CN109920213A - The method that Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning - Google Patents

The method that Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning Download PDF

Info

Publication number
CN109920213A
CN109920213A CN201910191242.6A CN201910191242A CN109920213A CN 109920213 A CN109920213 A CN 109920213A CN 201910191242 A CN201910191242 A CN 201910191242A CN 109920213 A CN109920213 A CN 109920213A
Authority
CN
China
Prior art keywords
rainfall
flood
period
critical
early warning
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
Application number
CN201910191242.6A
Other languages
Chinese (zh)
Other versions
CN109920213B (en
Inventor
童冰星
李致家
刘墨阳
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 CN201910191242.6A priority Critical patent/CN109920213B/en
Publication of CN109920213A publication Critical patent/CN109920213A/en
Application granted granted Critical
Publication of CN109920213B publication Critical patent/CN109920213B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather

Landscapes

  • Alarm Systems (AREA)

Abstract

The invention discloses a kind of method that Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning, the rainfall data before flood peak occurs in all previous peb process in the T period are taken passages first, and calculate the accumulation rainfall in the T period;Secondly, the rainfall data before occurring based on flood peak in the T period construct Lorentz curve, the Gini coefficient of Lorentz curve is calculated, and the rainfall in the preceding T period is occurred into flood peak according to Gini coefficient and is divided into three classes;Then the tension water content saturation degree at T moment, i.e. initial soil moisture content saturation degree before statistics flood peak occurs;Then judge whether all previous flood is super alert flood, respectively to uniform, unevenly, the other rainfall production accumulation rainfall-initial soil moisture content saturation degree scatter plot of three types is concentrated, and the corresponding point of super alert flood is marked, Critical Rainfall line is drawn in conjunction with the corresponding point of super alert flood;Real-time early warning is finally carried out according to Critical Rainfall line.

