CN108874750A - A kind of Calculation of Area Rainfall uncertainty estimation method - Google Patents

A kind of Calculation of Area Rainfall uncertainty estimation method Download PDF

Info

Publication number
CN108874750A
CN108874750A CN201810669035.2A CN201810669035A CN108874750A CN 108874750 A CN108874750 A CN 108874750A CN 201810669035 A CN201810669035 A CN 201810669035A CN 108874750 A CN108874750 A CN 108874750A
Authority
CN
China
Prior art keywords
calculation
rainfall
area
normal distribution
formula
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.)
Pending
Application number
CN201810669035.2A
Other languages
Chinese (zh)
Inventor
梁忠民
蒋晓蕾
牛小茹
胡义明
李彬权
王军
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hohai University HHU
Original Assignee
Hohai University HHU
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Hohai University HHU filed Critical Hohai University HHU
Priority to CN201810669035.2A priority Critical patent/CN108874750A/en
Publication of CN108874750A publication Critical patent/CN108874750A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Biology (AREA)
  • Computer Hardware Design (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Operations Research (AREA)
  • Probability & Statistics with Applications (AREA)
  • Evolutionary Computation (AREA)
  • Algebra (AREA)
  • Geometry (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a kind of Calculation of Area Rainfall uncertainty estimation methods.It is assumed that Calculation of Area Rainfall error Normal Distribution, and it is standardized, in conjunction with《Standardized normal distribution function table》The corresponding relationship of middle fraction and quantile carries out mathematical description to Calculation of Area Rainfall uncertainty.Meanwhile based on station method empirical equation is taken out, in known drainage area, dispersed elevation, precipitation station number and calculation interval, the anti-fraction that pushes away is 90% calculating error.Finally, bringing the calculating error of fraction 90% into Calculation of Area Rainfall uncertainty description formula, inquire into using calculated value as the conditional distribution function of the areal rainfall of condition, quantization Calculation of Area Rainfall is uncertain.

