CN107066425A - Overdetermination amount flood nonuniformity analysis method under a kind of changing environment - Google Patents
Overdetermination amount flood nonuniformity analysis method under a kind of changing environment Download PDFInfo
- Publication number
- CN107066425A CN107066425A CN201710159692.8A CN201710159692A CN107066425A CN 107066425 A CN107066425 A CN 107066425A CN 201710159692 A CN201710159692 A CN 201710159692A CN 107066425 A CN107066425 A CN 107066425A
- Authority
- CN
- China
- Prior art keywords
- flood
- nonuniformity
- threshold value
- sequence
- time
- 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.)
- Granted
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 102
- 238000000034 method Methods 0.000 claims abstract description 91
- 238000005070 sampling Methods 0.000 claims abstract description 12
- 238000011160 research Methods 0.000 claims abstract description 11
- 239000000203 mixture Substances 0.000 claims abstract description 7
- 238000003745 diagnosis Methods 0.000 claims description 4
- 239000004744 fabric Substances 0.000 claims description 4
- 238000003672 processing method Methods 0.000 claims description 3
- 230000009191 jumping Effects 0.000 claims 1
- 230000008859 change Effects 0.000 abstract description 26
- 230000008569 process Effects 0.000 abstract description 20
- 238000010276 construction Methods 0.000 abstract description 3
- 238000011161 development Methods 0.000 abstract description 2
- 238000013461 design Methods 0.000 description 36
- 238000009826 distribution Methods 0.000 description 36
- 230000015572 biosynthetic process Effects 0.000 description 20
- 238000003786 synthesis reaction Methods 0.000 description 19
- 239000013256 coordination polymer Substances 0.000 description 18
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 15
- 238000005452 bending Methods 0.000 description 12
- 238000004364 calculation method Methods 0.000 description 9
- 238000012360 testing method Methods 0.000 description 9
- 238000007476 Maximum Likelihood Methods 0.000 description 8
- 230000000694 effects Effects 0.000 description 8
- 238000000605 extraction Methods 0.000 description 8
- 238000012545 processing Methods 0.000 description 7
- 238000007796 conventional method Methods 0.000 description 6
- 238000005259 measurement Methods 0.000 description 5
- 241000208140 Acer Species 0.000 description 4
- 230000003247 decreasing effect Effects 0.000 description 4
- 230000007774 longterm Effects 0.000 description 4
- 238000006424 Flood reaction Methods 0.000 description 3
- 230000001419 dependent effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 239000006185 dispersion Substances 0.000 description 3
- 239000000284 extract Substances 0.000 description 3
- 238000012821 model calculation Methods 0.000 description 3
- 230000011218 segmentation Effects 0.000 description 3
- 101100326726 Flaveria trinervia PPCC gene Proteins 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 238000010189 synthetic method Methods 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 108091028043 Nucleic acid sequence Proteins 0.000 description 1
- 238000003646 Spearman's rank correlation coefficient Methods 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000407 epitaxy Methods 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 238000005206 flow analysis Methods 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 230000037361 pathway Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000000528 statistical test Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
Classifications
-
- 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
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Software Systems (AREA)
- Computer Hardware Design (AREA)
- Operations Research (AREA)
- Probability & Statistics with Applications (AREA)
- Geometry (AREA)
- Algebra (AREA)
- Life Sciences & Earth Sciences (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Computation (AREA)
- Complex Calculations (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention discloses overdetermination amount flood nonuniformity analysis method under a kind of changing environment, comprises the following steps：Sample is chosen：Sample sequence is screened using the overdetermination amount methods of sampling；Sequence nonuniformity is diagnosed：Judge jump variation and Trend Variation of the sequence with the presence or absence of extraodinary flood, carry out the Flood Frequency Analysis of overdetermination amount using different methods to jump and two kinds of different situations of trend；Overdetermination amount frequency is calculated under changing environment：Consider the overdetermination amount Flood Frequency Analysis of historical flood, the discontinuous POT samples of composition are combined with historical flood according to selected continuous POT samples, Flood Frequency Analysis is carried out to each sample segments sequence；Frequency analysis is carried out based on POT sequences, and consider sequence nonuniformity, flood is reacted in terms of flood magnitude and flood generating process two to change with time feature, propose the new method of research nonuniformity flood, promote the research of the hydrology development law under changing environment, strong reference is provided for hydraulic engineering construction.
Description
Technical field
The present invention relates to Flood Frequency Analysis technical field, more particularly, to overdetermination amount flood under a kind of changing environment
Nonuniformity analysis method.
Background technology
Under climate change and the effect of human activity, numerous rivers hydrologic regimes there occurs significant changes, the water of flood drought
Literary extreme value event takes place frequently, and the environmental background " uniformity " of numerous river flood sequence formation has not existed in the world, passes
" extreme value theory " of system extreme value flow analysis need correct non-stationary to adapt to sequence.Using existing project water price analysis side
River basin development utilizing works, flood control and drought resisting engineering and its traffic control that method is designed etc., will face what is brought by changing environment
The risk of design frequency distortion.
Flood Frequency Analysis method is using general cloth fitting observation extreme value, so as to be specified or the design of average recurrence period is big vast
Water, is that WR project plan and operation provide system foundation, and the existing last 100 yearses history of its application.Estimated by Flood Frequency Analysis
The greatest problem that meter engineering sets flood presence is that observational data is too short, and available Flood Information is not enough.Tradition obtains flood letter
The method of breath is year maximum (Annual Maximun Series, AMS), but using AMS samplings, can be ignored after changing environment
Year in second, third big flood peak, although they are generally more much greater than flood magnitude before changing environment.Overdetermination amount (Peak-
Over-Threshold, POT) model considers overdetermination amount year frequency distributed model and overdetermination amount distributed model simultaneously, than
AMS methods can it is more complete, flood and its generation process are described for greater flexibility.Therefore, POT models can be used as a kind of suitable changing environment
Frequency analysis method.POT sampling, which is chosen, exceedes all flood peaks of threshold value for sample in field data, can obtain than traditional
Year more Flood Information amounts of maximum (AMS) sequence, effectively improve Design Flood Calculation precision.Statistical test shows, adds
The historical flood return period of calculating is longer, more beneficial to improving frequency analysis precision and stability.Consider the POT floods of historical flood
Water frequency analysis, can make Flood Information amount using maximization in terms of actual measurement and textual criticism data two, improve design flood precision, tool
There is larger researching value.Existing part in POT methods on considering the research of historical flood at present, but only considers in continuous sample
A textual criticism phase historical flood is added in this, does not consider there is a situation where to be grouped historical flood；Data used are more to be tried by counting
Test actual measurement and the textual criticism data of acquisition rather than particular station.For specific Watershed Analysis historical flood to POT Flood Frequency Analysis
The research of influence is less.In actual applications, the historical flood investigated there may be multiple textual criticism phases, need to consider to be grouped history
The processing of flood.Therefore, influence of the research packet historical flood to POT methods, the applicability to improving POT Flood Frequency Analysis
It is significant.The frequency meter of nonuniformity (non-stationary) Hydrologic Series an emerging research topic, correlative study at last
Achievement is quite few.Domestic more common method be based on reduction/also show approach, mainly include：Before and after change point it is serial with it is a certain
The decomposition of the relation analysis, time series of parameter and synthetic method and 3 kinds of hydrological model.But the equal Shortcomings of the above method,
Decomposition and synthetic method such as time series is in the case of time span of forecast is longer, and existing certainty ingredient prediction method is difficult to make us letter
Take and there is larger extension risk；The certainty composition of Hydrologic Series, mould are separated from causal pathway by setting up hydrological model
The calibration of many parameters of type is confined to the basin physical condition in history a certain period.As whole world change influences on hydrologic process
Study on Problems is goed deep into, changing environment cause it is non-stationary under the conditions of hydrological frequency research in recent years especially paid close attention to.Pin
It is non-stationary to Hydrologic Series, it can set up and be estimated based on time-varying statistical parameter non-stationary series.It is external at present non-stationary
Flood Frequency Analysis common method mainly has：Flood Frequency Analysis is collected in time change square (TVM), region, and local likelihood method divides
Digit recurrence and Mixture Distribution Model etc..Due to non-stationary Flood evolution statistical parameter (such as average value and standard deviation) and point
Itself moment of cloth line style changes, and the uncertainty of respective design flow will also change.In this regard, Strupczewski etc.
