CN116679357B - Method for carrying out water balance treatment on radar quantitative precipitation estimation - Google Patents
Method for carrying out water balance treatment on radar quantitative precipitation estimation Download PDFInfo
- Publication number
- CN116679357B CN116679357B CN202310659300.XA CN202310659300A CN116679357B CN 116679357 B CN116679357 B CN 116679357B CN 202310659300 A CN202310659300 A CN 202310659300A CN 116679357 B CN116679357 B CN 116679357B
- Authority
- CN
- China
- Prior art keywords
- basin
- rainfall
- point
- calculated
- qpe
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 38
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 32
- 238000001556 precipitation Methods 0.000 title claims abstract description 22
- 238000012937 correction Methods 0.000 claims abstract description 25
- 238000004364 calculation method Methods 0.000 claims description 41
- 238000012797 qualification Methods 0.000 claims description 10
- 238000012795 verification Methods 0.000 claims description 8
- 238000007689 inspection Methods 0.000 abstract description 3
- 238000005259 measurement Methods 0.000 abstract description 3
- 230000007547 defect Effects 0.000 abstract description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000002035 prolonged effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/14—Rainfall or precipitation gauges
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/40—Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Environmental Sciences (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Ecology (AREA)
- Biodiversity & Conservation Biology (AREA)
- Atmospheric Sciences (AREA)
- Computer Networks & Wireless Communication (AREA)
- Computational Mathematics (AREA)
- Algebra (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Electromagnetism (AREA)
- Pure & Applied Mathematics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Hydrology & Water Resources (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a method for carrying out water balance treatment on radar quantitative precipitation estimation, which comprises the steps of determining the center point of a calculated basin according to the longitude and latitude of the centroid point of a unit grid where each boundary point of the calculated basin is positioned; calculating the minimum radius of the river basin by taking the center point of the calculated river basin as the origin, and determining an initial river basin; determining the rainfall characteristic radius of the initial river basin; determining a target river basin according to the center point of the calculated river basin and larger values of the minimum radius of the river basin and the characteristic radius of the rainfall; calculating the average rainfall of the measured surface of the target river basin and the average rainfall of the QPE lattice points in the region to obtain the correction ratio of the average rainfall and the average rainfall of the measured surface of the target river basin; and calculating the corrected QPE sequence according to the QPE data and the correction ratio of all the grid points in the calculated watershed. The method solves the problems that the conventional radar precipitation estimation inspection and error correction are mainly aimed at radar precipitation estimation divided by single points or different grades, are not verified with actual measurement rainfall data, and have the defects of large calculated amount and unbalanced water quantity.
Description
Technical Field
The invention relates to the technical field of hydrologic forecasting combining meteorology and hydrology, in particular to a method for carrying out water balance treatment on radar quantitative precipitation estimation.
Background
The rainfall is an important link in the hydrologic cycle process, and the refined and high-density rainfall monitoring and forecasting play an important supporting role in mountain torrent geological disasters and medium and small river flood forecasting and early warning, and especially the reliable rainfall information is important in prolonging the flood forecasting period. The radar quantitative estimation (QPE) can provide precipitation products with continuous time, high horizontal resolution and wide coverage range, but the radar precipitation estimation (QPE) effect still needs to be improved, and the conventional radar precipitation estimation (QPE) inspection and error correction are mostly aimed at radar precipitation estimation (QPE) of single point or different grades, and are not verified with actual measurement rainfall data, so that the radar precipitation estimation (QPE) has the defects of large calculated amount and unbalanced water quantity.
Disclosure of Invention
In view of the above drawbacks, the present invention provides a method for performing water balance treatment on radar quantitative precipitation estimation, which aims to solve the problems of large calculation amount and unbalanced water amount caused by the fact that the conventional radar precipitation estimation (QPE) inspection and error correction are mostly aimed at radar precipitation estimation (QPE) of single point or different level division, and are not verified with actual measurement rainfall data.
