CN103488871B - A kind of Flood Forecasting Method in basin without Streamflow Data - Google Patents
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Abstract
The invention discloses the Flood Forecasting Method in a kind of basin without Streamflow Data, have the preferable basin of history Streamflow Data, the value of forecasting for completed, in advance the drainage characteristics information after its model parameter, clustering processing is stored in database；Carry out giving the correct time in advance without Streamflow Data basin, first underground properties information in basin is carried out clustering processing automatically, in large watershed residing for this basin, then find the basin similar to each model parameter one by one, and this model parameter of analogy basin and the characteristic information being determined in advance are carried out correlation analysis, finally determine each parameter.The present invention is on the basis of the forecast accumulation of a large amount of basins, complete automatically the choosing of non-avaible forecast basin analogy basin, from dynamic correlation and finally the determining of model parameter, artificial subjective judgement error can be prevented effectively from, and improve efficiency, lay the foundation for the forecast of Cross Some Region Without Data on a large scale.
Description
Technical field
The present invention relates to the Flood Forecasting Method in a kind of basin without Streamflow Data, belong to flood forecasting technical field.
Background technology
Hydrologic process in nature is extremely complex, is affected by many factors, generally uses the hydrological model of generalization to enter
Row forecast, model parameter is mainly affected by features such as landform, landforms, underlying surfaces, and the important process of hydrologic forecast is i.e. suitable in employing
On the basis of model, determine the current Hydro-Model Parameter Calibration Technology forecasting basin.In major part basin, Hydro-Model Parameter Calibration Technology is by big
The history Streamflow Data simulation of amount calculates and (information such as rainfall, evaporation is substituted into model, makes the footpath of calculating flow through by adjusting parameter
Journey is coincide with reality)；But build less in early days because of rainfall/hydrometric station construction, history Streamflow Data sequence is the shortest, it is impossible to meet pre-
Report demand；Affecting because of mankind's activity etc. simultaneously, cause runoff characteristic generation large change, original data cannot reflect
Current water characteristic, causes data unavailable.In order to solve non-avaible/few data area hydrologic forecast problem, the international hydrology
Scientific institution (IAHS) starts the ten year plan of abbreviation " PUB " (unga(u)ged basin hydrologic forecast), to reduce hydrologic forecast
Uncertainty is core, it is intended to explores the new method of hydrological simulation, realize the important breakthrough that the hydrology is theoretical, especially sends out to meet
The exhibition socioeconomic needs of Chinese Home.
The method forecast without Streamflow Data River Basin Hydrology was included hydrologic assimilation method, parameter isoline method, runoff in the past
Y-factor method Y, regional experience equation, stochastic simulation method etc..Diverting from one use to another of the main thought of conventional method usually data, but ginseng
The selection examining station (basin) does not has effective method, is affected by hydrologist's subjective experience to a great extent.Footpath
The spatial variations of stream characteristic value is closely related with basin physical characteristic and meteorologic factor etc., fields method
(regionalization) i.e. grow up on the basis of this, i.e. find target basin (non-avaible stream by basin attribute
Territory) reference basin (having data basin), utilize and have the model parameter in data basin to inquire into the model parameter of unga(u)ged basin, from
And unga(u)ged basin is forecast.The common method of compartmentalization includes closely located method, attribute similarity method and the Return Law three kinds
Method, (1) closely located method refers to find out and study basin (unga(u)ged basin) apart from upper close one (or multiple) stream
(there is data basin in territory), and using its parameter as the parameter studying basin, its research is according to physics and the weather being the same area
Attribute Relative is consistent, and the hydrologic behavior in the most adjacent basin is similar.(2) attribute similarity method refers to find out and study basin attribute
(such as soil, landform, vegetation and weather etc.) upper similar basin, and using its parameter as the parameter studying basin.(3) Return Law
Refer to, according to model parameter and the basin attribute having data basin, set up multiple regression equation therebetween, thus utilize nothing
The basin attribute in data basin inquires into its model parameter.
Prior art has a disadvantage in that
Analogy basin is chosen and is lacked comprehensive, objectivity: existing research generally selects one or more landform, geomorphic feature to join
The composite index (such as topographic index ln (α/tan β)) of number differentiates as attribute finds analogy basin, then carries out diverting from one use to another of parameter
Or analyze.Because the physical significance of different model parameters is different, carry out differentiating not only in accordance with certain or several drainage characteristics parameter
Comprehensively, it is difficult to reflect that real basin is similar；Use all drainage characteristics analyses exist contain much information, complicated classification, it is impossible to sentence
Disconnected problem.