The TVM models of the non-stationary extreme value sequence of processing are proposed, the model considers the tendency of statistical parameter average and variance, can obtain
Design load changes with time relation.Strupczewski etc. proposes the TVM based on POT sequences by taking Poisson-exponential distribution as an example
Frequency analysis model, it is considered to POT frequency sequence first moments and POT sequences one, the tendency of second moment, with the square of sequence
Descriptive model distributed constant, and according to POT models and the corresponding relation of AMS models, respectively with year frequency and POT flood peak sequences
Row one, second order when bending moment AMS model profile parameters are described, changed with time relation so as to obtain design load.Based on POT sequences
Row non-uniform frequency analysis model can not only crest discharge change over time trend, moreover it is possible to reflect the change of flood frequency
Trend, can react flood and changes with time feature preferably in terms of magnitude and process two.The propositions such as Strupczewski
TVM models based on POT sequences, use fixed threshold value, and Kysely etc. is when used time bending moment analyzes temperature nonuniformity
Proposition realizes threshold value time-varying based on Technologies on Quantile Regression, and the POT sequence year frequencies obtained using this method meet one
Cause property is assumed.Hereafter, TVM methods are successfully applied to other areas by scholar, also obtain under certain standard P, flood design load XP
There is significant changes relation with the time.
The content of the invention
The technical problems to be solved by the invention be overcome available Flood Information not enough and flood extreme value sequence not
Meet uniformity to assume to carry out Flood Frequency Analysis using TVM models based on POT sequences there is provided one kind, and consider sequence non-one
Cause property, from flood magnitude and flood generating process two in terms of reacts flood and changes with time feature, proposition nonuniformity flood
The new method of frequency analysis.For there is extraodinary flood jump in overdetermination amount flood peak sequence, historical flood pair is inquired into
The influence of overdetermination amount Flood Frequency Analysis result；For super Quantitative Sequence there is a situation where trend time-varying, by based on when bending moment
Nonuniformity Flood Frequency Analysis method is applied to the analysis of overdetermination amount sample, realizes the methods of sampling of threshold value time-varying in flood
Application in frequency analysis.
In order to solve the above technical problems, technical scheme is as follows：Overdetermination amount flood non-one under a kind of changing environment
Cause property analysis method, comprises the following steps：
Sample is chosen：Consider that historical flood carries out Flood Frequency Analysis, threshold value is determined, using the overdetermination amount methods of sampling pair
Sample sequence is screened；
Sequence nonuniformity is diagnosed：Jump variation and Trend Variation of the sequence with the presence or absence of extraodinary flood are judged, to jump
The Flood Frequency Analysis of overdetermination amount is carried out using different methods with two kinds of different situations of trend；
Overdetermination amount frequency is calculated under changing environment：The overdetermination amount Flood Frequency Analysis of historical flood is considered, according to selected
Continuous POT samples, the discontinuous POT samples of composition are combined with historical flood, Flood Frequency Analysis is carried out to each sample segments sequence；
GP distributed constants are estimated using maximum-likelihood method, each sequence fit goodness and return period Design Flood Calculation result is obtained.Non- one
Cause property overdetermination amount Flood Frequency Analysis, is analyzed the maximum daily flow sequence of nonuniformity year using TVM models, passed through
The Long-term change trend and phase change feature of Mann-Kendall (M-K) methods and CSDMC method diagnosing sequences can be selected as foundation
The time origin of TVM methods is selected, the distribution of corresponding AMS models is finally derived, AMS sequences is fitted and carries out nonuniformity flood
Water frequency analysis.Fitting AMS sequences simultaneously carry out nonuniformity Flood Frequency Analysis.
In a kind of preferred scheme, the threshold value is true according to criterion of independence and overdetermination amount threshold value selection standard
It is fixed.Threshold value assumes common according to the serial frequency distribution of overdetermination amount, the distribution of overdetermination amount flood frequency and independent same distribution
It is determined that, the value model of threshold value is determined using overdetermination amount sample average method, dispersion index method, average annual overdetermination amount frequency μ methods
Enclose.
In a kind of preferred scheme, the sequence nonuniformity diagnosis is, using the analysis of M-K trend tests method, to judge flood
The tendency of water sequence and jump.
In a kind of preferred scheme, different Flood Frequency Analysis methods is used to different Flood evolutions.Time-varying door
The frequency analysis method of limit value refers to：Consider the temporal change characteristic of threshold value, overdetermination amount sample is extracted using the threshold value of time-varying
This, obtains the POT frequency sequences for meeting uniformity hypothesis.After POT samples are obtained using time-varying threshold value, it is considered to
POT sequences one, the tendency of second moment, are distributed using Poisson-GP, used time bending moment descriptive model distributed constant, carry out thresholding
The overdetermination amount Flood Frequency Analysis of value and POT sample moment time-varying.
In a kind of preferred scheme, described Flood Frequency Analysis method include fixed threshold value time-varying Moment Methods and when
Become threshold value time-varying Moment Methods.
In a kind of preferred scheme, the threshold value that the fixed threshold value time-varying Moment Methods are uniquely fixed for determination,
Different probability distribution are selected in Flood Frequency Analysis, it is considered to which two rank squares difference trend construction different TV M models is non-before sequence
Consistency processing method.TVM models consider the trend of the rank square of flood time series first, second (average m and standard deviation sigma) into
Point, the initial parameter used time bending moment of distribution is represented, the parameter to probability density function is estimated.Should maximum-likelihood method
With on the Flood evolution for meeting independence requirement, it is assumed that it is only there is trend because of sequence to cause sequence to be unsatisfactory for independence,
This trend is considered in a model.Finally with discrimination standard of the AIC criterion as optimal models.
In a kind of preferred scheme, the time-varying threshold value time-varying Moment Methods are by the nonuniformity research time-varying of temperature
Threshold value is applied in the extraction of flood overdetermination amount sample, and time-varying threshold value is calculated using regression quantile, and according to basin water
The storehouse situation of regulating and storing determines sectional door limit value, and the nonuniformity of flood frequency is considered in sampling.
Compared with prior art, the beneficial effect of technical solution of the present invention is：
(1) packet is gone through when being applied to there is extraodinary flood in overdetermination amount frequency analysis, analysis field data by historical flood
Influence of the history flood to POT Flood Frequency Analysis results.