To achieve the purpose, the invention adopts the following technical scheme:
A method for water balance treatment of radar quantitative precipitation estimation, comprising the steps of:
Step S1: based on the water collection area of the river or the target section, marking as a calculation basin Z 1, dividing the calculation basin Z 1 into unit grids with the size corresponding to the QPE grid point data, determining the longitude and latitude of the unit grid where each boundary point of the calculation basin Z 1 is positioned, and determining the center point of the calculation basin Z 1 according to the longitude and latitude of the centroid point of the unit grid where each boundary point of the calculation basin Z 1 is positioned;
step S2: calculating a minimum radius R 1 of the river basin taking the center point of the calculated river basin Z 1 as an origin, and determining an initial river basin Z 2;
Step S3: determining a rainfall characteristic radius R 2 of the initial basin Z 2;
Step S4: determining a target river basin Z 3 according to the center point of the calculated river basin Z 1 and larger values of the minimum radius R 1 and the characteristic radius R 2 of the rain amount of the river basin;
Step S5: calculating an actually measured surface average rainfall P 1 of a target river basin Z 3 and a QPE lattice point rainfall average P 2 in an area to obtain a correction ratio a of the actually measured surface average rainfall P 1 and the QPE lattice point rainfall average P 2;
Step S6: according to the QPE data of all grid points in the calculated watershed Z 1 and the correction ratio a, calculating to obtain a corrected QPE sequence;
step S7: and (3) establishing a flood forecast model, substituting the corrected QPE sequence as rainfall input into the flood forecast model, and carrying out flood forecast.
Preferably, in step S1, the center point of the basin Z 1 is determined according to the longitude and latitude of the centroid point of the unit mesh where each boundary point of the basin is located, and the calculation formula for calculating the center point of the basin Z 1 is as follows:
O((x1+x2+…+xn)/n,(y1+y2+…+yn)/n)
Wherein n represents the total number of boundary points of the river basin and is a positive integer; x n represents the abscissa value of the centroid point of the cell grid where the nth boundary point is located in the stream; y n represents the ordinate value of the centroid point of the cell grid in the stream where the nth boundary point is located.
Preferably, in step S2, the following substeps are specifically included:
Step S21: according to the longitude and latitude of the center point of the calculated basin Z 1, connecting the center point of the calculated basin Z 1 to each boundary point of the basin by a straight line, and calculating the distance from each boundary point of the basin to the center point of the calculated basin Z 1 Wherein j is the number of boundary points of the drainage basin; x o is the abscissa value of the center point of the calculated basin Z 1, and x j is the abscissa value of the j-th boundary point in the basin; y o is the ordinate value of the center point of the calculated basin Z 1; y j is the ordinate value of the jth boundary point in the basin;
Step S22: the maximum value of the distances from the boundary points of the river basin to the center point of the calculated river basin Z 1 is selected as the minimum radius R 1 of the river basin.
Preferably, in step S3, the following substeps are specifically included:
step S31: selecting all rainfall stations contained in an initial basin Z 2;
step S32: dividing all rainfall stations into two groups according to distribution conditions, wherein the two groups are respectively a calculation group and a verification group;
step S33: respectively calculating the surface average rainfall values of two groups of rainfall stations in different time periods by using a Thiessen polygon method, and recording the surface average rainfall values as P Calculation of i and P Verification i, wherein i represents the time period number;
Step S34: comparing the surface average rainfall values of two groups of rainfall stations in different time periods to generate an error;
step S35: judging whether the error is smaller than the relative error or the absolute error, if so, proving that the comparison result of the surface average rainfall values of the two groups of rainfall stations in the period is qualified, and obtaining the comparison qualification rate of the surface average rainfall values of the rainfall stations in the initial basin Z 2;
Step S36: and calculating the comparison qualification rate corresponding to the average rainfall value of the rainfall site surface of the initial drainage basin Z 2 under the condition of different radiuses, and taking the corresponding radius as the rainfall characteristic radius R 2 of the initial drainage basin Z 2 when the comparison qualification rate is larger than the set target value QR.
Preferably, in step S5, the measured surface average rainfall P 1 of the target basin Z 3 is calculated according to the taisen polygon method; and calculating a QPE lattice rainfall average value P 2 in the area according to the QPE algorithm program.