Description

A kind of Calculation of Area Rainfall uncertainty estimation method
Technical field
The present invention relates to hydrologic forecast prediction field more particularly to a kind of Calculation of Area Rainfall uncertainty estimation methods.
Background technique
Due to the limitation of the complexity of natural hydrologic process and human knowledge's level, so that can not during flood forecasting Avoid there are many uncertainties, so as to cause the uncertainty of flood forecasting result, bring risk for Flood Control Dispatch.Cause This carries out and forecasts uncertain quantization method research, and the uncertainty of each element, has highly important during quantized prediction Realistic meaning.As the most important input element of Flood Forecasting Model, the estimation precision of basin face mean rainfall is greatly determined The quality of final forecast result.Since website laying condition etc. limits, although the density of rainfall observation website is continuing to increase, But existing rainfall website still can not accomplish comprehensive laying to a basin, therefore inevitably need to pass through Field in Limited Rain The observation rainfall at amount station calculates basin face mean rainfall.In order to ensure the computational accuracy of face mean rainfall, hydrologist and statistics Scholar has developed many areal rainfall difference calculation methods, such as gram in golden difference, Thiessen polygon calculating method.Nevertheless, by In the influence for the conditions such as watershed unit, landforms, spatially distributed rainfall be uneven, the calculating of areal rainfall is uncertain inevitable. Therefore, carry out the research of Calculation of Area Rainfall uncertainty quantization method, have important practical significance.
Summary of the invention
It is an object of the present invention to solution the deficiencies in the prior art, the present invention provides a kind of Calculation of Area Rainfall uncertainty and estimates Meter method, it is assumed that Calculation of Area Rainfall error Normal Distribution, and it is standardized, it is based on standardized normal distribution fraction With the relationship of quantile, mathematical description is carried out to Calculation of Area Rainfall uncertainty;Corresponding fraction is pushed away using empirical equation is counter Calculate error;In conjunction with fraction, error and the probabilistic mathematical expression formula of Calculation of Area Rainfall are calculated, inquires into the item of areal rainfall Part probability distribution realizes the probabilistic quantization of Calculation of Area Rainfall with this.
In order to solve the above-mentioned technical problem, the technical scheme is that:A kind of Calculation of Area Rainfall uncertainty estimation side Method, which is characterized in that include the following steps:
Step 1:The probabilistic description of Calculation of Area Rainfall, to any moment t, it is assumed that the calculating relative error ε of areal rainfall (t) Normal Distribution, the corresponding relationship of combined standard normal distribution fraction and quantile, to Calculation of Area Rainfall uncertainty Carry out mathematical description;
Step 2:Formula is counter to be pushed away, counter to be pushed to the prediction error calculation formula for determining fraction according to existing empirical equation;
Step 3:In conjunction with step 1 and step 2, inquire into calculated valueFor the areal rainfall of conditionProbability distribution, It is uncertain to quantify Calculation of Area Rainfall.
Further, step 1 includes the following steps:
Step 1.1:It is assumed that Calculation of Area Rainfall valueRelative error ε (t) Normal Distribution it is as follows:
In formula,It is true face average rainfall;σ is the standard deviation of Calculation of Area Rainfall error.
Step 1.2:According to above-mentioned it is assumed that Calculation of Area Rainfall value can be inquired intoUnder known conditions, true face is averaged rain AmountCondition distribution it is as follows:
In formula, Φ is the probability function of standardized normal distribution.
Step 1.3:It is assumed that standardized variable u is as follows:
In formula, standardized variable u obeys standardized normal distribution, then can inquire《Standardized normal distribution function table》, Inquire into the corresponding quantile-u of a certain level of significance α (confidence level is η=1- α)α/2(t)、uα/2(t) and probability α/2, (1- α/ 2) (schematic diagram is shown in Fig. 2) passes through inquiry by taking unilateral quantile as an example《Standardized normal distribution function table》, available:
Φ(uα/2(t))=α/2 1- (4)
According to above formula, the definition of combining standardized variable u can be pushed away:
In formula, EηThe allowable error of η is taken for fraction, then areal rainfallCondition distribution can be rewritten as:
Further, step 2 is specially:
In conjunction with station method empirical equation is taken out, the anti-fraction that pushes away is 90% Calculation of Area Rainfall error E90%It is as follows:
E90%=0.099 × N-1.166×A0.3×H0.155×T-0.197 (7)
In formula, N is the quantity (station) for studying area's precipitation station;A is research area's area (km2);H is research area's dispersed elevation (m);T is that duration of raining is long (h), wherein N=12;A=805;H=479;T=1.
Further, step 3 is specially:
When fraction takes 90%, inquiry《Standardized normal distribution function table》It is found that unilateral quantile uα/2(t)= 1.64.In conjunction with above formula, it can push away and be able to calculated valueFor the areal rainfall of conditionCondition distribution it is as follows:
The beneficial effects obtained by the present invention are as follows:A kind of Calculation of Area Rainfall uncertainty estimation method provided by the invention, knot It closes fraction to be described with quartile point correspondence opposite rainfall calculating uncertainty, and method empirical equation in station is counter to be pushed away based on taking out The calculating error of 90% fraction, and then it is uncertain to quantify Calculation of Area Rainfall.
Detailed description of the invention
Fig. 1 is a kind of flow chart of Calculation of Area Rainfall uncertainty estimation method of the present invention;
Fig. 2 is standardized normal distribution probability density function schematic diagram;