(2) by based on when bending moment non-uniform Flood Frequency Analysis application super quantitative approach in, compared with annual maximum design flood,
Nonuniformity overdetermination amount Flood Frequency Analysis can reflect the variation characteristic for occurring flood generating process and flood magnitude simultaneously.
(3) sample is extracted using fixed threshold value more than nonuniformity overdetermination amount Flood Frequency Analysis, herein by with temperature
Nonuniformity research time-varying threshold value is applied in the extraction of flood overdetermination amount sample, and time-varying thresholding is calculated using regression quantile
Value, and sectional door limit value is determined according to basin Reservoir Operation situation, the nonuniformity of flood frequency is considered in sampling.
Brief description of the drawings
Fig. 1 is model framework figure of the present invention.
Fig. 2 chooses schematic diagram for the POT samples of the embodiment of the present invention 1.
Fig. 3 diagnoses schematic diagram for the sequence nonuniformity of the embodiment of the present invention 1.
Fig. 4 is the system block diagram of the embodiment of the present invention 1.
Fig. 5 is the station time-varying threshold value of Dong Jiang three and crest discharge of the embodiment of the present invention 2.
Fig. 6 is the station sectional door limit value of Dong Jiang three and crest discharge of the embodiment of the present invention 2.
Fig. 7 is POT flood frequency curve situation of change of the station of Dong Jiang three based on time reference point of the embodiment of the present invention 2.
Embodiment
Accompanying drawing being given for example only property explanation, it is impossible to be interpreted as the limitation to this patent；
In order to more preferably illustrate the present embodiment, some parts of accompanying drawing have omission, zoomed in or out, and do not represent actual product
Size；
To those skilled in the art, it is to be appreciated that some known features and its explanation, which may be omitted, in accompanying drawing
's.
Technical scheme is described further with reference to the accompanying drawings and examples.
Embodiment 1
As shown in figure 1, overdetermination amount flood nonuniformity analysis method under a kind of changing environment, comprises the following steps：
Sample is chosen：Consider that historical flood carries out Flood Frequency Analysis, threshold value is determined, using the overdetermination amount methods of sampling pair
Sample sequence is screened；
Sequence nonuniformity is diagnosed：Jump variation and Trend Variation of the sequence with the presence or absence of extraodinary flood are judged, to jump
The Flood Frequency Analysis of overdetermination amount is carried out using different methods with two kinds of different situations of trend；
Overdetermination amount frequency is calculated under changing environment：The overdetermination amount Flood Frequency Analysis of historical flood is considered, according to selected
Continuous POT samples, the discontinuous POT samples of composition are combined with historical flood, Flood Frequency Analysis is carried out to each sample segments sequence；
GP distributed constants are estimated using maximum-likelihood method, each sequence fit goodness and return period Design Flood Calculation result is obtained.Non- one
Cause property overdetermination amount Flood Frequency Analysis, is analyzed the maximum daily flow sequence of nonuniformity year using TVM models, passes through M-K
The Long-term change trend and phase change feature of method and CSDMC method diagnosing sequences can select the time base of TVM methods as foundation
Point, finally derives the distribution of corresponding AMS models, is fitted AMS sequences and carries out nonuniformity Flood Frequency Analysis.Fitting
AMS sequences simultaneously carry out nonuniformity Flood Frequency Analysis.
In specific implementation process, the threshold value is determined according to criterion of independence and overdetermination amount threshold value selection standard.
Threshold value assumes common true according to the serial frequency distribution of overdetermination amount, the distribution of overdetermination amount flood frequency and independent same distribution
It is fixed, the span of threshold value is determined using overdetermination amount sample average method, dispersion index method, average annual overdetermination amount frequency μ methods.
In specific implementation process, the sequence nonuniformity diagnosis is, using the analysis of M-K trend tests method, to judge flood
The tendency of sequence and jump.
In specific implementation process, different Flood Frequency Analysis methods is used to different Flood evolutions.Time-varying thresholding
The frequency analysis method of value refers to：Consider the temporal change characteristic of threshold value, overdetermination amount sample extracted using the threshold value of time-varying,
Obtain the POT frequency sequences for meeting uniformity hypothesis.After POT samples are obtained using time-varying threshold value, it is considered to POT sequences
The tendency of row one, second moment, is distributed using Poisson-GP, used time bending moment descriptive model distributed constant, carry out threshold value and
The overdetermination amount Flood Frequency Analysis of POT sample moment time-varying.
In specific implementation process, described Flood Frequency Analysis method includes fixed threshold value time-varying Moment Methods and time-varying
Threshold value time-varying Moment Methods.
In specific implementation process, the fixed threshold value time-varying Moment Methods is determine uniquely fixed threshold value, in flood
Different probability distribution are selected in water frequency analysis, it is considered to non-the one of two rank squares difference trend construction different TV M models before sequence
Cause property processing method.TVM models consider the trend of the rank square of flood time series first, second (average m and standard deviation sigma) into
Point, the initial parameter used time bending moment of distribution is represented, the parameter to probability density function is estimated.Should maximum-likelihood method
With on the Flood evolution for meeting independence requirement, it is assumed that it is only there is trend because of sequence to cause sequence to be unsatisfactory for independence,
This trend is considered in a model.Finally with discrimination standard of the AIC criterion as optimal models.
In specific implementation process, the time-varying threshold value time-varying Moment Methods are by the nonuniformity research time-varying door of temperature
Limit value is applied in the extraction of flood overdetermination amount sample, and time-varying threshold value is calculated using regression quantile, and according to basin reservoir
The situation of regulating and storing determines sectional door limit value, and the nonuniformity of flood frequency is considered in sampling.
In specific implementation process, it is considered to which the course of work of the overdetermination amount Flood Frequency Analysis of historical flood is as follows：
1. overdetermination amount Flood Frequency Analysis.If POT frequencies obey Poisson distributions, the probability in year frequency m
For：In formula, m is year frequency, and λ is Poisson distributed constants, the mathematics of Poisson distributions
Expect E (m)=λ.GP distributions are obeyed in the distribution of overdetermination amount flood frequency, and the condition of Poisson distribution is obeyed in overdetermination amount frequency
Under, then crest discharge x return period T (x) is：μ is annual overdetermination amount frequency in formula, and F (x) is
X is no more than probability.
2. flood peak independence and threshold value are chosen.The premise of overdetermination amount Flood Frequency Analysis is that flood peak sample has independently
Property.This model uses the independent flood peak discrimination standard that American Water Resource Association (USWRC) proposes.Two continuous flood peaks are chosen simultaneously
Condition be θ ＞ 5+ln (A) and XminIn ＜ 0.75min [Q1, Q2], formula, θ be two peak-to-peak interval times (my god)；A is stream
Domain area, Mile2；Qi is the maximum daily flow of i-th flood.It is unsatisfactory in the continuous flood peak of above-mentioned condition, only takes wherein most
A big flood peak.Threshold value is according to the serial frequency distribution of overdetermination amount, the distribution of overdetermination amount flood frequency and independent same distribution
Assuming that common determine.Threshold value is determined using overdetermination amount sample average method, dispersion index method, average annual overdetermination amount frequency μ methods
Span.