Description

The method that Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning
Technical field
The present invention relates to hydrology technology fields more particularly to a kind of Critical Rainfall based on rainfall rainfall process to carry out in real time The method of mountain torrents early warning.
Background technique
China river is numerous, drainage area 200 to 3000km2Middle small watershed nearly 9000.In recent years, climate changes It influences, the sudden flood of the middle and small river as caused by Local Heavy Precipitation frequently occurs, it has also become the main disasters to cause casualties Kind.Middle small watershed easily forms harm due to being generally in remote mountain areas with a varied topography, that the gradient is steep, the flood hurriedly to go up The flood of local resident's personal safety and social economy, thus it is prominent according to the rainfall data centering small watershed observed in real time Hair property flood carries out quick early warning as major issue urgently to be resolved.
Critical Rainfall method is a kind of method of the relatively broad carry out mountain torrents early warning of domestic and international application.Critical Rainfall is guidance When causing a basin that mountain flood will occur, magnitude or intensity that rainfall is likely to be breached.It is pushed away based on basin actual conditions It calculates when reliable accurately Critical Rainfall is the key that this method application and where core.However existing inquire into critical rain at present The method of amount does not account for the rainfall process of rainfall mostly.In fact, the heavy rain of very brief concentration is more for same rainfall It is easy to produce paroxysmal flood, therefore has more risk.If cannot be to this case during calculating Critical Rainfall Paid attention to, then it is excessively high to can frequently result in the Critical Rainfall extrapolated, and actual measurement rainfall, which is often not achieved, when mountain torrents real-time early warning faces Boundary's rainfall brings certain hidden danger to fail to report, for mountain flood prevention.How Critical Rainfall method is carried out it is perfect, thus one Determine in degree improve for the key points and difficulties in the attention and Critical Rainfall method development process of rainfall rainfall process feature it One.
In order to further promote the development of Critical Rainfall method, need to consider the uneven item of rainfall rainfall process deeper into research The evaluation method of part lower critical rainfall.
Lorentz curve (Lorenz curve) is exactly, in a totality (country, area), with population percentage be Abscissa, the curve formed with the point of the income percentage ordinate of each population percentage of correspondence.It is united by the U.S. originally Meter scholar M.O. Lorentz (Max Otto Lorenz, 1876-1959) is in proposing in 1907 to study national income in state The mathematical model of assignment problem between the people.The bending degree (being indicated using Gini coefficient) of its Lorentz curve has important meaning Justice.In general, it reflects the unequal degree of distribution of earnings.Gini coefficient is bigger, and bending degree is bigger, and distribution of earnings is got over Inequality, vice versa, therefore the curve is widely used in Science of Economics.In the case where considering rainfall time distribution feature Critical Rainfall is calculated, key seeks to quantify the degree of irregularity of rainfall sequence, and this is exactly long-range navigation The hereby range of CURVE STUDY, therefore for the deficiency in existing reckoning Critical Rainfall method, how to consider Lorentz curve During the reckoning of Critical Rainfall, quantify the time distribution feature of continuous development and change in rainfall, thus Improve the reliability of Critical Rainfall projectional technique, exactly inventor's problem to be solved.
Summary of the invention
When being based on rainfall the technical problem to be solved by the present invention is to provide one kind for defect involved in background The method that the Critical Rainfall of journey distribution carries out real-time mountain torrents early warning.
The present invention uses following technical scheme to solve above-mentioned technical problem
The method that Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning, comprising the following steps:
Step 1, the flow and rainfall data information in all previous peb process in basin are collected, for flood mistake each time Journey takes passages the rainfall data before flood peak occurs in the T period, and calculates the accumulation rainfall in the T period, and T is whole more than or equal to 2 Number;
Step 2, for each flood events, the rainfall data before being occurred according to its flood peak in the T period construct Lorentz Curve calculates the Gini coefficient of Lorentz curve, then by Gini coefficient respectively with pre-set Gini coefficient threshold X G, DG It is compared and then the rainfall of peb process is divided, XG < DG, if 0 < G≤XG, it is believed that rain types are equal It is even, if XG < G≤DG, it is believed that rain types be it is uneven, if DG < G, it is believed that rain types be concentrate;
Step 3, the tension water content saturation degree at T moment before flood peak occurs in each flood events is counted, i.e., initial soil Earth water content saturation degree;
Step 4, for each flood events, judge whether it is super alert flood, and respectively to uniform, uneven, collection In the other flood peak of three types occur before rainfall production accumulation rainfall-initial soil moisture content saturation degree scatter plot in the T period, The corresponding point of super alert flood is marked, draws Critical Rainfall line in conjunction with the corresponding point of super alert flood;
Step 5, based on real-time rainfall data and soil moisture content saturation degree, judge whether to occur in conjunction with Critical Rainfall line Super alert flood such as occurs, and issues mountain torrents early warning to current rainfall.
As the present invention is based on the method that the Critical Rainfall of rainfall rainfall process carries out real-time mountain torrents early warning, the steps 1 Specific step is as follows:
Step 1.1, the flow and rainfall data information in all previous peb process in basin are collected, for flood mistake each time Journey:
Step 1.1.1, finds out maximum flow value in peb process, and at the time of determine that maximum flow value occurs, i.e., MQ_T between the peak of flood is current;
Step 1.1.2 takes passages the rainfall data Seq_P before flood peak occurs in the T period;
Seq_P={ PMQ_T,PMQ_T-1,PMQ_T-2…PMQ_T-T}
In formula, PMQ_TFor the rainfall at MQ_T moment;PMQ_T-1For the rainfall at MQ_T-1 moment;PMQ_T-2When for MQ_T-2 The rainfall at quarter;PMQ_T-TFor the rainfall at MQ_T-T moment;