Fig. 3 is the Calculation of Area Rainfall uncertainty schematic diagram of certain hydrometric station rainfall;
Fig. 4 is certain the 6th period of hydrometric station rainfall areal rainfall conditional probability density function figure.
Specific embodiment
With reference to the accompanying drawings and detailed description, the present invention is furture elucidated, it should be understood that following specific embodiments are only For illustrating the present invention rather than limiting the scope of the invention.
Below with reference to example, the present invention will be further explained.
As Figure 1-Figure 4, a kind of Calculation of Area Rainfall uncertainty estimation method, which is characterized in that include the following steps:
Step 1:The probabilistic description of Calculation of Area Rainfall, to any moment t, it is assumed that the calculating error ε (t) of areal rainfall takes From normal distribution, the corresponding relationship of combined standard normal distribution fraction and quantile carries out Calculation of Area Rainfall uncertainty Mathematical description;
Step 2:Formula is counter to be pushed away, counter to be pushed to the prediction error calculation formula for determining fraction according to existing empirical equation;
Step 3:In conjunction with step 1 and step 2, inquire into calculated valueFor the areal rainfall of conditionProbability distribution, It is uncertain to quantify Calculation of Area Rainfall.
Specific implementation process is as follows:A kind of Calculation of Area Rainfall uncertainty estimation method, includes the following steps:
(1) assume Calculation of Area Rainfall valueRelative error ε (t) Normal Distribution it is as follows:
In formula,It is true face average rainfall;σ is the standard deviation of Calculation of Area Rainfall error.
(2) according to above-mentioned it is assumed that Calculation of Area Rainfall value can be inquired intoUnder known conditions, true face mean rainfallCondition distribution it is as follows:
In formula, Φ is the probability function of standardized normal distribution.
(3) assume that standardized variable u is as follows:
In formula, standardized variable u obeys standardized normal distribution, then can inquire《Standardized normal distribution function table》, Inquire into the corresponding quantile-u of a certain level of significance α (confidence level is η=1- α)α/2(t)、uα/2(t) and probability α/2, (1- α/ 2) (schematic diagram is shown in Fig. 2) passes through inquiry by taking unilateral quantile as an example《Standardized normal distribution function table》, available:
Φ(uα/2(t))=α/2 1- (4)
According to above formula, the definition of combining standardized variable u can be pushed away:
In formula, EηThe allowable error of η is taken for fraction, then areal rainfallCondition distribution can be rewritten as:
(4) it combines and takes out station method empirical equation, the anti-Calculation of Area Rainfall error E for pushing away fraction and being 90%90%It is as follows:
E90%=0.099 × N-1.166×A0.3×H0.155×T-0.197 (7)
In formula, N is the quantity (station) for studying area's precipitation station;A is research area's area (km2);H is research area's dispersed elevation (m);T is duration of raining length (h).
(5) when fraction takes 90%, inquiry《Standardized normal distribution function table》It is found that unilateral quantile uα/2(t)= 1.64.In conjunction with above formula, it can push away and be able to calculated valueFor the areal rainfall of conditionCondition distribution it is as follows:
Embodiment:Existing a certain drainage area A=805km2, basin dispersed elevation H=479m has precipitation station N in basin =12, the material calculation (duration of raining length) of deterministic prediction model is T=1h.To a certain field rainfall in the basin into The quantization of row Calculation of Area Rainfall uncertainty:
(1) assume Calculation of Area Rainfall valueRelative error ε (t) Normal Distribution it is as follows:
In formula,It is true face average rainfall;σ is the standard deviation of Calculation of Area Rainfall error.
(2) according to above-mentioned it is assumed that Calculation of Area Rainfall value can be inquired intoUnder known conditions, true face mean rainfallCondition distribution it is as follows:
In formula, Φ is the probability function of standardized normal distribution.
(3) assume that standardized variable u is as follows:
In formula, standardized variable u obeys standardized normal distribution, then can inquire《Standardized normal distribution function table》, Inquire into the corresponding quantile-u of a certain level of significance α (confidence level is η=1- α)α/2(t)、uα/2(t) and probability α/2, (1- α/ 2) (schematic diagram is shown in Fig. 2) passes through inquiry by taking unilateral quantile as an example《Standardized normal distribution function table》, available:
Φ(uα/2(t))=α/2 1- (4)
According to above formula, the definition of combining standardized variable u can be pushed away:
In formula, EηThe allowable error of η is taken for fraction, then areal rainfallCondition distribution can be rewritten as:
(4) it combines and takes out station method empirical equation, the anti-Calculation of Area Rainfall error E for pushing away fraction and being 90%90%It is as follows:
E90%=0.099 × N-1.166×A0.3×H0.155×T-0.197 (7)
In formula, N=12;A=805;H=479;T=1.
(5) when fraction takes 90%, inquiry《Standardized normal distribution function table》It is found that unilateral quantile uα/2(t)= 1.64.In conjunction with above formula, it can push away and be able to calculated valueFor the areal rainfall of conditionCondition distribution it is as follows:
(6) face mean rainfall can be quantified using above formula to any time tUncertainty, it is a certain with the basin For the rainfall of field, the Calculation of Area Rainfall uncertainty schematic diagram (Fig. 3) of this rainfall is drawn, and by taking the 6th moment as an example, drawing should When facet mean rainfall probability density function figure (Fig. 4).
The present invention is described Calculation of Area Rainfall uncertainty by the relationship of fraction and quantile, and is based on experience Formula inquires into the calculating error of 90% fraction, and it is uncertain to quantify Calculation of Area Rainfall on this basis.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered It is considered as protection scope of the present invention.