Preferably, in step S5, the calculation formula of the correction ratio a is as follows:
a＝P1/P2
Wherein a represents a correction ratio; p 1 represents the measured surface average rainfall of the target basin Z 3; p 2 represents the average of the QPE lattice rainfall in the area.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
According to the scheme, firstly, the rainfall characteristic radius of a river basin is verified and determined based on the rainfall site data of the river basin, then the correction ratio of the rainfall characteristic radius of the river basin and the average rainfall value of QPE lattice points in the region is determined according to the measured surface average rainfall value of the region, the QPE value of the river basin is further calculated by amplifying or shrinking the same ratio, the corrected QPE sequence is obtained, and finally, the corrected QPE sequence is substituted into a flood forecast model as rainfall forecast input to calculate the flood process of a target section of the river basin. According to the scheme, the grid point rainfall distribution distinction of radar quantitative rainfall estimation and the total water balance of actual rainfall are fully considered, meanwhile, grid distinction of meteorological QPE values is utilized, the problem of unclear drainage basin rainfall distribution data caused by insufficient density of the arranged rainfall stations is solved, the problem of short prediction period of the existing drainage basins, especially small and medium river drainage basins, caused by short converging time is solved, the prediction precision of a flood process is improved, the flood prediction period is prolonged, and if the distributed unit line model is combined, random point prediction can be realized, so that the method has the advantages of wide application range and high fitting precision.
Drawings
FIG. 1 is a flow chart of method steps for performing a water balance process on a radar quantitative precipitation estimate.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
A method for water balance treatment of radar quantitative precipitation estimation, comprising the steps of:
Step S1: based on the water collection area of the river or the target section, marking as a calculation basin Z 1, dividing the calculation basin Z 1 into unit grids with the size corresponding to the QPE grid point data, determining the longitude and latitude of the unit grid where each boundary point of the calculation basin Z 1 is positioned, and determining the center point of the calculation basin Z 1 according to the longitude and latitude of the centroid point of the unit grid where each boundary point of the calculation basin Z 1 is positioned;
step S2: calculating a minimum radius R 1 of the river basin taking the center point of the calculated river basin Z 1 as an origin, and determining an initial river basin Z 2;
Step S3: determining a rainfall characteristic radius R 2 of the initial basin Z 2;
Step S4: determining a target river basin Z 3 according to the center point of the calculated river basin Z 1 and larger values of the minimum radius R 1 and the characteristic radius R 2 of the rain amount of the river basin;
Step S5: calculating an actually measured surface average rainfall P 1 of a target river basin Z 3 and a QPE lattice point rainfall average P 2 in an area to obtain a correction ratio a of the actually measured surface average rainfall P 1 and the QPE lattice point rainfall average P 2;
Step S6: according to the QPE data of all grid points in the calculated watershed Z 1 and the correction ratio a, calculating to obtain a corrected QPE sequence;
step S7: and (3) establishing a flood forecast model, substituting the corrected QPE sequence as rainfall input into the flood forecast model, and carrying out flood forecast.
In the method for carrying out water balance treatment on radar quantitative precipitation estimation, as shown in fig. 1, the first step is to record the water collection area of a river or a target section as a calculation basin Z 1, divide the calculation basin Z 1 into unit grids with the size corresponding to QPE grid point data, determine the longitude and latitude of the unit grid where each boundary point of the calculation basin Z 1 is located, determine the center point of the calculation basin Z 1 according to the longitude and latitude of the unit grid where each boundary point of the calculation basin Z 1, in one embodiment, divide the calculation basin Z 1 into a plurality of square grids with the area of 1km 2, and in the process of determining the longitude and latitude of the unit grid where each boundary point of the basin is located, when the area of the unit grid where a certain boundary point of the basin is located is less than 1km 2, the scheme can calculate the longitude and latitude of the unit grid according to the area of the unit grid where the boundary point is 1km 2, and the calculation of the longitude and latitude of the unit grid is specifically expressed by the longitude and latitude of the centroid point of the unit grid where the centroid point of the unit is the intersection point of the unit grid. Further, according to the longitude and latitude of the centroid point of the unit grid where each boundary point of the drainage basin is located, the center point of the drainage basin Z 1 is determined and calculated according to the analysis geometry method. The second step is to calculate the minimum radius R 1 of the basin with the center point of the calculated basin Z 1 as the origin, and determine the initial basin Z 2, specifically, draw a circle with the center point of the calculated basin Z 1 as the origin and the minimum radius R 1 of the basin as the radius, and the circle area is the initial basin Z 2. The third step is to determine the rain characteristic radius R 2 of the initial basin Z 2, specifically the rain characteristic radius R 2, which facilitates subsequent comparisons with the basin minimum radius R 1. The fourth step is to determine the target river basin Z 3 according to the center point of the calculated river basin Z 1 and the larger values of the minimum radius R 1 and the characteristic radius R 2 of the rain amount, specifically, to select the larger values of the minimum radius R 1 and the characteristic radius R 2 of the rain amount of the river basin as the radius to draw a circle by taking the center point of the calculated river basin Z 1 as the center of the circle, and the circle area is the target river basin Z 3. By calculating the minimum radius R 1 of the river basin and the characteristic radius R 2 of the rainfall, and selecting the larger value of the minimum radius R 1 and the characteristic radius R 2 as the radius, the area of the target river basin Z 3 is guaranteed to be large enough, and the rainfall true value is obtained. The fifth step is to calculate the measured average rainfall P 1 of the target river basin Z 3 and the average rainfall P 2 of the QPE grid points in the region to obtain the correction ratio a of the measured average rainfall P 1 and the average rainfall P 2 of the QPE grid points in the region, and specifically, the calculation of the correction ratio a can enable the QPE grid points to reach the maximum water balance. The sixth step is to calculate the corrected QPE sequence according to the QPE data and the correction ratio a of all the grid points in the calculation basin Z 1, specifically, multiply the QPE data of all the grid points in the calculation basin Z 1 by the correction ratio a to obtain the corrected QPE sequence, so that the QPE grid points reach the water balance. And the seventh step is to establish a flood forecast model, substitute the corrected QPE sequence as rainfall input into the flood forecast model to forecast the flood, so that the rainfall spatial distribution situation can be described more accurately, and the flood simulation precision is improved.