Prior art does not considers the difference of different parameters: Cross Some Region Without Data parameter generally uses and diverts from one use to another or regression analysis at present
Determining: the most first find with reference to basin when diverting from one use to another, the most all parameters are unified diverts from one use to another；Regression analysis the most first determines and to be analyzed
Basin, the most each parameter is carried out in same basin group.It practice, the physical significance that in hydrological model, each parameter represents
Difference, because each basin has it unique, is difficult to find the basin of the correlated characteristic all similar of all parameters with model, and
Study and found with reference to basin only in accordance with one or more characteristic variables, and the unification of all parameters has been diverted from one use to another or used and flowed with some
The uniqueness of parameter cannot be reflected in territory.
Subjectivity differentiates, efficiency is low: prior art all uses the mode of artificial cognition, process, attempts solving Cross Some Region Without Data
Flood forecasting problem, employing technology is difficult to large-scale popularization, and wherein comprises artificial subjectivity, inefficiency.
Summary of the invention
For making up the defect of prior art, the invention provides the Flood Forecasting Method in a kind of basin without Streamflow Data, adopt
It is analyzed by all retrievable related streams characteristic of field information so that choosing of analogy basin is more objective, comprehensively.
The present invention is to use following technological means to realize goal of the invention:
The Flood Forecasting Method in a kind of basin without Streamflow Data, comprises the steps
1) Land_use change and soil characteristic information to all existing first-class Prediction version basins carry out clustering processing, described
Land_use change and soil characteristic information are mainly various vegetation coverage and soil types coverage rate；
2) each parameter to hydrological model, chooses all or part of drainage characteristics information and carries out stepwise regression analysis,
Determine the drainage characteristics information relevant to this parameter；
3) for all existing first-class Prediction version basins, drainage characteristics information database is set up；
4) basin without Streamflow Data to parameter to be determined, first according to longitude and latitude automatically from the Internet download digital elevation
Model data and vegetation, soil information, then use Law of DEM Data to carry out basin relevant information extraction, and to planting
Quilt, soil information clusters, and obtains the drainage characteristics information identical with aforementioned existing first-class Prediction version basin；
5) in described step 3) the drainage characteristics information database set up is found with parameter to be determined without Streamflow Data
Basin belongs to the sub basin of a large watershed；
6) for each parameter of hydrological model, it is first depending on described step 2) basin relevant to this parameter that determine
Characteristic information, in described step 5) in the sub basin selected seeks the basin without Streamflow Data of parameter to be determined based on this ginseng
The analogy basin of number, if analogy basin number meets certain requirements, it is determined that this sub basin is analogy basin；Otherwise in described step
Rapid 5) analogy basin is sought in the upper level basin perimeter of large watershed, until meeting number requirement；
7) each parameter to be determined to hydrological model, in described step 6) in the analogy basin that determines, to this ginseng
The characteristic information that number is relevant carries out correlation analysis, sets up the regression equation of this parameter and drainage characteristics information, obtains coefficient correlation,
And determine this parameter；
8), after the parameter determination all to be determined of hydrological model, parameter can be brought into flood forecast system, carry out this nothing
The flood forecasting in Streamflow Data basin.
Aforesaid Land_use change cluster is deep root vegetation coverage and the big class of shallow root vegetation coverage two.
Aforesaid soil characteristic information cluster is two big classes, and wherein the first big class is divided into again two groups, particularly as follows: first is big
Class the first group: dwarf soil coverage rate, Anthrosol's coverage rate, rhogosol coverage rate；First big class the second group: alfisol covers
Rate, inceptisol coverage rate, Alisol coverage rate, acrisol coverage rate；Second largest class: Lixisol covers
Rate, impact soil coverage rate, gleisoil coverage rate, planosol coverage rate, podzolic soil coverage rate, sand dune coverage rate, rock outcrop soil
Coverage rate, water body (in soil) coverage rate.