Step 1.1.3 calculates the accumulation rainfall AccP in the T period;
As the present invention is based on the method that the Critical Rainfall of rainfall rainfall process carries out real-time mountain torrents early warning, the steps 2 In specifically includes the following steps:
Step 2.1, for each flood events:
The ascending sequence of rainfall in Seq_P is obtained NSeq_P by step 2.1.1;
NSeq_P={ P0,P1…Pj…PT}
In formula, j is the integer for being less than or equal to T more than or equal to 0;
Accumulation period Precipitation Series ASeq_P is calculated based on NSeq_P in step 2.1.2;
ASeq_P={ AP0,AP1…APj…APT}
In formula, APjAccumulation period rainfall when for the period being j,
Step 2.1.3 calculates the accumulation period rainfall percentage in Seq_P, obtains accumulation period rainfall Percent sequence ANSeq_P;
NSeq_P={ F0,F1…Fj…FT}
In formula,
Step 2.1.4 calculates Gini coefficient G based on ASeq_P and ANSeq_P;
Step 2.2, by the Gini coefficient G of all previous rainfall respectively with pre-set Gini coefficient threshold X G, DG into Row relatively, and then classify to all previous rainfall, XG < DG, if 0 < G≤XG, it is believed that rain types be it is uniform, if XG < G≤DG, it is believed that rain types be it is uneven, if DG < G, it is believed that rain types be concentrate.
As the present invention is based on the method that the Critical Rainfall of rainfall rainfall process carries out real-time mountain torrents early warning, the steps 4 Specific step is as follows:
Step 4.1, for each flood events, judge whether it is super alert flood:
Step 4.1.1 calculates tension water content dynamic changing process and the safety in basin using Xinanjiang model The Variations in Flow Changes of protected object position;
Step 4.1.2 counts the soil tension water content saturation degree at T moment before flood peak, i.e. initial soil moisture content is saturated Spend Init_W;
Init_W=WMQ_T-T/WM
In formula, WMQ_T-TFor the tension water content at MQ_T-T moment in basin;WM is basin tension water capacity;
Step 4.1.3, the early warning of taking precautions against natural calamities that river basin authority is investigated or consulted by floodmark on the spot are planned to obtain safety The Alarm flow Warn_Q of protected object position;
Step 4.1.4 determines maximum stream flow Max_Q based on the Variations in Flow Changes of safeguard protection object position;
Step 4.1.5 judges flood for super alert flood if Max_Q >=Warn_Q in peb process;
Step 4.2, the rainfall before occurring respectively to uniform, uneven, the other flood peak of three types of concentration in the T period Rainfall-initial soil moisture content saturation degree scatter plot is accumulated in production, is marked in scatter plot using cross symbol super alert big vast Not super alert flood is marked using circle symbol in water;
Step 4.3, according to cross symbol and circle symbol in accumulation rainfall-initial soil moisture content saturation degree scatter plot Distribution characteristics, using W-H (widrow-hoff) algorithm based on minimum variance principle, draw critical warning rainfall line to get Critical Rainfall line into basin under different types of rainfall, under various soil water status conditions.
As the present invention is based on the method that the Critical Rainfall of rainfall rainfall process carries out real-time mountain torrents early warning, the steps 5 Specific step is as follows:
In real-time early warning, the initial soil of accumulation rainfall and preceding T moment before continuous this moment of circle statistics in the T period Earth water content saturation degree calculates the Gini coefficient of rainfall in preceding T time section, so that the classification of rainfall is judged, by the secondary drop This turns to data point to rain process, is labeled in accumulation rainfall-initial soil moisture content saturation degree scatter plot of corresponding classification, if The position of the point marked judges that super alert flood occurs, issues mountain torrents early warning in the top of Critical Rainfall line.
The invention adopts the above technical scheme compared with prior art, has following technical effect that
The method that a kind of Critical Rainfall based on rainfall rainfall process provided by the invention carries out real-time mountain torrents early warning, with shadow Based on the physical agent for ringing Critical Rainfall, the dynamic of the time distribution feature of rainfall during calculating Critical Rainfall is featured Development and change, have quantified influence of the rainfall process feature for Critical Rainfall of rainfall, and then have estimated small in the property of mountain area Critical Rainfall in basin.The precision and reliability of calculated result were not only ensure that in this way, but also can be timely and conveniently in the property of mountain area The Critical Rainfall of small watershed promotes and applies in calculating.And this method mainly observes data using existing rainfall website, data are come Source is reliable and stable, and the functional relation in method between variable is clear, is conducive to the fast automatic calculating of Critical Rainfall in basin, can Further to promote the deep development of small watershed mountain torrents study on prevention in digital hydrology and mountain area property.
Detailed description of the invention
Fig. 1 is calculation process signal;
Fig. 2 is big sill may basin schematic diagram;
Fig. 3 is Lorentz curve schematic diagram;
Fig. 4 is rainfall critical line schematic diagram in the big uniform situation of sill may Basin Rainfall;
Fig. 5 is rainfall critical line schematic diagram in the big uneven situation of sill may Basin Rainfall;
Fig. 6 is rainfall critical line schematic diagram in the case of big sill may Basin Rainfall is concentrated.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawing:
As shown in Figure 1, the invention discloses a kind of, the Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning Method, comprising the following steps:
Step 1, the flow and rainfall data information in all previous peb process in basin are collected, for flood mistake each time Journey takes passages the rainfall data before flood peak occurs in the T period, and calculates the accumulation rainfall in the T period, and T is whole more than or equal to 2 Number;
Step 1.1, the flow and rainfall data information in all previous peb process in basin are collected, for flood mistake each time Journey:
Step 1.1.1, finds out maximum flow value in peb process, and at the time of determine that maximum flow value occurs, i.e., MQ_T between the peak of flood is current;
Step 1.1.2 takes passages the rainfall data Seq_P before flood peak occurs in the T period;
Seq_P={ PMQ_T,PMQ_T-1,PMQ_T-2…PMQ_T-T}
In formula, PMQ_TFor the rainfall at MQ_T moment;PMQ_T-1For the rainfall at MQ_T-1 moment;PMQ_T-2When for MQ_T-2 The rainfall at quarter;PMQ_T-TFor the rainfall at MQ_T-T moment;