According to the scheme, firstly, the rainfall characteristic radius of a river basin is verified and determined based on the rainfall site data of the river basin, then the correction ratio of the rainfall characteristic radius of the river basin and the average rainfall value of QPE lattice points in the region is determined according to the measured surface average rainfall value of the region, the QPE value of the river basin is further calculated by amplifying or shrinking the same ratio, the corrected QPE sequence is obtained, and finally, the corrected QPE sequence is substituted into a flood forecast model as rainfall forecast input to calculate the flood process of a target section of the river basin. According to the scheme, the grid point rainfall distribution distinction of radar quantitative rainfall estimation and the total water balance of actual rainfall are fully considered, meanwhile, grid distinction of meteorological QPE values is utilized, the problem of unclear drainage basin rainfall distribution data caused by insufficient density of the arranged rainfall stations is solved, the problem of short prediction period of the existing drainage basins, especially small and medium river drainage basins, caused by short converging time is solved, the prediction precision of a flood process is improved, the flood prediction period is prolonged, and if the distributed unit line model is combined, random point prediction can be realized, so that the method has the advantages of wide application range and high fitting precision.
Preferably, in step S1, the center point of the basin Z 1 is determined according to the longitude and latitude of the centroid point of the unit mesh where each boundary point of the basin is located, and the calculation formula for calculating the center point of the basin Z 1 is as follows:
O((x1+x2+…+xn)/n,(y1+y2+…+yn)/n)
Wherein n represents the total number of boundary points of the river basin and is a positive integer; x n represents the abscissa value of the centroid point of the cell grid where the nth boundary point is located in the stream; y n represents the ordinate value of the centroid point of the cell grid in the stream where the nth boundary point is located.
In this embodiment, according to the longitude and latitude of the centroid point of the unit grid where each boundary point of the drainage basin is located as G1(x1,y1)、G2(x2,y2)、…Gn(xn,yn),, the longitude and latitude of the center point of the calculation drainage basin Z 1 is determined as O ((x 1+x2+…+xn)/n,(y1+y2+…+yn)/n) according to the analytical geometry method.
Preferably, in step S2, the method specifically comprises the following substeps:
Step S21: according to the longitude and latitude of the center point of the calculated basin Z 1, connecting the center point of the calculated basin Z 1 to each boundary point of the basin by a straight line, and calculating the distance from each boundary point of the basin to the center point of the calculated basin Z 1 Wherein j is the number of boundary points of the drainage basin; x o is the abscissa value of the center point of the calculated basin Z 1, and x j is the abscissa value of the j-th boundary point in the basin; y o is the ordinate value of the center point of the calculated basin Z 1; y j is the ordinate value of the jth boundary point in the basin;
Step S22: the maximum value of the distances from the boundary points of the river basin to the center point of the calculated river basin Z 1 is selected as the minimum radius R 1 of the river basin.
In this embodiment, by selecting the maximum value of the distances from the boundary points of the basin to the center point of the calculated basin Z 1 as the minimum radius R 1 of the basin, the calculated initial basin Z 2 can completely cover the calculated basin Z 1, that is, the calculated basin Z 1 must be a part of the initial basin Z 2, which is beneficial to the subsequent verification of the water balance problem of the calculated basin Z 1.