Aforesaid step 3) drainage characteristics information database include watershed information, watershed unit characteristic information, described step
Rapid 1) the soil types information after the clustering processing obtained, the vegetation pattern information after clustering processing, the hydrology mould that basin uses
Shape parameter information, described step 2) landform relevant to Hydro-Model Parameter Calibration Technology that obtain, soil and vegetation information.
Aforesaid step 6) in, seek analogy basin and refer to the sub basin for higher level basin, parameter basin to be determined, adopt
The drainage characteristics information relevant to this Hydro-Model Parameter Calibration Technology with it clusters, when the distance of cluster is less than a certain limit value,
It is analogy basin.
Aforesaid step 6) in, the number that analogy basin meets requires as more than or equal to 5.
Aforesaid step 7) in, if coefficient correlation is less than 0.8, then the basin without Streamflow Data of this parameter to be determined is pre-
Report scheme degradation uses.
By using above-mentioned technological means, the invention have the benefit that
1) completed for the history forecasting model parameter with degree of precision and drainage characteristics information are all designed and be stored in
In database, can conveniently inquire about information and the parameter forecasting basin, it is simple to be analyzed, statistics etc.；
2) parameter determination process is more objective: the parameter determination process that the present invention relates to, and each step is all according to being previously set
Rule, computer automatically seek, as the selection of analogy basin determine, the clustering processing etc. of drainage characteristics information, it is to avoid
The artificial subjectivity judged, makes parameter determination process more objective；
3) information and technological approaches are used more comprehensively: the present invention is the selection of drainage characteristics information, choosing of analogy basin
Etc. aspect, all have employed all information that can obtain, be that each parameter chooses different analogy basin according to parameter characteristic simultaneously,
Make Cross Some Region Without Data Flood Forecasting Model parameter determination method at the aspect such as firsthand information, technological approaches the most more comprehensively；
4) area without runoff data model parameter determines in hgher efficiency: the present invention is by the determination of Cross Some Region Without Data model parameter
Method is designed as the system of complete set, from the process of drainage characteristics information, analogy basin seek the determination to dependency relation
It is automatically performed according to the rule set by system so that whole process efficiency is higher.
Accompanying drawing explanation
Fig. 1 is that the present invention determines flow chart without Streamflow Data river basin flood forecast parameter；
Fig. 2 is land use pattern Cluster tendency of the present invention；
Fig. 3 is soil characteristic information cluster pedigree chart of the present invention.
Detailed description of the invention
The present invention will be further described with detailed description of the invention below in conjunction with the accompanying drawings.
As it is shown in figure 1, the Flood Forecasting Method in the basin without Streamflow Data of the present invention, comprise the steps:
1) information that drainage characteristics is relevant includes landform, Land_use change and soil characteristic information three class, wherein Land_use change,
Soil characteristic is mainly the coverage rate of various vegetation, soil types, classifies relatively thin, and such as Land_use change coverage rate includes often
Green coniferous forest, evergreen broadleaf forest, meadows etc. more than ten are planted.It practice, Hydro-Model Parameter Calibration Technology and vegetation, soil mainly show as pine coupling
Close relevant, such as multiple studies have shown that basin average Free water reservoir capacity SM is relevant to forest rate, will not be specific to evergreen
The correlation analysis such as coniferous forest, evergreen broadleaf forest, therefore, the present invention is first sharp to the soil in all existing first-class Prediction version basins
Cluster by, soil characteristic information.As Land_use change clusters as in figure 2 it is shown, see from right to left, hierarchical classification, the present invention will
It is divided into deep root vegetation coverage, the big class of shallow root vegetation coverage two；Soil characteristic information cluster is as it is shown on figure 3, from right to left
Seeing, the present invention is classified as two big classes, and wherein the first big class is divided into again two groups, is specifically categorized as: first big class the first group:
Dwarf soil coverage rate, Anthrosol's coverage rate, rhogosol coverage rate；First big class the second group: alfisol coverage rate, inceptisol cover
Lid rate, Alisol coverage rate, acrisol coverage rate；Second largest class: Lixisol coverage rate, impact soil cover
Rate, gleisoil coverage rate, planosol coverage rate, podzolic soil coverage rate, sand dune coverage rate, rock outcrop soil coverage rate, water body (soil
In earth) coverage rate.