3. parameter Estimation.This model uses Maximum-likelihood estimation, under the conditions of a textual criticism phase historical flood, if the textual criticism phase
For N, there are k historical floods in year in the time (N-S) without field data, wherein minimum historical flood is X0, for textual criticism
The data of unknown flood discharge in phase, but its known flow is less than the minimum flood in the textual criticism phase in known historical flood, with not
Represented more than probability, it is known that the historical flood of flow represents that then log-likelihood function is with probability density function：
In formula, h=μ * (N-S) are that (N-S) of no field data exceedes the flood quantity of threshold value in year；Xi is actual measurement
Flood, yj is historical flood, and remaining parameter meaning is the same.
4. the test of fitness of fot.Using based on criterion from (residual) poor quadratic sum minimum criteria (OLS) and Probability Point according to phase
The goodness of fit of relation number (PPCC) evaluation model.PPCC test statistics：
In formula, x(i)And xmThe average of the measured value after sequence and actual measurement sample is represented respectively；y(i)And ymAssume that respectively point
Cloth is relative to x(i)Theoretical value and average, in theory, y(i)=E (x(i)), ym=xm。
OLS is examined：
In formula, PiFor corresponding to x(i)Empirical Frequency, f (Pi, θ) and it is frequency curve ordinate, other specification meaning is the same.
5. trend test.Using Spearman rank correlation coefficient method test samples tendencys.Statistic ZSPReceived with n increase
Hold back in standardized normal distribution.If data xi is sorted in ascending order, ZSP>0, show that sequence is on the rise；ZSP<0, show sequence
Show downward trend；If sorting in descending order, conversely.|ZSP|≤Zα/2, then null hypothesis, i.e. trend are received not notable；Otherwise, become
Gesture is notable.α is significance Z0.05/2=1.96.
In specific implementation process, based on when bending moment nonuniformity overdetermination amount Flood Frequency Analysis the course of work such as
Under：
1. Flood evolution nonuniformity is diagnosed.Utilize Cumulative Sum of Departures of
ModulusCoefficient (CSDMC) detects crest discharge changes phase feature, and this method can reflect sequence time change
Detailed information.Flood time series trend feature is analyzed using M-K trend tests method.
The conversion of 2.POT models and AMS models.Using Poisson fitting of distribution overdetermination amounts flood year frequency sequence,
With the super Quantitative Sequence of GP fittings of distribution, POT models are described using Pareto-Poisson distributions, then corresponding AMS sequences are obeyed
GEV is distributed.The parameter of POT models and AMS models is changed, for xx0, parameter k*, α *, ξ * of AMS sequences GEV distributions
It is distributed with POT sequences Pareto-PoissonParameter lambda, α, k, conversion
Relation is：ξ*=ξ+α ln (λ) α*=α k*=k ≠ 0
α is the scale parameter that GP is distributed, and k is form parameter；K* is that AMS form parameters, α * are that AMS scale parameters, ξ * are
AMS location parameters.
3. time-varying Moment Methods.The trend components pair of the rank square of flood time series first and second are considered in Flood Frequency Analysis
Sequence carries out nonuniformity processing.
The specific implementation method of time change Moment Methods is：
Bending moment model when 3.1..If the probability density function of distribution is f=f (x；P), wherein, p is distributed constant, and preceding
The relation of two rank squares is p=p (m, σ), then probability density function is f=f (x；m,σ).Wherein m, σ are the sample for considering trend components
This square, it is relevant with the time, there are m=m (t；θ(m)) and σ=(t；θ(σ)), use θ(m)And θ(σ)M and σ parameter vector is represented respectively, then
Parameter p is p=p (t；θ), θ is by θ(m)、θ(σ)The parameter matrix of composition.Distributed constant vector p is converted to by time-varying moments method
M and σ parameter vector θ(m)、θ(σ), i.e. f=f (x, t；θ).
3.2. trend model.The trend that second moment is present before sample is stated with simple continuous function, it is considered to existed linear
The situation of trend and parabola trend, analyzes m- trend species at six kinds altogether：1. average has linear trend (AL)；2. mark
Quasi- difference has linear trend (BL)；3. the linear trend of average, standard deviation, and with a fixed value (variation coefficient Cv) for ratio
Related (CL)；4. average and standard deviation all have linear trend, and uncorrelated (DL)；5. average has parabola trend
(AP)；6. average, standard deviation have parabola trend, and are that ratio is related (CP) with a fixed value (variation coefficient Cv).In flood
Consider that the trend components of the rank square of flood time series first and second carry out nonuniformity processing to sequence in water frequency analysis.Also
A kind of stable state situation (S), it is assumed that it is stable that Long-term change trend, i.e. distributed constant is not present in sample moment.POT models need what is considered
There are two sequences, one is the overdetermination amount year frequency sequence for using Poisson fittings of distribution, and one is to use GP fittings of distribution
In overdetermination amount Flood evolution, two sequences there is trend in any one sequence, will all influence the parameter meter of AMS models GEV distributions
Calculate result.Due to the mathematic expectaion that Poisson distributed constants λ is overdetermination amount year frequency sample, therefore overdetermination amount year generation is secondary
Number Sequence need to only consider the trend of first moment；The trend of second moment before POT sequences consider.Two sequences are taken into consideration, can derive
A variety of trend models, this model considers 15 kinds altogether, and model name " ALS " represents that overdetermination amount year frequency sample average has line
Property trend, second moment does not have trend before overdetermination amount Flood evolution, and " SAL " represents overdetermination amount year frequency sample average not
With trend, overdetermination amount Flood evolution average has linear trend, and remaining model is similarly.Second moment before each trend model sample
Expression formula and model increase number of parameters refer to the expression formula of each rank square of trend model two of table 1.
3.3. parameter Estimation.Estimate parameter using maximum-likelihood method, parameter estimation result is to take log-likelihood function lnL
Parameter matrix g and h during maximum, POT model parameters when thus calculating each time reference point t, further according to POT models and AMS
Model dependency relation calculates corresponding GEV distributed constants.
3.4. optimal trend model selection.This model using based on principle of maximum entropy AIC criterion as optimal trend model choosing
Select standard.The criterion considers two parts content, and one is fitting effect of the model to sample, is reacted with likelihood function value；Two be mould
Type stability, is punished to realize by the number of parameters to model.Final choose is fitted preferably and number of parameters to data
Model as few as possible is optimal models.Increase model parameter can improve the fitting effect to sample, but probably due to undue strong
Tune reduces curve epitaxy to the fitting effect of sample, due to epitaxial part of the Flood Frequency Analysis more concerned with curve, so
In model selection, should try one's best reduced parameter.AIC criterion can verify the significance of difference between different models, and choosing comprehensively mould
Relation between type applicability and number of parameters, it is simple, objective to calculate.Calculation formula：In AIC=-2lnML+2k, formula, ML is
The maximum of likelihood function, is the corresponding likelihood function value of maximum likelihood parameter estimation result；K is model parameter number.AIC values
Minimum trend model is optimal models.
3.5. sequence is reconstructed.Estimated with maximum-likelihood method POT models GP-Poisson distribution when bending moment parameter after, just
Desirable arbitrary year (t0) as the benchmark reference time, by the way that actual measurement sequence to be converted to the sequence under stable condition more than probability
Row.
The expression formula of each rank square of trend model two of table 1.
In specific implementation process, it is considered to which the course of work of the overdetermination amount Flood Frequency Analysis of time-varying threshold value is as follows：
1. time-varying threshold value is estimated.