Preferably, in step S3, the method specifically comprises the following substeps:
step S31: selecting all rainfall stations contained in an initial basin Z 2;
step S32: dividing all rainfall stations into two groups according to distribution conditions, wherein the two groups are respectively a calculation group and a verification group;
step S33: respectively calculating the surface average rainfall values of two groups of rainfall stations in different time periods by using a Thiessen polygon method, and recording the surface average rainfall values as P Calculation of i and P Verification i, wherein i represents the time period number;
Step S34: comparing the surface average rainfall values of two groups of rainfall stations in different time periods to generate an error;
step S35: judging whether the error is smaller than the relative error or the absolute error, if so, proving that the comparison result of the surface average rainfall values of the two groups of rainfall stations in the period is qualified, and obtaining the comparison qualification rate of the surface average rainfall values of the rainfall stations in the initial basin Z 2;
Step S36: and calculating the comparison qualification rate corresponding to the average rainfall value of the rainfall site surface of the initial drainage basin Z 2 under the condition of different radiuses, and taking the corresponding radius as the rainfall characteristic radius R 2 of the initial drainage basin Z 2 when the comparison qualification rate is larger than the set target value QR.
In this embodiment, the initial basin Z 2 has a plurality of rainfall stations, and these rainfall stations are divided into two groups according to the distribution condition, one group is considered as a calculation group, and the other group is considered as a verification group, so that the two selected groups of rainfall stations are ensured to be distributed as discretely and uniformly as possible and can represent the rainfall value on the whole initial basin Z 2 surface. In the scheme, the Thiessen polygon method is used for respectively calculating the surface average rainfall values of two groups of rainfall stations in different time periods, is a method for calculating the average rainfall according to the rainfall of the weather stations in discrete distribution, and is an existing hydrologic calculation method.
Further, the physical meaning of the rainfall characteristic radius is that when the radius of any basin is larger than the rainfall characteristic radius, the measured surface average rainfall value in the basin is compared with the actually generated rainfall value through a grouping error, so that the error between the measured surface average rainfall value and the actually generated rainfall value is considered to be smaller than the relative error or the absolute error, and the water quantity in the basin is balanced as a whole.
Further, comparing the surface average rainfall values of two groups of rainfall stations in different time periods, when the error is smaller than the relative error m or the absolute error n, proving that the comparison result of the surface average rainfall values of the two groups of rainfall stations in the time period is qualified, and obtaining the comparison qualification rate of the surface average rainfall values of the rainfall stations in the initial basin Z 2, specifically, the relative error m and the absolute error n can be obtained according to the forecasting accuracy requirement values, taking a flood peak forecasting permission error as an example, when rainfall runoffs are forecasted to take 20% of measured flood peak flow as flow permission errors, and river flow is forecasted to take 20% of measured amplitude as water level permission errors in the forecasting period, wherein the relative error m is 20%. When the flow allowable error is smaller than 5% of the actually measured flow value, taking 5% of the actually measured flow value as the flow allowable error, and when the water level allowable error is smaller than the water level amplitude value corresponding to 5% of the actually measured flood peak flow or smaller than 0.10m, taking 5% of the actually measured flood peak flow as the water level allowable error, wherein the absolute error n is 5%.
Preferably, in step S5, the measured surface average rainfall P 1 of the target basin Z 3 is calculated according to the thasen polygon method; and calculating a QPE lattice rainfall average value P 2 in the area according to the QPE algorithm program.
In this embodiment, the QPE algorithm program is an existing algorithm program, and can estimate the average rainfall. The measured surface average rainfall P 1 of the target river basin Z 3 and the average rainfall P 2 of the QPE lattice points in the region are calculated, so that the correction ratio of the measured surface average rainfall P 1 and the average rainfall P 2 of the QPE lattice points in the region can be obtained, and the QPE lattice points can be further balanced in water quantity.
Preferably, in step S5, the calculation formula of the correction ratio a is as follows:
a＝P1/P2
Wherein a represents a correction ratio; p 1 represents the measured surface average rainfall of the target basin Z 3; p 2 represents the average of the QPE lattice rainfall in the area.
In this embodiment, by calculating the correction ratio of the average rainfall on the measured surface of the target river basin Z 3 and the average rainfall on the QPE lattice points in the region, the QPE lattice points can reach the water balance to the maximum extent.
Furthermore, functional units in various embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations of the above embodiments may be made by those skilled in the art within the scope of the invention.