2) for each parameter of hydrological model, whole drainage characteristics information or the physical significance according to parameter can be chosen
Selected part watershed information carries out stepwise regression analysis, so that it is determined that the drainage characteristics information relevant to this parameter, sends out as analyzed
Drainage characteristics information predominantly basin mean sea level that evapotranspiration conversion factor K of existing Xinanjiang model is relevant, deeply take root in coating
Lid rate and shallow root vegetation coverage.
3) for the basin of all existing first-class Prediction version, drainage characteristics information database is set up, including:
Watershed information, including river, province, longitude and latitude, rainfall runoff characteristic description etc. residing for basin；
Watershed unit characteristic information, including mean sea level, stream gradient, river length, area, form factor etc.；
Soil types information after clustering processing, such as class soil (thin layer figure, Anthrosol, rhogosol coverage rate etc.), two classes
Soil etc.；
Vegetation pattern information after clustering processing, such as deep root vegetation coverage (green coniferous forest, evergreen broadleaf forest etc.), shallow root
Vegetation coverage；
The Hydro-Model Parameter Calibration Technology information that basin uses；
Step 2) obtain the landform relevant to each model parameter, soil, vegetation information.
4) basin without Streamflow Data to parameter to be determined, is first depending on longitude and latitude automatically from the Internet download digital elevation
Model data and vegetation, soil information, then use Law of DEM Data to carry out basin relevant information extraction, and to planting
Quilt, soil information cluster, and obtain the drainage characteristics information identical with aforementioned existing first-class Prediction version basin, such as described step
Rapid 2), in, drainage characteristics information predominantly basin mean sea level that evapotranspiration conversion factor K of Xinanjiang model is relevant, deeply take root in
Capped rate and shallow root vegetation coverage, then obtain the deep root vegetation coverage in parameter basin to be determined, shallow root vegetation coverage
Etc. information.
5) finding because of research, there is phase to a certain extent in drainage characteristics and rainfall runoff in the range of same large watershed
Like property, first in described step 3) the drainage characteristics information database set up is found with parameter to be determined without runoff money
Stream territory belongs to the sub basin of a large watershed, if the basin without Streamflow Data of parameter to be determined belongs to horse hair river, then exists
Drainage characteristics information bank is found all sub basin of its higher level river basins scope (Qingshui river basins).
6) for each parameter of hydrological model, it being first depending on described step 2) basin relevant to this parameter that determine be special
Reference ceases, in described step 5) in seek the basin without Streamflow Data of parameter to be determined in selected sub basin based on this parameter
Analogy basin, if analogy basin number meets certain requirements, it is determined that this sub basin is analogy basin；Otherwise in described large watershed
More upper level basin perimeter in seek, such as described step 5) higher level's Wushui River basin of Qingshuijiang, until meeting analogy basin
Requirement.Preferably, the present invention sets the number seeking analogy basin more than or equal to 5 for meeting number requirement.Wherein, phase is sought
It is the sub basin for higher level basin, parameter basin to be determined like the method in basin, uses it relevant to this Hydro-Model Parameter Calibration Technology
Drainage characteristics information clusters, and when the distance of cluster is less than a certain limit value, is analogy basin, because of different information cluster
Situation is different, therefore its limit value is different, mainly differentiates according to cluster spectrogram.
7) each parameter to be determined of pin hydrological model, in described step 6) in the analogy basin that determines, to this ginseng
The characteristic information that number is relevant carries out correlation analysis, sets up the regression equation of this parameter and drainage characteristics information, and obtains phase relation
Number, and determine this parameter.Wherein, regression equation is automatically to be selected from a large amount of alternative variablees by special algorithm software
Those variablees important to setting up regression equation, and automatically seek the regression equation that coefficient correlation is the highest.Regression equation is true
After Ding, the coefficient correlation of regression equation and each point can be calculated.If the evapotranspiration values of factor K of Xinanjiang model is at certain similar stream
The regression equation set up in the group of territory see table, and coefficient correlation is the highest under normal circumstances, and indices also meets requirement；When relevant
Achievement can not meet demand, typically takes coefficient correlation less than 0.8 for can not meet demand, then this parameter to be determined without runoff money
The Prediction version in stream territory should be demoted use, and in hydrologic forecast specification, the precision for Prediction version has carried out classification, and flood is pre-
Report scheme precision reaches two grade persons of first, second, can be used for issuing formal forecast；Scheme precision reaches third gradegrade C person, can be used for joining
The property examined is forecast；Person below the third gradegrade C, is only used for referential and estimates report, above-mentioned when coefficient correlation is less than 0.8, as former Prediction version is
The second grade, then reduce to the third gradegrade C.