Claims (6)

1. a kind of Calculation of Area Rainfall uncertainty estimation method, which is characterized in that include the following steps:
Step 1:The probabilistic description of Calculation of Area Rainfall, to any moment t, it is assumed that the relative error ε (t) of Calculation of Area Rainfall value Normal Distribution, the corresponding relationship of combined standard normal distribution fraction and quantile, to Calculation of Area Rainfall uncertainty into Row mathematical description;
Step 2:Formula is counter to be pushed away, counter to be pushed to the prediction error calculation formula for determining fraction according to existing empirical equation;
Step 3:In conjunction with step 1 and step 2, inquires into using Calculation of Area Rainfall value as the probability distribution of the areal rainfall of condition, quantify face Rainfall calculates uncertain.
2. a kind of Calculation of Area Rainfall uncertainty estimation method according to claim 1, which is characterized in that step 1 is specific Include the following steps:
Step 1.1:It is assumed that Calculation of Area Rainfall valueRelative error ε (t) Normal Distribution it is as follows:
In formula,It is true face average rainfall;σ is the standard deviation of Calculation of Area Rainfall error.
Step 1.2:According to above-mentioned it is assumed that Calculation of Area Rainfall value can be inquired intoUnder known conditions, true face mean rainfallCondition distribution it is as follows:
In formula, Φ is the probability function of standardized normal distribution;
Step 1.3:It is assumed that standardized variable u is as follows:
In formula, standardized variable u obeys standardized normal distribution, then can inquire《Standardized normal distribution function table》, inquire into A certain level of significance α, confidence level η, corresponding quantile-uα/2(t)、uα/2(t) and probability α/2, (α/2 1-), pass through Inquiry《Standardized normal distribution function table》, available:
Φ(uα/2(t))=α/2 1- (4)
According to above formula, the definition of combining standardized variable u can be pushed away:
In formula, EηThe allowable error of η=1- α is taken for fraction, then areal rainfallCondition distribution can be rewritten as:
Wherein, t is the moment, and σ is the standard deviation of Calculation of Area Rainfall error.
3. a kind of Calculation of Area Rainfall uncertainty estimation method according to claim 1, which is characterized in that step 2 is specific For:
In conjunction with station method empirical equation is taken out, the anti-fraction that pushes away is 90% Calculation of Area Rainfall error E90%It is as follows:
E90%=0.099 × N-1.166×A0.3×H0.155×T-0.197 (7)
In formula, N is the quantity for studying area's precipitation station;A is research area's area;H is research area's dispersed elevation;T is that duration of raining is long.
4. a kind of Calculation of Area Rainfall uncertainty estimation method according to claim 3, which is characterized in that step 3 is specific For:
When fraction takes 90%, inquiry《Standardized normal distribution function table》It is found that unilateral quantile uα/2(t)=1.64;Knot Box-like (7), can push away and be able to calculated valueFor the areal rainfall of conditionCondition distribution it is as follows:
Wherein, Φ is the probability function of standardized normal distribution.
5. a kind of Calculation of Area Rainfall uncertainty estimation method according to claim 3, which is characterized in that the N=12, A=805.
6. a kind of Calculation of Area Rainfall uncertainty estimation method according to claim 4, which is characterized in that H=479, T= 1。
CN201810669035.2A 2018-06-22 2018-06-22 A kind of Calculation of Area Rainfall uncertainty estimation method Pending CN108874750A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810669035.2A CN108874750A (en) 2018-06-22 2018-06-22 A kind of Calculation of Area Rainfall uncertainty estimation method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810669035.2A CN108874750A (en) 2018-06-22 2018-06-22 A kind of Calculation of Area Rainfall uncertainty estimation method

Publications (1)

Publication Number Publication Date
CN108874750A true CN108874750A (en) 2018-11-23

Family

ID=64295765

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810669035.2A Pending CN108874750A (en) 2018-06-22 2018-06-22 A kind of Calculation of Area Rainfall uncertainty estimation method

Country Status (1)

