CN110457374A - A method of identification period typical case Heavy Rainfall Process - Google Patents

A method of identification period typical case Heavy Rainfall Process Download PDF

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Publication number
CN110457374A
CN110457374A CN201910770804.2A CN201910770804A CN110457374A CN 110457374 A CN110457374 A CN 110457374A CN 201910770804 A CN201910770804 A CN 201910770804A CN 110457374 A CN110457374 A CN 110457374A
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rainfall
typical case
period
typical
sample
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CN110457374B (en
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李胜
张健
张�荣
李涛
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GUIZHOU EAST CENTURY TECHNOLOGY Co Ltd
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GUIZHOU EAST CENTURY TECHNOLOGY Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462—Approximate or statistical queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2474—Sequence data queries, e.g. querying versioned data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • 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

Abstract

The invention discloses a kind of methods for identifying period typical case Heavy Rainfall Process, it includes the following steps: (1) determining Period Length T；Accumulated rainfall in step 2, calculation interval length T；Step 3 extracts typical rainfall sample；Step 4: determining typical case's class；Step 5 establishes period typical case's rainfall characteristic index system；Step 6, calculation interval typical case's rainfall characteristic index value weighted average；Step 7 determines period typical case's rainfall sequence；Present method solves conventional methods there is a problem of that subjective random and labor workload is larger, so that typical Heavy Rainfall Process selection identification work is had objectivity, quantification and automation, improves work efficiency simultaneously.