Step 1.1.3 calculates the accumulation rainfall AccP in the T period;
Step 2, for each flood events, the rainfall data before being occurred according to its flood peak in the T period construct Lorentz Curve calculates the Gini coefficient of Lorentz curve, then by Gini coefficient respectively with pre-set Gini coefficient threshold X G, DG It is compared and then the rainfall of peb process is divided, XG < DG, if 0 < G≤XG, it is believed that rain types are equal It is even, if XG < G≤DG, it is believed that rain types be it is uneven, if DG < G, it is believed that rain types be concentrate;
Step 2.1, for each flood events:
The ascending sequence of rainfall in Seq_P is obtained NSeq_P by step 2.1.1;
NSeq_P={ P0,P1…Pj…PT}
In formula, j is the integer for being less than or equal to T more than or equal to 0;
Accumulation period Precipitation Series ASeq_P is calculated based on NSeq_P in step 2.1.2;
ASeq_P={ AP0,AP1…APj…APT}
In formula, APjAccumulation period rainfall when for the period being j,
Step 2.1.3 calculates the accumulation period rainfall percentage in Seq_P, obtains accumulation period rainfall Percent sequence ANSeq_P;
NSeq_P={ F0,F1…Fj…FT}
In formula,
Step 2.1.4 calculates Gini coefficient G based on ASeq_P and ANSeq_P;
Step 2.2, by the Gini coefficient G of all previous rainfall respectively with pre-set Gini coefficient threshold X G, DG into Row relatively, and then classify to all previous rainfall, XG < DG, if 0 < G≤XG, it is believed that rain types be it is uniform, if XG < G≤DG, it is believed that rain types be it is uneven, if DG < G, it is believed that rain types be concentrate.
Step 3, the tension water content saturation degree at T moment before flood peak occurs in each flood events is counted, i.e., initial soil Earth water content saturation degree;
Step 4, for each flood events, judge whether it is super alert flood, and respectively to uniform, uneven, collection In the other flood peak of three types occur before rainfall production accumulation rainfall-initial soil moisture content saturation degree scatter plot in the T period, The corresponding point of super alert flood is marked, draws Critical Rainfall line in conjunction with the corresponding point of super alert flood;
Step 4.1, for each flood events, judge whether it is super alert flood:
Step 4.1.1 calculates tension water content dynamic changing process and the safety in basin using Xinanjiang model The Variations in Flow Changes of protected object position;
Step 4.1.2 counts the soil tension water content saturation degree at T moment before flood peak, i.e. initial soil moisture content is saturated Spend Init_W;
Init_W=WMQ_T-T/WM
In formula, WMQ_T-TFor the tension water content at MQ_T-T moment in basin;WM is basin tension water capacity;
Step 4.1.3, the early warning of taking precautions against natural calamities that river basin authority is investigated or consulted by floodmark on the spot are planned to obtain safety The Alarm flow Warn_Q of protected object position;
Step 4.1.4 determines maximum stream flow Max_Q based on the Variations in Flow Changes of safeguard protection object position;
Step 4.1.5 judges flood for super alert flood if Max_Q >=Warn_Q in peb process;
Step 4.2, the rainfall before occurring respectively to uniform, uneven, the other flood peak of three types of concentration in the T period Rainfall-initial soil moisture content saturation degree scatter plot is accumulated in production, is marked in scatter plot using cross symbol super alert big vast Not super alert flood is marked using circle symbol in water;
Step 4.3, according to cross symbol and circle symbol in accumulation rainfall-initial soil moisture content saturation degree scatter plot Distribution characteristics, using W-H (widrow-hoff) algorithm based on minimum variance principle, draw critical warning rainfall line to get Critical Rainfall line into basin under different types of rainfall, under various soil water status conditions.
Step 5, based on real-time rainfall data and soil moisture content saturation degree, judge whether to occur in conjunction with Critical Rainfall line Super alert flood such as occurs, and issues mountain torrents early warning to current rainfall:
In real-time early warning, the initial soil of accumulation rainfall and preceding T moment before continuous this moment of circle statistics in the T period Earth water content saturation degree calculates the Gini coefficient of rainfall in preceding T time section, so that the classification of rainfall is judged, by the secondary drop This turns to data point to rain process, is labeled in accumulation rainfall-initial soil moisture content saturation degree scatter plot of corresponding classification, if The position of the point marked judges that super alert flood occurs, issues mountain torrents early warning in the top of Critical Rainfall line.
By taking the big sill may basin in Shaanxi Province as an example, as shown in Fig. 2, the basin is located in Qinling Mountains southern foot, water collection basin area is about 2182km2, total river is about 161km, river average gradient about 5.44 ‰., upstream is largely high Zhongshan District, absolute elevation 700- 3500m, mountain shape is grand, and the folded barrier of weight mountains in a range, peak valley is alternate, breaking topography, and hillside is mostly concave-convex slope, and only in watershed, one band is distributed with Staight slope, mean inclination is between 40-60 °.Along the river there are low mountains and hills, the natural landscape approximation Huashan in two sides.Belong to warm temperature in basin Band broad-leaved deciduous forest and the wealthy mixed forest belt of needle, the Vertical Distribution Law of forest form is obvious, and basin afforestation rate is 82%.Stream Domain is ploughed in geology and makes upper category south Qingling fold belt.It is main to build rock are as follows: rotten migmatite class, granite also have fragmentary distribution. Using yellowish soil, brown earth as representative in basin.SOIL DISTRIBUTION has drab soil, cinnamon soil, brown brown earth, alpine meadow soil from bottom to top.By In the weathering of parent rock, there is sand soil distribution on basin surface layer.
Basin is located at north temperate zone, belongs to continental monsoon climate, 700~900mm of mean annual precipitation, and river water is main It is rainwater supply, isolated storm is the main reason for flood occurs.Basin is averaged 100~500mm of height of run-off, runoff coefficient 0.2~0.5, it is relatively high Runoff Generating Area, 100~200t/km of erosion modulus2
It studies area's rainfall initial data and is seen using 17 precipitation station observations in basin between -2018 years 2010 by hour rainfall Measured data.
Step 1: collecting flow and rainfall data of the big sill may basin between 2010 to 2018 in all previous peb process Data, and the rainfall data in each flood events in flood peak appearance preceding 12 period are taken passages, calculate the accumulation drop in 12 periods Rainfall, specifically includes the following steps:
1) flow and rainfall data information of the big sill may basin between 2010 to 2018 in all previous peb process are collected, At the time of finding out maximum flow value in peb process, and determine that maximum flow value occurs in each flood events, as MQ_T between the peak of this flood is current;
2) the rainfall data Seq_P in flood peak appearance preceding 12 period is taken passages;
Seq_P={ PMQ_T,PMQ_T-1,PMQ_T-2…PMQ_T-12}
In formula: PMQ_TFor the rainfall at MQ_T moment;PMQ_T-1For the rainfall at MQ_T-12 moment;PMQ_T-12For MQ_T-12 The rainfall at moment;Successively push away class, PMQ_T-12For the rainfall at MQ_T-12 moment, this series of rainfall is constituted as flood Rainfall data Seq_P before peak occurs in the T period;The value of T is determined depending on specific watershed concentration feature and Alert Standard.
3) the accumulation rainfall AccP in the T period is calculated;
In formula: MQ_T-i is the subscript of rainfall, changes to MQ_T-12 from MQ_T, i.e. i changes to 12 from 0.
Step 2: the rainfall data in preceding 12 period occur based on the flood peak taken passages out constructs Lorentz curve, such as Fig. 3 institute Show, calculates the Gini coefficient of Lorentz curve, and the rainfall in the preceding T period is occurred into flood peak according to Gini coefficient and is divided into It is even, unevenly, three classes are concentrated, specifically includes the following steps:
1) by the ascending sequence of rainfall in Seq_P, NSeq_P is obtained;
NSeq_P={ P0,P1…Pj…P12}
In formula: j is the subscript of rainfall, changes to 12 from 0;And P0<P1<…<Pj<…P12, i.e., with the increase of subscript j, PjValue be also increasing.
2) accumulation period Precipitation Series ASeq_P is calculated based on NSeq_P;
ASeq_P={ AP0,AP1…APj…AP12}
In formula: APjAccumulation period rainfall when for the period being j, and AP0<AP1<…<APj<…AP12, i.e., with subscript j's Increase, PjValue be also increasing, maximum AP12Value be Accp.Specific calculation method is as follows:
In formula: k is rainfall P0To PjBetween subscript, change to j from 0.
3) the accumulation period rainfall percentage in Seq_P is calculated, accumulation period rainfall Percent sequence ANSeq_P is obtained;
NSeq_P={ F0,F1…Fj…F12}
In formula: j changes to T from 0;F0<F1<…<Fj<…F12, i.e., with the increase of subscript j, FjValue also constantly increasing Greatly, maximum F12Value be 1.Specific FjCalculation method it is as follows:
4) Gini coefficient G is calculated based on ASeq_P and ANSeq_P;
5) using 2) between 4) the step of, calculate the Gini coefficient of rainfall each time, and will according to Gini coefficient The rainfall that flood peak occurred in preceding 12 period is divided into uniformly, unevenly, concentrates three classes;
In conjunction with basin comprehensive natural geographic basis and practical early-warning and predicting operating experience, it is arranged threshold X G (being set as 0.3) With DG (being set as 0.5), think as 0 < G≤0.3 rain types be it is uniform, think as 0.3 < G≤0.5 rain types be not Uniformly, rain types are thought when as 0.5 < G to concentrate.
Step 3: judge whether flood is super alert flood, respectively to uniform, unevenly, the other rainfall system of three types is concentrated Make accumulation rainfall-initial soil moisture content saturation degree scatter plot, and mark the corresponding point of super alert flood, in conjunction with super alert flood pair The point answered draws Critical Rainfall line, specifically includes the following steps:
1) Xinanjiang model is used, the tension water content dynamic changing process and safeguard protection object in basin are calculated The Variations in Flow Changes of position;
2) count flood peak before 12 moment soil tension water content saturation degree, i.e. initial soil moisture content saturation degree Init_ W;
Init_W=WMQ_T-12/WM
In formula: WMQ_T-12For the tension water content at MQ_T-12 moment in basin;WM is basin tension water capacity.
3) it plans to obtain safeguard protection object by the investigation of floodmark on the spot or the early warning of taking precautions against natural calamities of access river basin authority The Alarm flow Warn_Q of position, the value are about 1000m in big sill may basin3/s;
4) Variations in Flow Changes based on the safeguard protection object position being calculated in step 3.1 determines maximum Flow Max_Q;
If 5) Max_Q >=Warn_Q in peb process, judge this flood for super alert flood.Inhomogeneity is made respectively Super alert flood is used cross in scatter plot by accumulation rainfall-initial soil moisture content saturation degree scatter plot under the rainfall of type Symbol is marked, and not super alert flood is marked using circle symbol;
6) distribution according to cross symbol and circle symbol in accumulation rainfall-initial soil moisture content saturation degree scatter plot Feature draws critical warning rainfall line to get to basin using W-H (widrow-hoff) algorithm based on minimum variance principle In under different types of rainfall, the Critical Rainfall line under various soil water status conditions, as shown in Fig. 4, Fig. 5, Fig. 6.
Step 4: judging whether to need with soil moisture content saturation degree based on real-time rainfall data in real-time early warning Mountain torrents early warning is issued to current rainfall, specifically includes the following steps:
In real-time early warning, accumulation rainfall and preceding 12 moment before continuous this moment of circle statistics in 12 periods it is initial Soil moisture content saturation degree calculates the Gini coefficient of rainfall in preceding 12 period, so that the classification of rainfall is judged, by the secondary drop This turns to data point to rain process, is labeled in accumulation rainfall-initial soil moisture content saturation degree scatter plot of corresponding classification, if Mountain torrents early warning is then issued in the top of Critical Rainfall line in the position of the point marked.
Those skilled in the art can understand that unless otherwise defined, all terms used herein (including skill Art term and scientific term) there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Also It should be understood that those terms such as defined in the general dictionary should be understood that have in the context of the prior art The consistent meaning of meaning will not be explained in an idealized or overly formal meaning and unless defined as here.
Above-described specific embodiment has carried out further the purpose of the present invention, technical scheme and beneficial effects It is described in detail, it should be understood that being not limited to this hair the foregoing is merely a specific embodiment of the invention Bright, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the present invention Protection scope within.