1.1 estimate time-varying threshold value by Quantile Regression, and it is time-varying door that the High Quantiles that variable is distributed intuitively are taken naturally
Limit value carries out super quantitative analysis.Quantile estimate estimation passes through
Complete minimum value linear programming.In formula, θ is the fractile to be estimated, represents the number below the tropic or regression surface
According to the percentage for accounting for all data, θ ∈ (0,1)；β is the coefficient vector changed with θ, and β (θ) is called θ recurrence point
Digit；yiFor dependent variable vector, xiFor independent variable vector.Using crest discharge correspondence year as independent variable, crest discharge is dependent variable,
Quantile estimate estimation is carried out to determine time-varying threshold value.Overdetermination is tentatively first extracted with larger average annual overdetermination amount frequency μ
Flood peak is measured as dependent variable, quantile is determined further according to required average annual frequency, quantile estimate estimation is finally carried out, is located at
Crest discharge on the tropic is the POT flood peak sequences obtained according to time-varying threshold value.
1.2 determine sectional door limit value according to valley environment variation characteristic.Measured discharge data are divided with different time interval,
Overdetermination amount sample is individually extracted by giving average annual frequency in each time phase, so that it is determined that respective stage threshold value.When
Between divided stages can be according to mankind's activity such as land use, Influence of Water Conservancy Projects and the climate change of each hydrometric station control catchment
Feature determines that the threshold value thereby determined that can reflect valley environment variation characteristic.In addition, also can first be carried using fixed threshold value
POT samples are taken, are determined by the phase change feature for analyzing overdetermination amount year frequency sequence.
2. the overdetermination amount flood frequency distribution of threshold value time-varying.If X*=(x1* ..., xi* ..., xn*) represent to use time-varying
The overdetermination amount crest discharge sequence that threshold value is extracted, n is sequence length；X=(x1..., xi..., xn) represent that crest discharge exceedes
The part of threshold value；S=(s1..., sj..., sN) it is each year threshold value, N is year；Then xi=xi*-sj, j is xiPlace year.
It is X to remember POT sequences, for when bending moment analysis for sequence X one, second moment.Sample X obeys GP distributions.Because X is overdetermination amount
The super thresholding part of flood peak, therefore the location parameter ζ of GP distributions is 0.The meter of the return period T super thresholding value part x (T) of synthesis design
Calculating formula is：Because each year threshold value is different, therefore correspondence X* actual design flood every year
Peak value X* (T) is relevant with threshold value then, and calculation formula is：xj* (T)=sj+x(T)。
3. time change Moment Methods.Specific implementation method is identical with the overdetermination amount Flood Frequency Analysis for considering historical flood.
Embodiment 2
As shown in figures 1-4, overdetermination amount flood nonuniformity analysis system under a kind of changing environment, including：Sample analysis is gone
Overdetermination amount frequency analysis method (TVM frequency analysis moulds under the diagnosis of (POT overdetermination amounts sampling), sequence nonuniformity, changing environment
Type).
The course of work that overdetermination amount flood nonuniformity is analyzed under changing environment is as follows：
1. needed for data
As shown in figure 5, accounting for the overdetermination amount of threshold value time-varying by taking Dongjiang basin Longchuan, riverhead, the station of Boluo three as an example
Flood Frequency Analysis, it is discharge process day by day that each hydrometric station, which is used for the data of crest discharge sample extraction,.Flowed day by day according to each station
Amount process, extracts independent flood peak sequence, and overdetermination amount flood peak is tentatively first extracted with average annual overdetermination amount frequency μ=10 is used for time-varying
The determination of threshold value and the extraction of POT samples.It is the average annual overdetermination amount frequencies of POT to take μ=2.5, then using regression quantile
When estimating time-varying threshold value, it is 75% to determine quantile, and the crest discharge more than the tropic is the POT floods finally obtained
Peak.During using sectional door limit value, according to it is each station upper pond start storage time divide time phase, in each time phase with
The stage extraction POT sequences of μ=2.5.Fengshuba Reservoir starts retaining in October, 1973, therefore Longchuan station is divided into 1954-1973
Year and -2009 years two stages in 1974；Riverhead station is influenceed by maple dam, Xinfengjiang Reservoir, before Xinfengjiang Reservoir influence
Time-nineteen fifty-nine in 1954 stage it is too short, be not segmented individually, thus riverhead station segmentation it is identical with Longchuan station；Remove by new at Boluo station
Feng Jiang, the influence of maple dam are outer, the Baipenzhu reservoir of also western Zhijiang, therefore divide three time phases：- 1973 years 1954,
- 1984 years 1974, -2009 years 1985.
2. determination and the POT sample extractions of time-varying threshold value
The time-varying threshold value that 2.1 regression quantiles are determined
POT sequences are tentatively extracted based on daily flow sequential extraction procedures independence flood peak, and with average annual frequency μ=10 of POT, with
75% regression quantile of the POT sequences is the POT flood peak samples that threshold value extracts threshold value time-varying, the flood peak sequence thus extracted
The average annual frequency μ=2.5, Fig. 5 of POT of row are the crest discharge that each station μ=10 are extracted and corresponding 75% percentile door
Limit value, the crest discharge more than time-varying threshold value curve is the POT sequences extracted according to time-varying threshold value.
2.2 sectional door limit values
As shown in fig. 6, starting storage time according to each hydrometric station upstream storehouse, POT sequences are extracted to daily flow sequence segment,
The average annual frequency μ of POT take 2.5, Fig. 6 to be the crest discharge and day part threshold value that each station μ=10 are extracted in day part, are located at
Crest discharge more than threshold value curve is the POT sequences extracted according to time-varying threshold value.
2.3 sequence nonuniformities are diagnosed
The POT sequences and corresponding POT sequences frequency sequence extracted using time-varying threshold value are entered using M-K methods
Row trend test.5% significance is taken according to M-K assays, the POT samples extracted using linear time-varying and sectional door limit value
This, corresponding year frequency sequence does not have notable trend, it is seen that the overdetermination amount sample extracted based on time-varying threshold value
Year frequency sequence meets uniformity hypothesis.Longchuan and riverhead station POT sequences, which have, is remarkably decreased trend, Boluo station POT sequences
Row have downward trend, but not up to 5% significance.
The M-K of POT frequency sequences acquired in contrast quantile estimate threshold value and sectional door limit value examines knot
Fruit understands that Longchuan, riverhead station use year genetic sequence row trend during quantile estimate threshold value smaller, and Boluo station is using segmentation
Year frequency Sequence Trend is smaller during threshold value.When therefore accounting for the overdetermination amount Flood Frequency Analysis of a square, Longchuan, river
Source station returns the POT sequences that threshold value is extracted using digit, and Boluo station uses the POT sequences that sectional door limit value is extracted.