Description

A method of identification period typical case Heavy Rainfall Process
Technical field
The invention belongs to heavy rain identification technology more particularly to a kind of methods for identifying period typical case Heavy Rainfall Process.
Background technique
Heavy Rainfall Process is that storm rainfall changes with time and assigning process, passes through typical Heavy Rainfall Process Derivation Design heavy rain mistake Journey is one of important content and method of analytical calculation design storm flood.The selection of typical heavy rain identifies whether rationally, directly The precision of design flood is influenced, and then influences the scale of Hydraulic Engineering Design and the safety of operational management, and influences related flood The accuracy safety of water risk assessment and engineering operation dispatching simulation.In actual application, conventional method is dropped from actual measurement In rain sequence data, have according to selection certain representative, storm intensity and the total precipitation are big, and main rain peak is to the rear, to flood control compared with The qualitative principle of unfavorable Heavy Rainfall Process selects typical heavy rain.Conventional method mainly passes through qualitative method choice typical case heavy rain, deposits In subjective random biggish deficiency, and there is a problem of that labor workload is larger.
Summary of the invention:
The technical problem to be solved by the present invention is a kind of method for identifying period typical case Heavy Rainfall Process is provided, it is existing to solve There is technology to be identified by qualitative method choice typical case heavy rain to typical heavy rain, there is subjective random biggish deficiency, and There is a problem of that labor workload is larger.
Technical solution of the present invention:
A method of identification period typical case Heavy Rainfall Process, it includes:
Step 1 determines Period Length T；
Accumulated rainfall in step 2, calculation interval length T；
Step 3 extracts typical rainfall sample；
Step 4: determining typical case's class；
Step 5 establishes period typical case's rainfall characteristic index system；
Step 6, calculation interval typical case's rainfall characteristic index value weighted average；
Step 7 determines period typical case's rainfall sequence.
The Period Length T be T=1h, 3h, 6h, 12h, for 24 hours, 3d or survey rainfall data time interval it is any whole Multiple.
The method of accumulated rainfall in the calculation interval length T are as follows: under standard rainwater feelings database platform, root Rainfall sequence data P is surveyed according to historyY, i (y=year；I=0,1,2 ... n), the accumulative precipitation P of calculation interval T is slided year by yearY, T。
The method of the typical rainfall sample of extraction described in step 3 are as follows: according to the accumulative precipitation P of period TY, TValue is extracted P in year outY, TIt is worth maximum precipitation series；In remaining continuous sequence data, sliding calculates P respectivelyY, T, extract corresponding PY, T It is worth maximum precipitation series；
Using same logical method, the history of Cong Genian is surveyed in rainfall sequence data, extracts 8 precipitation series respectively As period typical case's rainfall sample.
The method of typical case's class is determined described in step 4 are as follows: using K-means Unsupervised clustering analysis method to the allusion quotation extracted Type rainfall sample carries out clustering, and classification is determined as 3 classes, filters out the most classification of wherein sample number as typical class Sample.
The method of period typical case's rainfall characteristic index system is established described in step 5 are as follows: with the maximum raininess in period T SM, p_max1(m=1,2,3...n), the second largest raininess SM, p_max2, the third-largest raininess SM, p_max3, quantum of rainfall PM, always, rain peak coefficient R, second half section quantum of rainfall PM, rear 1/2, rear 1/4 section of quantum of rainfall PM, rear 1/4For the characteristic index value of typical rainfall, weight Coefficient is respectively WI (i=1,2,3...7)；
The method of calculation interval typical case rainfall characteristic index value weighted average described in step 6 are as follows: use maximum Each characteristic index value is carried out normalization processing by standardized method, and to normalization, treated that characteristic value is weighted and averaged meter It calculates, obtains weighted average Wm(m=1,2,3...n).
Described in step 7 determine period typical case rainfall sequence method are as follows: to weighted average according to value from big to small into Row sequence, being maximized corresponding play rainfall sequence is period typical case rainfall sequence.
Beneficial effects of the present invention:
Calculating process of the present invention is simple, by simple programming, can be realized from a large amount of history rainfall original series In data, automatically quantitative analysis identifies the long typical Heavy Rainfall Process of arbitrary period；Relative to traditional method of discrimination, this method solution Conventional method of having determined has that subjective random and labor workload is larger, makes typical Heavy Rainfall Process selection identification work tool There are objectivity, quantification and automation, improves work efficiency simultaneously.
Specific embodiment:
A method of identification period typical case Heavy Rainfall Process, it includes the following steps:
Step 1: determining Period Length T；Typical Period Length T=1h, 3h, 6h, 12h, for 24 hours, 3d etc., while can root According to demand, determined with surveying any integral multiple of time interval of rainfall data；
Step 2: accumulated rainfall in calculation interval T；Under standard rainwater feelings database platform, surveyed according to history Rainfall sequence data py, i (y=year；I=0,1,2 ... n)；(wherein y is the time, and i is actual measurement rainfall data value serial number) sliding is counted year by year Calculate the accumulative precipitation P of period TY, T；
Step 3 extracts typical rainfall sample；
The method of the typical rainfall sample of extraction described in step 3 are as follows: according to the accumulative precipitation P of period TY, TValue is extracted P in year outY, TIt is worth maximum precipitation series；In remaining two sections of continuous sequence data, sliding calculates P respectivelyY, T, extract corresponding PY, TIt is worth maximum precipitation series；Using same logical method, the history of Cong Genian is surveyed in rainfall sequence data, is mentioned respectively 8 periods are taken to add up the maximum precipitation series of precipitation as period typical case's rainfall sample.
Step 4: determining typical case's class；
The method of typical case's class is determined described in step 4 are as follows: using K-means Unsupervised clustering analysis method to the allusion quotation extracted Type rainfall sample carries out clustering, and classification is determined as 3 classes, filters out the most classification of wherein sample number n as typical Class sample.
Step 5 establishes period typical case's rainfall characteristic index system；
The method of period typical case's rainfall characteristic index system is established described in step 5 are as follows: according to " storm intensity is big, drop Water inventory is big " and " main rain peak is to the rear " principle, with the maximum raininess S in period TM, p_max1(m=1,2,3...n) (m is sample Serial number), the second largest raininess SM, p_max2, the third-largest raininess SM, p_max3, quantum of rainfall PM, always, rain peak coefficient r (time to peak and rainfall The ratio lasted), second half section (1/2) quantum of rainfall PM, rear 1/2, rear 1/4 section of quantum of rainfall PM, rear 1/4For the spy of typical rainfall Index value is levied, weight coefficient is respectively WI (i=1,2,3...7)；(typical wI (i=1,2,3...7)=0.2,0.1,0.06,0.18,0.14, 0.14,0.18)；
Step 6, calculation interval typical case's rainfall characteristic index value weighted average；
The method of calculation interval typical case rainfall characteristic index value weighted average described in step 6 are as follows: use maximum Each characteristic index value is carried out normalization processing by standardized method, and to normalization, treated that characteristic value is weighted and averaged meter It calculates, obtains weighted average Wm(m=1,2,3...n).
Step 7 determines period typical case's rainfall sequence.
The method of period typical case rainfall sequence is determined described in step 7 are as follows: to weighted average according to value Wm(m=1,2, 3...n it) is ranked up from big to small, is maximized Max (Wm(m=1,2,3 ... n)) corresponding play rainfall sequence is period allusion quotation Type rainfall sequence.
Period typical case Heavy Rainfall Process is identified using the present invention, only need to determine Period Length T, can be provided automatically from historical series In material, analysis identifies the typical rainfall of corresponding Period Length；Identify the representativeness of the typical rainfall result obtained Dependent on the accumulation time of historical series data, the time is more, representative better.