Table 1 Xinanjiang model regression equation and index of correlation
8), after all parameter determinations to be determined, parameter can be substituted into flood forecast system, carry out this Cross Some Region Without Data
Flood forecasting.
Claims (5)
1. the Flood Forecasting Method without Streamflow Data basin, it is characterised in that: comprise the steps
1) Land_use change and soil characteristic information to all existing first-class Prediction version basins carry out clustering processing, described soil
Utilize and soil characteristic information is mainly various vegetation coverage and soil types coverage rate；
2) each parameter to hydrological model, chooses all or part of drainage characteristics information and carries out stepwise regression analysis, determine
The drainage characteristics information relevant to this parameter；
3) for the basin of all existing first-class Prediction version, drainage characteristics information database is set up；
4) basin without Streamflow Data to parameter to be determined, first according to longitude and latitude automatically from the Internet download digital elevation model
Data and vegetation, soil information, then use Law of DEM Data to carry out basin relevant information extraction, and to vegetation, soil
Earth information clusters, and obtains the drainage characteristics information identical with aforementioned existing first-class Prediction version basin；
5) in the drainage characteristics information database that described step 3) is set up, the basin without Streamflow Data with parameter to be determined is found
Belong to the sub basin of a large watershed；
6) for each parameter of hydrological model, it is first depending on described step 2) drainage characteristics relevant to this parameter that determine
Information, the basin without Streamflow Data seeking parameter to be determined in the sub basin selected in described step 5) is based on this parameter
Analogy basin, if analogy basin number meets more than or equal to 5, it is determined that this sub basin is final analogy basin；Otherwise in institute
Analogy basin is sought, until meeting number requirement in the upper level basin perimeter of the large watershed stating step 5)；Described seek similar
Basin refers to the sub basin for higher level basin, parameter basin to be determined, uses the basin that it is relevant to this Hydro-Model Parameter Calibration Technology special
Reference breath clusters, and when the distance of cluster is less than a certain limit value, is analogy basin；
7) each parameter to be determined to hydrological model, in the final analogy basin that described step 6) determines, to this
The characteristic information that parameter is relevant carries out correlation analysis, sets up the regression equation of this parameter and drainage characteristics information, obtains phase relation
Number, and determine this parameter；
8) after the parameter determination all to be determined of hydrological model, parameter can be brought into flood forecast system, carry out this without runoff
The flood forecasting in data basin.
The Flood Forecasting Method in a kind of basin without Streamflow Data the most according to claim 1, it is characterised in that: described soil
Utilizing cluster is deep root vegetation coverage and the big class of shallow root vegetation coverage two.
The Flood Forecasting Method in a kind of basin without Streamflow Data the most according to claim 1, it is characterised in that: described soil
Characteristic information cluster is two big classes, and wherein the first big class is divided into again two groups, is specifically categorized as: first big class the first group: thin
Layer soil coverage rate, Anthrosol's coverage rate, rhogosol coverage rate；First big class the second group: alfisol coverage rate, inceptisol cover
Rate, Alisol coverage rate, acrisol coverage rate；Second largest class: Lixisol coverage rate, impact soil cover
Rate, gleisoil coverage rate, planosol coverage rate, podzolic soil coverage rate, sand dune coverage rate, rock outcrop soil coverage rate, water body cover
Lid rate.
The Flood Forecasting Method in a kind of basin without Streamflow Data the most according to claim 1, it is characterised in that: described step
3) drainage characteristics information database includes watershed information, watershed unit characteristic information, the clustering processing that described step 1) obtains
After soil types information and vegetation pattern information after clustering processing, the Hydro-Model Parameter Calibration Technology information that basin uses, described step
Rapid 2) landform relevant to Hydro-Model Parameter Calibration Technology obtained, soil and vegetation information.
The Flood Forecasting Method in a kind of basin without Streamflow Data the most according to claim 1, it is characterised in that: described step
7) in, if coefficient correlation is less than 0.8, then the Prediction version degradation in the basin without Streamflow Data of this parameter to be determined uses.
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