2.4 optimal trend model selections
According to AIC criterion choose the station of Dong Jiang three obtained by time-varying threshold value POT serial means, standard deviation optimal trend
Model, it is excellent trend to choose the minimum model of AIC values, and Longchuan, riverhead Boluo station are that CP trend is optimal, i.e., POT serial means,
Standard deviation is parabola trend, and with fixed proportion (CV) correlation.3. the corresponding rule of line style and synthesis design stream under changing environment
Amount change
Flood line style response pattern under 3.1 changing environments
Influenceed by Reservoir Operation, Longchuan, riverhead Boluo station according to time-varying threshold value extract POT crest discharges still suffer from down
Drop trend.To study the situation of different changes phase flood frequency curves, analysis hydraulic engineering (mainly retaining) is to design flood
The influence of peak flow, the POT serial means obtained according to the AIC criterion selection station of Dong Jiang three by time-varying threshold value, standard deviation are most
Excellent trend model.The POT sequences extracted according to time-varying threshold value are reconstructed into the stable POT sequences under each characteristic time datum mark,
According to basis for selecting selection time datum mark.As shown in fig. 7, drawing flood frequency according to the stable POT sequences of each time reference point
Rate curve, and with not considering that the flood frequency distribution result of POT sequence samples square trend features is contrasted.3 of Longchuan station
Time reference point represent respectively within 1962,1989 and 2009 Fengshuba Reservoir build before, build behind storehouse and present situation situation.Maple
Before dam water regulation effect, time reference point is represented with 1962 Nian Wei：With not considering POT during POT sample moments trend (S models)
And the contrast of GP flood frequency curves, it is that the POT sample points evidence that time reference point is reconstructed is surveying POT sample points according to upper with this year
Side, the high water tail end of GP-CP frequency curves is steeper.In stage after being built up with 1989 and 2009 chronological table Fengshuba Reservoirs, this two
Individual time origin, corresponding GP-CP curve locations were below GP-S curves, it is seen that reduce with magnitude flood probability of happening, explanation
Longchuan's station overdetermination amount flood peak is cut the obvious GP-CP curves in 2009 of function influence above curve in 1989 by Reservoir Operation, but
Correspondence threshold value is less than 1989 within 2009, therefore the relation of the two time point specified value synthesis design magnitudes needs further
Analysis.
4 time reference points at riverhead station are 1956,1966,1989 and 2009.Storehouse is built in Xinfengjiang Reservoir
Before, riverhead station flow is not by water regulation effect, and 1956 year datum marks reconstruct POT sequences and GP-CP curves are located at each time
The top of basic point frequency, big magnitude flood occurs general larger.Before Xinfengjiang Reservoir retaining, maple Ba Ku are built, adjusted by Xinfengjiang
Influence is stored, the GP-CP curves of 1966 year basic points have declined.After Fengshuba Reservoir is built up, influenceed by two big reservoir fillings,
The frequency curve of 1989 and 2009 is below GP-S curves, and great flood probability of occurrence is remarkably decreased.GP-CP songs in 2009
Line is located above curve in 1989, but correspondence threshold value in 2009 is less than 1989.The frequency of riverhead station different time datum mark
Curvilinear motion rule is similar with Longchuan station.
5, Boluo station time reference point is respectively 1956,1966,1978,1994 and 2009.1956,
The high water afterbody of GP-CP frequency curves of 1966 and 1978 gradually tends towards stability, and curve location moves down the frequency of wherein 1966
Rate curve is more similar to GP-S curves.Several time dot frequency variation characteristics show that great flood probability of occurrence is remarkably decreased above.
GP-CP curves were almost overlapped with 1978 within 1994, but correspondence threshold value in 1994 is less than 1978, therefore great flood in 1994 goes out
Existing probability is less than 1978.Frequency curve is located above curve in 1994 within 2009, and two time reference points correspondence threshold value is identical
Therefore above year curve top, the identical event year curve of two time reference points correspondence threshold value, two time reference points correspondence threshold value phase
Together, thus great flood probability of occurrence in 2009 is more than 1994, need further analysis with the relation of other times point design load.
3.2 synthesis design changes in flow rate features
Consider after threshold value time-varying and POT serial means, standard deviation variation tendency, the synthesis design flow of specified value is
The amount changed over time, to inquire into influence of the changing environment to crest discharge design load, respectively stands optimal based on above selected herein
1954~2009 years processes that change with time of crest discharge (are met within 100 years one) under trend model, analysis indication standard.
Stable model, i.e. threshold value are fixed and not considered under overdetermination amount sample moment time dependant conditions, and Longchuan stands 100 years one and meets flood
Peak flow is 7141m3/s.After considering threshold value linear time-varying and POT sample moments with CP trend time-varying, over time, Longchuan
100 years one chance synthesis design flows of standing first reduce, and amplitude of variation is gradually reduced；Flood magnitude was by about 12000m in 19543/ s subtracts
As low as 4000m3/ s, crest discharge has increased after nineteen ninety-five.
Riverhead is stood firm, and to meet synthesis designs be 10748m for 100 years one calculated under fixed condition3/ s, it is considered to threshold value linear time-varying
And after POT sample moments are with CP trend time-varying, synthesis design changes in flow rate feature is more than Longchuan to the similar but amplitude of variation in Longchuan station
Stand.1954 annual flood magnitude about 15000m3/ s, has been decreased to 4100m to nineteen ninety-five3/ s, has increased after nineteen ninety-five, and 2009
It is more than 5000m during year3/s。
Boluo is stood firm, and to meet synthesis designs be 13032m for 100 years one calculated under fixed condition3/s.Boluo station threshold value is segmentation
Time-varying, POT sample moments are with CP Long-term change trends.Because different phase takes threshold value, Boluo station is met synthesis design for 100 years one and changed
Journey non-smooth curve, but synthesis design change procedure non-smooth curve is met in year one, but synthesis design change is met in year one
Process non-smooth curve, but there is mutation at 1974 and 1985.Two stages of 1954-1973 and 1974-1984,
Boluo station crest discharge is changed over time and reduced, and 1985-2009 crest discharges have increased.
(a-hundred-year) synthesis design flow changes over time situation and shown under specified value, the station specified value of Dong Jiang three
Synthesis design flow magnitude generally there are from large to small, then the trend gone up.At sequence nonuniformity
Reason, is respectively 7141m using conventional method calculating Longchuan, riverhead, the a-hundred-year design flood in Boluo station3/s、10748m3/ s and
13032m3/s.And consider after threshold value time-varying and POT sample moment variation tendencies, the synthesis design value that conventional method is calculated occurs
During 1960-1970, each station discharge process is influenceed less by Reservoir Operation during this period, and after the seventies, is adjusted by reservoir
Influence is stored, synthesis design is respectively less than conventional method result of calculation, if not considering flood peak sample nonuniformity, Flood Frequency Analysis knot
Fruit can over-evaluate design flood magnitude.
3.3 nonuniformity methods are contrasted with the conventional method return period
With present situation 2009 for time reference point, it is considered to specify mark crest discharge and base after the non-uniform processing that threshold value becomes
The traditional analysis result difference degree assumed in uniformity.Trend term is represented neither to consider threshold value time-varying with SS, also neither considered
The stable state of threshold value time-varying, also POT sample moments time-varying；MS represents threshold value time-varying, and POT sample moments are stable；E_MS is represented
The diversity factor for setting value and SS modelling values that MS models are calculated.
Table 2 shows：Synthesis design is respectively less than the result of calculation assumed based on uniformity after the nonuniformity processing of Longchuan station；Only
The calculating of threshold value time-varying is considered with assuming that flood peak diversity factor is about 10% based on uniformity, and difference degree is with return period increase
Slightly reduce；After considering that POT sample moments are with CP trend time-varying during threshold value, it is more than with the difference degree of conventional method result of calculation
30%, and diversity factor increases with the increase of return period.Synthesis design is respectively less than based on consistent after the nonuniformity processing of riverhead station
Property the result of calculation assumed, and diversity factor increases and increases with the return period, it is considered to which the diversity factor of POT sample moment time-varying is not more than
Consider the situation of POT sample moment time-varying；When return period is 100 years, MS models and SS model differences degree are up to 25%, CP models and SS
Model difference degree is up to 51%.Boluo station MS the model calculations are less than SS models, and diversity factor increases and increased with the return period, and 100
Diversity factor is 15% during the return period in year；CP models are different with Longchuan, riverhead station from the relation of SS models, are less than 20 in the return period
When, CP the model calculations are slightly larger than SS models, after the return period was more than 30 years, and CP the model calculations are less than SS models, and poor
DRS degree increases and increased with the return period, and diversity factor is 5.5% during 100 year return period.