Claims (5)

1. the method that the Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning, which is characterized in that including following step It is rapid:
Step 1, the flow and rainfall data information collected in all previous peb process in basin pluck each flood events The rainfall data before flood peak occurs in the T period are recorded, and calculate the accumulation rainfall in the T period, T is the integer more than or equal to 2;
Step 2, for each flood events, the rainfall data before being occurred according to its flood peak in the T period construct Lorentz curve, The Gini coefficient of Lorentz curve is calculated, then carries out Gini coefficient with pre-set Gini coefficient threshold X G, DG respectively Compare, and then the rainfall of peb process divided, XG < DG, if 0 < G≤XG, it is believed that rain types be it is uniform, such as Fruit XG < G≤DG, it is believed that rain types be it is uneven, if DG < G, it is believed that rain types be concentrate;
Step 3, the tension water content saturation degree at T moment before flood peak occurs in each flood events is counted, i.e. initial soil contains Water saturation degree;
Step 4, for each flood events, judge whether it is super alert flood, and respectively to uniform, uneven, concentration three Rainfall production accumulation rainfall-initial soil moisture content saturation degree scatter plot before the other flood peak of type occurs in the T period, marks The corresponding point of super alert flood draws Critical Rainfall line in conjunction with the corresponding point of super alert flood;
Step 5, based on real-time rainfall data and soil moisture content saturation degree, judge whether that super police occurs in conjunction with Critical Rainfall line Flood such as occurs, and issues mountain torrents early warning to current rainfall.
2. the method that the Critical Rainfall according to claim 1 based on rainfall rainfall process carries out real-time mountain torrents early warning, It is characterized in that, specific step is as follows for the step 1:
Step 1.1, the flow and rainfall data information in all previous peb process in basin are collected, for each flood events:
Step 1.1.1, finds out maximum flow value in peb process, and at the time of determine that maximum flow value occurs, i.e. flood Peak it is current between MQ_T;
Step 1.1.2 takes passages the rainfall data Seq_P before flood peak occurs in the T period;
Seq_P={ PMQ_T,PMQ_T-1,PMQ_T-2…PMQ_T-T}
In formula, PMQ_TFor the rainfall at MQ_T moment;PMQ_T-1For the rainfall at MQ_T-1 moment;PMQ_T-2For the MQ_T-2 moment Rainfall;PMQ_T-TFor the rainfall at MQ_T-T moment;
Step 1.1.3 calculates the accumulation rainfall AccP in the T period;
3. the method that the Critical Rainfall according to claim 1 based on rainfall rainfall process carries out real-time mountain torrents early warning, Be characterized in that, it is in the step 2 specifically includes the following steps:
Step 2.1, for each flood events:
The ascending sequence of rainfall in Seq_P is obtained NSeq_P by step 2.1.1;
NSeq_P={ P0,P1…Pj…PT}
In formula, j is the integer for being less than or equal to T more than or equal to 0;
Accumulation period Precipitation Series ASeq_P is calculated based on NSeq_P in step 2.1.2;
ASeq_P={ AP0,AP1…APj…APT}
In formula, APjAccumulation period rainfall when for the period being j,
Step 2.1.3 calculates the accumulation period rainfall percentage in Seq_P, obtains accumulation period rainfall Percent sequence ANSeq_P;
NSeq_P={ F0,F1…Fj…FT}
In formula,
Step 2.1.4 calculates Gini coefficient G based on ASeq_P and ANSeq_P;
Step 2.2, the Gini coefficient G of all previous rainfall is compared with pre-set Gini coefficient threshold X G, DG respectively Compared with, and then classify to all previous rainfall, XG < DG, if 0 < G≤XG, it is believed that rain types be it is uniform, if XG < G≤ DG, it is believed that rain types be it is uneven, if DG < G, it is believed that rain types be concentrate.
4. the method that the Critical Rainfall according to claim 1 based on rainfall rainfall process carries out real-time mountain torrents early warning, It is characterized in that, specific step is as follows for the step 4:
Step 4.1, for each flood events, judge whether it is super alert flood:
Step 4.1.1 calculates tension water content dynamic changing process and the safeguard protection in basin using Xinanjiang model The Variations in Flow Changes of object position;
Step 4.1.2 counts the soil tension water content saturation degree at T moment before flood peak, i.e. initial soil moisture content saturation degree Init_W;
Init_W=WMQ_T-T/WM
In formula, WMQ_T-TFor the tension water content at MQ_T-T moment in basin;WM is basin tension water capacity;
Step 4.1.3, the early warning of taking precautions against natural calamities that river basin authority is investigated or consulted by floodmark on the spot are planned to obtain safeguard protection The Alarm flow Warn_Q of object position;
Step 4.1.4 determines maximum stream flow Max_Q based on the Variations in Flow Changes of safeguard protection object position;
Step 4.1.5 judges flood for super alert flood if Max_Q >=Warn_Q in peb process;
Step 4.2, the rainfall before occurring respectively to uniform, uneven, the other flood peak of three types of concentration in the T period makes Rainfall-initial soil moisture content saturation degree scatter plot is accumulated, super alert flood is marked, adopts using cross symbol in scatter plot Not super alert flood is marked with circle symbol;
Step 4.3, point according to cross symbol and circle symbol in accumulation rainfall-initial soil moisture content saturation degree scatter plot Cloth feature draws critical warning rainfall line using W-H (widrow-hoff) algorithm based on minimum variance principle to get stream is arrived Critical Rainfall line in domain under different types of rainfall, under various soil water status conditions.
5. the method that the Critical Rainfall according to claim 1 based on rainfall rainfall process carries out real-time mountain torrents early warning, It is characterized in that, specific step is as follows for the step 5:
In real-time early warning, the initial soil of accumulation rainfall and preceding T moment before continuous this moment of circle statistics in the T period contains Water saturation degree calculates the Gini coefficient of rainfall in preceding T time section, so that the classification of rainfall is judged, by the secondary rainfall This turns to data point to journey, is labeled in accumulation rainfall-initial soil moisture content saturation degree scatter plot of corresponding classification, if marking Point position in the top of Critical Rainfall line, judge to occur super alert flood, issue mountain torrents early warning.
CN201910191242.6A 2019-03-13 2019-03-13 Method for carrying out real-time mountain torrent early warning based on critical rainfall of rainfall time-course distribution Expired - Fee Related CN109920213B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910191242.6A CN109920213B (en) 2019-03-13 2019-03-13 Method for carrying out real-time mountain torrent early warning based on critical rainfall of rainfall time-course distribution

