Can be seen that distribution linetype exists minimum and maximum test value quantity the most time, then by
Select；Otherwise, then abandon.
In above table " rainfall peak value " and " single storm " due to the method for inspection with the method for inspection of " tidal level " complete phase
With, special its concrete numerical value of omission.In a word, all of space is required for inspection, is all by PPCC, RMSE, MAE tri-kinds inspection
Mode is checked, and principle is the same, and PPCC test value is the bigger the better, RMSE and MAE is the smaller the better.
Step 8, employing archimedes type Copula family apply wide Frank Copula and AMH Copula
Function builds the Joint Distribution of characteristics of rainfall variable respectively, due to the 2 kinds of linear simulations of each series, so for
Each Copula function needs to calculate 8 times；
Below to each project, we represent selected two kinds of approximating methods with A, B
The above-mentioned combination being just by the calculating of Copula Joint Distribution, chooses the associating of optimum by AIC and OLS inspection
Distributed combination mode.
Minimum (OLS) Criterion Method of step 9, selection AIC information criterion method (AIC) and sum of deviation square is to Copula function
The goodness of fit is evaluated.
Above in conjunction with embodiment, the present invention is carried out exemplary description, it is clear that the realization of the present invention is not by above-mentioned side
The restriction of formula, if the various improvement that the method design that have employed the present invention is carried out with technical scheme, or the most improved by this
Bright design and technical scheme directly apply to other occasion, the most within the scope of the present invention.
Claims (5)
1. a tide flood combined probability analysis method based on Copula function, comprises the following steps:
Tidal level station that step 1, Analysis on Selecting section are representative and precipitation station, representational tidal level station should be at section and enters sea
At Kou and obtain its tidal level series materials；Representational precipitation station is positioned to be analyzed the basin, downstream of section and obtains its rainfall money
Material, chooses the precipitation station of respective amount according to the downstream drainage area size analyzing section；
Step 2, step 1 gained tidal level series materials is carried out consistent correction；
Step 3, each representational precipitation station selected by step 1, use rainfall intensity method, by continuous print rain time
Sequences segmentation becomes catchment, carries out rainfall data segmentation, and precipitation time series is divided into different rainfall plays, Jin Ertong
Meter " single storm " and " rainfall peak value " two characterizes the characteristic variable of rainfall pattern；
Step 3 gained " single storm " and " rainfall peak value " are sampled by step 4, employing annual maximum design flood: according to not same district
Characteristic of field, as a example by design lasts 720min (i.e. 12h) or 360min (i.e. 6h) or Nmin, N is natural number, samples in each year
Maximum " single storm " numerical value sample and " rainfall peak value " numerical value sample；
Step 5, for maximum " single storm " the numerical value sample in step 4 and " rainfall peak value " numerical value sample, use Tyson many
Limit shape method calculates face, basin " single storm " and " rainfall peak value " two characteristic variables；
Step 6, for single storm, rainfall peak value and tidal level series, calculate the marginal probability distribution of each series respectively, choose
Multiple distribution linetype in hydrologic(al) frequency analysis carries out curve plan to " tidal level ", " rainfall peak value " and " single storm " respectively
Close；
Step 7, use Probability Point according to related-coefficient test method (PPCC), intend excellent sum-of-squares criterion method (RMSE) and plan excellent absolute value
Three kinds of goodness-of-fit test methods of Criterion Method (MAE) determine that the two kind edges best with each variable data series fit effect divide
Cloth line style；
Step 8, employing archimedes type Copula family apply wide Frank Copula and AMH Copula function
Build the joint probability distribution of characteristics of rainfall variable respectively；
Step 9, selection AIC information criterion method (AIC) and sum of deviation square minimum criteria method (OLS) matching to Copula function
Goodness is evaluated, and chooses optimal joint probability distribution.
Tide flood combined probability analysis method based on Copula function the most according to claim 1, it is characterised in that: step 2
Can replace with the order of step 3, not affect the evaluation result in step 9.
Tide flood combined probability analysis method based on Copula function the most according to claim 1 or claim 2, it is characterised in that: step
Multiple distribution linetype in hydrologic(al) frequency analysis in rapid 6 is respectively as follows: P-III type distribution curve (P3), logarithm normal distribution song
Line (LN2) and generalized extreme value distribution curve (GEV).
4. according to tide flood combined probability analysis method based on Copula function described in claim 1,2 or 3, it is characterised in that:
Due to the two kinds of linear simulations of each variable data series in step 8, so needing for each Copula function
Calculate 8 times.
5. in any of the one of claim 1-4 based on Copula function tide flood combined probability analysis method should
With, it is characterised in that: on the premise of determining rainfall peak value, calculate single storm and be more than more than some numerical value and tidal level
The simultaneous probability of some tidal level, or on the premise of single storm determines, rainfall peak value is big more than a certain numerical value and tidal level
In the simultaneous probability of a certain tidal level, construction and flood forecasting for flood control works provide foundation.
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| CN107133473A (en) * | 2017-05-09 | 2017-09-05 | 河海大学 | Hydrologic design values method of estimation in two variable hydrologic(al) frequency analysis under a kind of changing environment |
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| CN107423546A (en) * | 2017-04-18 | 2017-12-01 | 武汉大学 | Multivariable hydrological uncertainty processing method based on Copula functions |
| CN108320091A (en) * | 2018-01-26 | 2018-07-24 | 中国海洋大学 | A kind of joint probability method calculating the extreme water level in river mouth harbour |
| CN108596998A (en) * | 2018-04-24 | 2018-09-28 | 江西省水利科学研究院 | A kind of rainfall runoff correlation drawing drawing method based on Copula functions |
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| CN110673230A (en) * | 2019-07-12 | 2020-01-10 | 中山大学 | Entropy decision method based dynamic critical rainfall calculation method |
| CN111831966A (en) * | 2020-05-21 | 2020-10-27 | 中山大学 | Combined river water level forecasting method based on high-dimensional probability distribution function |
| CN112085298A (en) * | 2020-09-23 | 2020-12-15 | 中国电建集团成都勘测设计研究院有限公司 | Non-continuous sequence flood frequency analysis method considering historical flood |
| CN112396297A (en) * | 2020-11-03 | 2021-02-23 | 华中科技大学 | Method and system for analyzing encounter time and magnitude occurrence rule in flood process |
| CN113378389A (en) * | 2021-06-11 | 2021-09-10 | 中国长江三峡集团有限公司 | Uncertainty evaluation method and device for flood encounter combined risk analysis |
| CN114722744A (en) * | 2022-06-08 | 2022-07-08 | 水利部交通运输部国家能源局南京水利科学研究院 | Evaluation method and system for rainstorm and tide level coordination of plain basin design |
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