Country Link
CN (1) CN108874750A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109709015A (en) * 2018-12-25 2019-05-03 河海大学 It is a kind of can the preferential flow phenomenon of quantitative description kinematic infiltration method
CN110895354A (en) * 2019-12-04 2020-03-20 中国水利水电科学研究院 Surface rainfall calculation method based on dynamic adjustment of Thiessen polygon

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102867106A (en) * 2012-08-14 2013-01-09 贵州乌江水电开发有限责任公司 Method and system for predicting short-term running water
CN107229823A (en) * 2017-05-18 2017-10-03 西南交通大学 A kind of probabilistic analysis method of wind effect extreme value
CN107491903A (en) * 2017-09-27 2017-12-19 河海大学 A kind of Flood Forecasting Method based on data mining similarity theory
CN107992961A (en) * 2017-11-21 2018-05-04 中国水利水电科学研究院 A kind of adaptive basin Medium-and Long-Term Runoff Forecasting model framework method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102867106A (en) * 2012-08-14 2013-01-09 贵州乌江水电开发有限责任公司 Method and system for predicting short-term running water
CN107229823A (en) * 2017-05-18 2017-10-03 西南交通大学 A kind of probabilistic analysis method of wind effect extreme value
CN107491903A (en) * 2017-09-27 2017-12-19 河海大学 A kind of Flood Forecasting Method based on data mining similarity theory
CN107992961A (en) * 2017-11-21 2018-05-04 中国水利水电科学研究院 A kind of adaptive basin Medium-and Long-Term Runoff Forecasting model framework method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
梁忠民: "考虑降雨不确定性的洪水概率预报方法", 《河海大学学报(自然科学版)》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109709015A (en) * 2018-12-25 2019-05-03 河海大学 It is a kind of can the preferential flow phenomenon of quantitative description kinematic infiltration method
CN109709015B (en) * 2018-12-25 2021-03-02 河海大学 Motion wave infiltration method capable of quantitatively describing preferential flow phenomenon
CN110895354A (en) * 2019-12-04 2020-03-20 中国水利水电科学研究院 Surface rainfall calculation method based on dynamic adjustment of Thiessen polygon

Similar Documents

Publication Publication Date Title
Su et al. A probabilistic approach to rainwater harvesting systems design and evaluation
CN108983325B (en) Rainfall runoff forecasting method
CN108764515A (en) A kind of reservoir operation Application of risk decision method of Coupled Numerical meteorological model DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM
US20210256378A1 (en) System and method for weather dependent machine learning architecture
KR102073768B1 (en) Drought information supply system based on portal
CN103903105A (en) Nuclear accident consequence assessment and auxiliary decision integrated platform and method
CN109814178A (en) Hydrological probability forecasting procedure based on Copula- Model Condition processor
CN108874750A (en) A kind of Calculation of Area Rainfall uncertainty estimation method
CN109472396A (en) Mountain fire prediction technique based on depth e-learning
CN109508476A (en) Mountain fire based on depth e-learning predicts modeling method
WO2020118586A1 (en) Energy consumption prediction method and device
CN113159434A (en) Radar echo prediction method, device, equipment and storage medium
CN116993030B (en) Reservoir pressure salty taste adjustment method and system under variable conditions
CN104484677A (en) Method for analyzing demographic data information by means of satellite images
TW201737164A (en) Method and apparatus for correcting service data prediction
CN108829990B (en) Rainfall process design method of regional rainfall artificial simulation system
CN116821585A (en) Non-parameter time downscaling method and system for long-sequence reconstruction runoff
Schevenhoven et al. Improving weather and climate predictions by training of supermodels
Ismail et al. Scenario approach for the seasonal forecast of Kharif flows from the Upper Indus Basin
Liu et al. Meteorological drought forecasting using Markov Chain model
Zhang et al. Daily reservoir inflow forecasting combining QPF into ANNs model
Jang et al. An intercomparison study between optimization algorithms for parameter estimation of microphysics in Unified model: Micro-genetic algorithm and Harmony search algorithm
Khoorani et al. Effects of Climate Change on Drought Duration and Severity in Arid and Semi-arid Stations (Bandarabbassand Shahrekord), Based on HADCM3 Model
CN108921340A (en) A kind of flood probability forecasting procedure based on error transfer density function
CN116524374B (en) Satellite image real-time processing and distributing method and system

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
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20181123