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910191242.6A CN109920213B (en) 2019-03-13 2019-03-13 Method for carrying out real-time mountain torrent early warning based on critical rainfall of rainfall time-course distribution

Publications (2)

Publication Number Publication Date
CN109920213A true CN109920213A (en) 2019-06-21
CN109920213B CN109920213B (en) 2020-10-23

Family

ID=66964707

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910191242.6A Expired - Fee Related CN109920213B (en) 2019-03-13 2019-03-13 Method for carrying out real-time mountain torrent early warning based on critical rainfall of rainfall time-course distribution

Country Status (1)

Country Link
CN (1) CN109920213B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111027764A (en) * 2019-12-06 2020-04-17 中国水利水电科学研究院 Flood forecasting method suitable for runoff data lack basin based on machine learning
CN111047213A (en) * 2019-12-25 2020-04-21 长江水利委员会水文局 Middle and long term water resource critical early warning index method based on multi-factor joint discrimination
CN111462450A (en) * 2020-01-16 2020-07-28 华中科技大学 Mountain torrent early warning method considering rainfall spatial heterogeneity

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101864750A (en) * 2010-06-29 2010-10-20 西安理工大学 Multi-model meta-synthesis flood forecasting system and forecasting method thereof
CN102013150A (en) * 2010-09-28 2011-04-13 浙江工业大学 System for predicting geologic hazard based on rainfall intensity, moisture content of slope soil and deformation
CN102169617A (en) * 2011-04-15 2011-08-31 中国科学院水利部成都山地灾害与环境研究所 Early warning method of mud-rock flow used in regions short of rainfall data
JP2012086747A (en) * 2010-10-21 2012-05-10 Bridgestone Corp Method and device for predicting hydroplaning phenomenon
CN103197046A (en) * 2013-04-04 2013-07-10 中国科学院、水利部成都山地灾害与环境研究所 Method for measuring volume water content of debris flow critical soil body and debris flow pre-warning method
CN104299367A (en) * 2014-10-23 2015-01-21 中国科学院、水利部成都山地灾害与环境研究所 Landslide hazard multi-stage comprehensive monitoring and early warning method
CN204759699U (en) * 2015-07-31 2015-11-11 珠江水利委员会珠江水利科学研究院 Mountain torrents calamity monitoring and early warning device
CN107085658A (en) * 2017-04-19 2017-08-22 郑州大学 A kind of mountain flood time of causing disaster determines method
CN108597189A (en) * 2018-04-24 2018-09-28 河海大学 Small watershed geological disaster and flood warning method in distribution based on Critical Rainfall
CN108647805A (en) * 2018-04-03 2018-10-12 郑州大学 A kind of mountain flood Critical Rainfall comprehensive test method