The threshold value time-varying of table 2 handles (t0=2009) and conventional method estimation synthesis design difference degree is same or analogous
The same or analogous part of label correspondence；
Term the being given for example only property explanation of position relationship described in accompanying drawing, it is impossible to be interpreted as the limitation to this patent；
Obviously, the above embodiment of the present invention is only intended to clearly illustrate example of the present invention, and is not pair
The restriction of embodiments of the present invention.For those of ordinary skill in the field, may be used also on the basis of the above description
To make other changes in different forms.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Any modifications, equivalent substitutions and improvements made within the spirit and principle of invention etc., should be included in the claims in the present invention
Protection domain within.
Claims (7)
1. overdetermination amount flood nonuniformity analysis method under a kind of changing environment, it is characterised in that comprise the following steps：
Sample is chosen：Consider that historical flood carries out Flood Frequency Analysis, threshold value is determined, using the overdetermination amount methods of sampling to sample
Sequence is screened；
Sequence nonuniformity is diagnosed：Jump variation and Trend Variation of the sequence with the presence or absence of extraodinary flood are judged, to jumping and becoming
Two kinds of different situations of gesture carry out the Flood Frequency Analysis of overdetermination amount using different methods；
Overdetermination amount frequency is calculated under changing environment：The overdetermination amount Flood Frequency Analysis of historical flood is considered, according to selected continuous
POT samples, the discontinuous POT samples of composition are combined with historical flood, Flood Frequency Analysis is carried out to each sample segments sequence；Non- one
Cause property overdetermination amount Flood Frequency Analysis, is analyzed the maximum daily flow sequence of nonuniformity year using TVM models, is fitted AMS
Sequence simultaneously carries out nonuniformity Flood Frequency Analysis.
2. overdetermination amount flood nonuniformity analysis method under changing environment according to claim 1, it is characterised in that described
Threshold value is determined according to criterion of independence and overdetermination amount threshold value selection standard.
3. overdetermination amount flood nonuniformity analysis method under changing environment according to claim 1, it is characterised in that described
The diagnosis of sequence nonuniformity is to utilize M-K trend analyses, judges tendency and the jump of Flood evolution.
4. overdetermination amount flood nonuniformity analysis method under changing environment according to claim 2, it is characterised in that to not
Same Flood evolution uses different Flood Frequency Analysis methods.
5. overdetermination amount flood nonuniformity analysis method under changing environment according to claim 4, it is characterised in that described
Flood Frequency Analysis method include fixed threshold value time-varying Moment Methods and time-varying threshold value time-varying Moment Methods.
6. overdetermination amount flood nonuniformity analysis method under changing environment according to claim 5, it is characterised in that described
Fixed threshold value time-varying Moment Methods select different probability point to determine uniquely fixed threshold value in Flood Frequency Analysis
Cloth, it is considered to which two rank squares difference trend constructs the nonuniformity processing method of different TV M models before sequence.
7. overdetermination amount flood nonuniformity analysis method under changing environment according to claim 5, it is characterised in that described
Time-varying threshold value time-varying Moment Methods are that the nonuniformity research time-varying threshold value of temperature is applied into carrying for flood overdetermination amount sample
In taking, time-varying threshold value is calculated using regression quantile, and sectional door limit value is determined according to basin Reservoir Operation situation, in sampling
When consider flood frequency nonuniformity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710159692.8A CN107066425B (en) | 2017-03-17 | 2017-03-17 | Method for analyzing non-uniformity of ultra-quantitative flood in changing environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710159692.8A CN107066425B (en) | 2017-03-17 | 2017-03-17 | Method for analyzing non-uniformity of ultra-quantitative flood in changing environment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107066425A true CN107066425A (en) | 2017-08-18 |
| CN107066425B CN107066425B (en) | 2020-08-14 |
Family
ID=59620043
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710159692.8A Active CN107066425B (en) | 2017-03-17 | 2017-03-17 | Method for analyzing non-uniformity of ultra-quantitative flood in changing environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107066425B (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107797969A (en) * | 2017-10-30 | 2018-03-13 | 中国水利水电科学研究院 | A kind of determination method and device of flood retrieving parameter |
| CN108009565A (en) * | 2017-11-07 | 2018-05-08 | 中山大学 | River network design flood level computational methods under one kind variation environment |
| CN109753633A (en) * | 2018-12-05 | 2019-05-14 | 中国能源建设集团江苏省电力设计院有限公司 | A kind of structures under wind Failure risk evaluation method based on non-stationary GEV distributed model |
| CN110020469A (en) * | 2019-03-21 | 2019-07-16 | 武汉大学 | Flood warning analysis method and system based on Poisson regression and space filter value |
| CN110598315A (en) * | 2019-09-10 | 2019-12-20 | 太原理工大学 | Uncertainty analysis method for basin non-uniformity design flood under variable conditions |
| CN111080059A (en) * | 2019-11-11 | 2020-04-28 | 天津大学 | Non-uniform multi-source flood encounter risk analysis method |
| CN111241478A (en) * | 2020-01-08 | 2020-06-05 | 南京大学 | Flood frequency estimation method considering historical flood |
| CN111488679A (en) * | 2020-04-03 | 2020-08-04 | 中国能源建设集团江苏省电力设计院有限公司 | Method for calculating non-uniform wind speed sequence design wind speed |
| CN112183870A (en) * | 2020-10-09 | 2021-01-05 | 黄河水利委员会黄河水利科学研究院 | Design flood uncertainty analysis method based on overdetermined flood time-varying property |
| CN114580171A (en) * | 2022-03-03 | 2022-06-03 | 中国科学院地理科学与资源研究所 | Method for identifying river basin flood type and analyzing influence factors of river basin flood type |
| CN114595425A (en) * | 2021-12-20 | 2022-06-07 | 西安理工大学 | Method for diagnosing and analyzing inconsistent mutation points of runoff relation of drainage basin rainfall |
| CN114970187A (en) * | 2022-06-09 | 2022-08-30 | 中国科学院地理科学与资源研究所 | Method for realizing unbiased estimation of trend of hydrological climate time series |
| CN118395192A (en) * | 2024-06-26 | 2024-07-26 | 中南民族大学 | Non-stationary flood area frequency analysis method considering climate and reservoir influence |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105178240A (en) * | 2015-06-08 | 2015-12-23 | 武汉大学 | Optimization method for drawing P-III type distribution frequency curve |
-
2017