Claims (8)

1. a kind of method for identifying period typical case Heavy Rainfall Process, it includes:
Step 1 determines Period Length T；
Accumulated rainfall in step 2, calculation interval length T；
Step 3 extracts typical rainfall sample；
Step 4: determining typical case's class；
Step 5 establishes period typical case's rainfall characteristic index system；
Step 6, calculation interval typical case's rainfall characteristic index value weighted average；
Step 7 determines period typical case's rainfall sequence.
2. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: segment length when described Degree T be T=1h, 3h, 6h, 12h, for 24 hours, 3d or survey rainfall data time interval any integral multiple.
3. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: when the calculating The method of accumulated rainfall in segment length T are as follows: under standard rainwater feelings database platform, rainfall sequence is surveyed according to history Data pY, i (y=year；I=0,1,2 ... n), the accumulative precipitation P of calculation interval T is slided year by yearY, T。
4. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: described in step 3 The method for extracting typical rainfall sample are as follows: according to the accumulative precipitation P of period TY, TValue, extracts P in yearY, TIt is worth maximum Precipitation series；In remaining two sections of continuous sequence data, sliding calculates P respectivelyY, T, extract corresponding PY, TIt is worth maximum precipitation system Column；Using same logical method, the history of Cong Genian is surveyed in rainfall sequence data, extracts 8 precipitation series conducts respectively Period typical case's rainfall sample.
5. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: described in step 4 Determine typical case class method are as follows: using K-means Unsupervised clustering analysis method to the typical rainfall sample extracted into Row clustering, classification are determined as 3 classes, filter out the most classification of wherein sample number as typical class sample.
6. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: described in step 5 The method for establishing period typical case's rainfall characteristic index system are as follows: with the maximum raininess S in period TM, p_max1(m=1,2, 3...n), the second largest raininess SM, p_max2, the third-largest raininess SM, p_max3, quantum of rainfall PM, always, rain peak coefficient r, second half section rainfall it is total Measure PM, rear 1/2, rear 1/4 section of quantum of rainfall PM, rear 1/4For the characteristic index value of typical rainfall, weight coefficient is respectively WI (i=1,2,3...7)。
7. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: described in step 6 The method of calculation interval typical case's rainfall characteristic index value weighted average are as follows: use maximum standardized method by each feature Index value carries out normalization processing, and to normalization, treated that characteristic value is weighted and averaged calculating, obtains weighted average WM (m=1,2,3...y*8)。
8. a kind of method for identifying period typical case Heavy Rainfall Process according to claim 1, it is characterised in that: described in step 7 The method for determining period typical case's rainfall sequence are as follows: weighted average is according to value ranked up from big to small, is maximized pair The play rainfall sequence answered is period typical case rainfall sequence.
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