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101864750A (en) * 2010-06-29 2010-10-20 西安理工大学 Multi-model meta-synthesis flood forecasting system and forecasting method thereof
CN102013150A (en) * 2010-09-28 2011-04-13 浙江工业大学 System for predicting geologic hazard based on rainfall intensity, moisture content of slope soil and deformation
JP2012086747A (en) * 2010-10-21 2012-05-10 Bridgestone Corp Method and device for predicting hydroplaning phenomenon
CN102169617A (en) * 2011-04-15 2011-08-31 中国科学院水利部成都山地灾害与环境研究所 Early warning method of mud-rock flow used in regions short of rainfall data
CN103197046A (en) * 2013-04-04 2013-07-10 中国科学院、水利部成都山地灾害与环境研究所 Method for measuring volume water content of debris flow critical soil body and debris flow pre-warning method
CN104299367A (en) * 2014-10-23 2015-01-21 中国科学院、水利部成都山地灾害与环境研究所 Landslide hazard multi-stage comprehensive monitoring and early warning method
CN204759699U (en) * 2015-07-31 2015-11-11 珠江水利委员会珠江水利科学研究院 Mountain torrents calamity monitoring and early warning device
CN107085658A (en) * 2017-04-19 2017-08-22 郑州大学 A kind of mountain flood time of causing disaster determines method
CN108647805A (en) * 2018-04-03 2018-10-12 郑州大学 A kind of mountain flood Critical Rainfall comprehensive test method
CN108597189A (en) * 2018-04-24 2018-09-28 河海大学 Small watershed geological disaster and flood warning method in distribution based on Critical Rainfall

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111027764A (en) * 2019-12-06 2020-04-17 中国水利水电科学研究院 Flood forecasting method suitable for runoff data lack basin based on machine learning
CN111027764B (en) * 2019-12-06 2020-07-31 中国水利水电科学研究院 Flood forecasting method suitable for runoff data lack basin based on machine learning
CN111047213A (en) * 2019-12-25 2020-04-21 长江水利委员会水文局 Middle and long term water resource critical early warning index method based on multi-factor joint discrimination
CN111462450A (en) * 2020-01-16 2020-07-28 华中科技大学 Mountain torrent early warning method considering rainfall spatial heterogeneity

Also Published As

Publication number Publication date
CN109920213B (en) 2020-10-23

Similar Documents

Publication Publication Date Title
CN111582755B (en) Mountain torrent disaster comprehensive risk dynamic assessment method based on multi-dimensional set information
CN109920213A (en) The method that Critical Rainfall based on rainfall rainfall process carries out real-time mountain torrents early warning
Meko et al. The tree‐ring record of severe sustained drought 1
Chu et al. Spatial and temporal variability of daily precipitation in Haihe River basin, 1958–2007
Mack Landscape as a predictor of wetland condition: an evaluation of the landscape development index (LDI) with a large reference wetland dataset from Ohio
Li et al. Observed changes in streamflow at the headwaters of the Urumqi River, eastern Tianshan, central Asia
Bari Abarghouei et al. The survey of climatic drought trend in Iran
CN109993350A (en) A kind of Critical Rainfall evaluation method based on spatially distributed rainfall
McCabe et al. Recent declines in western US snowpack in the context of twentieth-century climate variability
Baldi et al. Hail occurrence in Italy: Towards a national database and climatology
CN108960599A (en) Transmission line of electricity Rainfall Disaster fining prediction technique and system based on inversion algorithm
Zakhem et al. Investigation of hydrological drought using Cumulative Standardized Precipitation Index (SPI 30) in the eastern Mediterranean region (Damascus, Syria)
Wu et al. Spatiotemporal variations in extreme precipitation on the middle and lower reaches of the Yangtze River Basin (1970–2018)
CN103646157B (en) Method for evaluating transmission line fault caused by rainstorm
Lee et al. Use of Landsat TM/ETM+ data to analyze urban heat island and its relationship with land use/cover change
Lu et al. Evaluation and spatial distribution characteristics of freeze-thaw erosion intensity in the Yalu Tsangpo River basin on the basis of geographic information system
Sharma et al. Analysis of wind characteristics parameters with the application of lidar and mast
Li et al. Combined effect of boundary layer recirculation factor and stable energy on local air quality in the Pearl River Delta over southern China
Esfandiari et al. The effect of atmospheric rivers on cold-season heavy precipitation events in Iran
Freda et al. A pilot study of the wind speed along the Rome–Naples HS/HC railway line.: Part 2—Probabilistic analyses and methodology assessment
Ayantobo et al. Climatology of landfalling atmospheric rivers and its attribution to extreme precipitation events over Yangtze River Basin
Zhang et al. Mesoscale climatology and variation of surface winds over the Chukchi–Beaufort coastal areas
Zhang et al. A temperature indicator for heavy air pollution risks (TIP)
Fan et al. Near-surface heat transfer at two gentle slope sites with differing aspects, Qinghai-Tibet Plateau
Homan et al. Arctic snow distribution patterns at the watershed scale

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
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20201023

CF01 Termination of patent right due to non-payment of annual fee