- 2017-03-17 CN CN201710159692.8A patent/CN107066425B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105178240A (en) * | 2015-06-08 | 2015-12-23 | 武汉大学 | Optimization method for drawing P-III type distribution frequency curve |
Non-Patent Citations (3)
| Title |
|---|
| W.G STRUPCZEWSKI，V.P.SINGH，W.FELUCH: "Non-stationary approach to at-site flood frequency modeling I. Maximum likelihood estimation", 《JOURNAL OF HYDROLOGY》 * |
| 叶长青，陈晓宏，张家鸣，朱爱萍，张丽娟: "具有趋势变异的非一致性东江流域洪水序列频率计算研究", 《自然资源学报》 * |
| 张丽娟，陈晓宏，叶长青，张家鸣: "考虑分组历史洪水的超定量洪水频率分析", 《水力发电学报》 * |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107797969A (en) * | 2017-10-30 | 2018-03-13 | 中国水利水电科学研究院 | A kind of determination method and device of flood retrieving parameter |
| CN108009565A (en) * | 2017-11-07 | 2018-05-08 | 中山大学 | River network design flood level computational methods under one kind variation environment |
| CN109753633A (en) * | 2018-12-05 | 2019-05-14 | 中国能源建设集团江苏省电力设计院有限公司 | A kind of structures under wind Failure risk evaluation method based on non-stationary GEV distributed model |
| CN110020469B (en) * | 2019-03-21 | 2022-07-19 | 武汉大学 | Poisson regression and spatial filtering value-based flood early warning analysis method and system |
| CN110020469A (en) * | 2019-03-21 | 2019-07-16 | 武汉大学 | Flood warning analysis method and system based on Poisson regression and space filter value |
| CN110598315A (en) * | 2019-09-10 | 2019-12-20 | 太原理工大学 | Uncertainty analysis method for basin non-uniformity design flood under variable conditions |
| CN110598315B (en) * | 2019-09-10 | 2022-11-18 | 太原理工大学 | Uncertainty analysis method for basin non-uniformity design flood under variable conditions |
| CN111080059A (en) * | 2019-11-11 | 2020-04-28 | 天津大学 | Non-uniform multi-source flood encounter risk analysis method |
| CN111241478A (en) * | 2020-01-08 | 2020-06-05 | 南京大学 | Flood frequency estimation method considering historical flood |
| CN111488679B (en) * | 2020-04-03 | 2022-06-10 | 中国能源建设集团江苏省电力设计院有限公司 | Method for calculating non-uniform wind speed sequence design wind speed |
| CN111488679A (en) * | 2020-04-03 | 2020-08-04 | 中国能源建设集团江苏省电力设计院有限公司 | Method for calculating non-uniform wind speed sequence design wind speed |
| CN112183870A (en) * | 2020-10-09 | 2021-01-05 | 黄河水利委员会黄河水利科学研究院 | Design flood uncertainty analysis method based on overdetermined flood time-varying property |
| CN112183870B (en) * | 2020-10-09 | 2023-09-01 | 黄河水利委员会黄河水利科学研究院 | Design flood uncertainty analysis method based on super-quantitative flood time variability |
| CN114595425A (en) * | 2021-12-20 | 2022-06-07 | 西安理工大学 | Method for diagnosing and analyzing inconsistent mutation points of runoff relation of drainage basin rainfall |
| CN114595425B (en) * | 2021-12-20 | 2024-08-16 | 西安理工大学 | Method for diagnosing and analyzing non-uniform mutation points of drainage basin rainfall runoff relationship |
| CN114580171A (en) * | 2022-03-03 | 2022-06-03 | 中国科学院地理科学与资源研究所 | Method for identifying river basin flood type and analyzing influence factors of river basin flood type |
| CN114580171B (en) * | 2022-03-03 | 2022-09-30 | 中国科学院地理科学与资源研究所 | Method for identifying basin flood type and analyzing influence factors of basin flood type |
| CN114970187A (en) * | 2022-06-09 | 2022-08-30 | 中国科学院地理科学与资源研究所 | Method for realizing unbiased estimation of trend of hydrological climate time series |
| CN114970187B (en) * | 2022-06-09 | 2024-04-16 | 中国科学院地理科学与资源研究所 | Method for realizing unbiased estimation of hydrologic climate time sequence trend |
| CN118395192A (en) * | 2024-06-26 | 2024-07-26 | 中南民族大学 | Non-stationary flood area frequency analysis method considering climate and reservoir influence |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107066425B (en) | 2020-08-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107066425A (en) | Overdetermination amount flood nonuniformity analysis method under a kind of changing environment | |
| CN111104981A (en) | Hydrological prediction precision evaluation method and system based on machine learning | |
| CN109543147A (en) | A kind of method of the non-linear quick diagnosis of Basin Rainfall runoff relationship and classification, Reasons | |
| CN108955652A (en) | A kind of hydrology nonuniformity sequence reconstructing method | |
| CN107423857B (en) | A kind of long-term water multiple target joint probability Forecasting Methodology in region | |
| CN112183870B (en) | Design flood uncertainty analysis method based on super-quantitative flood time variability | |
| CN107093013A (en) | A kind of hydrologic regime evaluation method for considering the hydrology index regularity of distribution | |
| CN109783934A (en) | A kind of mean velocity in section fitting rating method based on H-ADCP | |
| CN111241478A (en) | Flood frequency estimation method considering historical flood | |
| Xia et al. | Bioindicator assessment framework of river ecosystem health and the detection of factors influencing the health of the Huai River Basin, China | |
| CN111090831A (en) | Lake area change key driving factor identification method | |
| CN103487644A (en) | Electric energy subentry energy consumption metering method and device | |
| Wang et al. | Uncertainty analysis of hydrological processes based on ARMA-GARCH model | |
| CN106446547A (en) | Generalized second-category beta distribution based flood frequency analysis method | |
| CN111260159A (en) | Meteorological-hydrological coupling flood measuring and reporting method | |
| CN108595814B (en) | Method for simulating daily rainfall by using measured perennial rainfall data | |
| Yang et al. | Fuzzy risk analysis of dam overtopping from snowmelt floods in the nonstationarity case of the Manas River catchment, China | |
| Peng et al. | Positive effect of a canal system and reservoir group on the spatial-temporal redistribution of water resources in a pinnate drainage pattern | |
| Guo et al. | Synergistic evolution and attribution analysis of water-sediment in the middle and lower reaches of the Yangtze River | |
| Wu et al. | Local and regional flood frequency analysis based on hierarchical Bayesian model: application to annual maximum streamflow for the Huaihe River basin | |
| CN109870146A (en) | Flood frequency calculation method and device under a kind of climate change | |
| Kroll et al. | Prediction of hydrologic statistics in nested watersheds across the United States | |
| CN107133473A (en) | Hydrologic design values method of estimation in two variable hydrologic(al) frequency analysis under a kind of changing environment | |
| CN109871988B (en) | Flood forecast early warning precision analysis method | |
| CN113705091A (en) | Non-uniform design flood calculation method considering change environment and scheduling influence |
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 | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20170818 Assignee: Guangzhou Kangpusi Network Technology Co.,Ltd. Assignor: SUN YAT-SEN University Contract record no.: X2023980054174 Denomination of invention: A method for analyzing non consistency of ultra quantitative floods in changing environments Granted publication date: 20200814 License type: Common License Record date: 20231227 Application publication date: 20170818 Assignee: Huanyi (Guangdong) emergency safety Technology Group Co.,Ltd. Assignor: SUN YAT-SEN University Contract record no.: X2023980053955 Denomination of invention: A method for analyzing non consistency of ultra quantitative floods in changing environments Granted publication date: 20200814 License type: Common License Record date: 20231225 |