Claims (4)
1. A method for performing water balance treatment on radar quantitative precipitation estimation, characterized by: the method comprises the following steps:
Step S1: based on the water collection area of the river or the target section, marking as a calculation basin Z 1, dividing the calculation basin Z 1 into unit grids with the size corresponding to the QPE grid point data, determining the longitude and latitude of the unit grid where each boundary point of the calculation basin Z 1 is positioned, and determining the center point of the calculation basin Z 1 according to the longitude and latitude of the centroid point of the unit grid where each boundary point of the calculation basin Z 1 is positioned;
step S2: calculating a minimum radius R 1 of the river basin taking the center point of the calculated river basin Z 1 as an origin, and determining an initial river basin Z 2;
Step S3: determining a rainfall characteristic radius R 2 of the initial basin Z 2;
Step S4: determining a target river basin Z 3 according to the center point of the calculated river basin Z 1 and larger values of the minimum radius R 1 and the characteristic radius R 2 of the rain amount of the river basin;
Step S5: calculating an actually measured surface average rainfall P 1 of a target river basin Z 3 and a QPE lattice point rainfall average P 2 in an area to obtain a correction ratio a of the actually measured surface average rainfall P 1 and the QPE lattice point rainfall average P 2;
Step S6: according to the QPE data of all grid points in the calculated watershed Z 1 and the correction ratio a, calculating to obtain a corrected QPE sequence;
Step S7: establishing a flood forecast model, substituting the corrected QPE sequence as rainfall input into the flood forecast model, and forecasting the flood;
in step S2, the method specifically includes the following substeps:
Step S21: according to the longitude and latitude of the center point of the calculated basin Z 1, connecting the center point of the calculated basin Z 1 to each boundary point of the basin by a straight line, and calculating the distance from each boundary point of the basin to the center point of the calculated basin Z 1 Wherein j is the number of boundary points of the drainage basin; x o is the abscissa value of the center point of the calculated basin Z 1, and x j is the abscissa value of the j-th boundary point in the basin; y o is the ordinate value of the center point of the calculated basin Z 1; y j is the ordinate value of the jth boundary point in the basin;
Step S22: selecting the maximum value in the distance from each boundary point of the river basin to the central point of the calculated river basin Z 1 as the minimum radius R 1 of the river basin;
In step S3, the method specifically includes the following substeps:
step S31: selecting all rainfall stations contained in an initial basin Z 2;
step S32: dividing all rainfall stations into two groups according to distribution conditions, wherein the two groups are respectively a calculation group and a verification group;
step S33: respectively calculating the surface average rainfall values of two groups of rainfall stations in different time periods by using a Thiessen polygon method, and recording the surface average rainfall values as P Calculation of i and P Verification i, wherein i represents the time period number;
Step S34: comparing the surface average rainfall values of two groups of rainfall stations in different time periods to generate an error;
step S35: judging whether the error is smaller than the relative error or the absolute error, if so, proving that the comparison result of the surface average rainfall values of the two groups of rainfall stations in the period is qualified, and obtaining the comparison qualification rate of the surface average rainfall values of the rainfall stations in the initial basin Z 2;
Step S36: and calculating the comparison qualification rate corresponding to the average rainfall value of the rainfall site surface of the initial drainage basin Z 2 under the condition of different radiuses, and taking the corresponding radius as the rainfall characteristic radius R 2 of the initial drainage basin Z 2 when the comparison qualification rate is larger than the set target value QR.
2. A method of water balancing radar quantitative precipitation estimation according to claim 1, wherein: in step S1, the center point of the basin Z 1 is determined and calculated according to the longitude and latitude of the centroid point of the unit grid where each boundary point of the basin is located, and the calculation formula for calculating the center point of the basin Z 1 is as follows:
O((x1+x2+…+xn)/n,(y1+y2+…+yn)/n)
Wherein n represents the total number of boundary points of the river basin and is a positive integer; x n represents the abscissa value of the centroid point of the cell grid where the nth boundary point is located in the stream; y n represents the ordinate value of the centroid point of the cell grid in the stream where the nth boundary point is located.
3. A method of water balancing radar quantitative precipitation estimation according to claim 1, wherein: in step S5, the measured surface average rainfall P 1 of the target basin Z 3 is calculated according to the tesen polygon method; and calculating a QPE lattice rainfall average value P 2 in the area according to the QPE algorithm program.
4. A method of water balancing radar quantitative precipitation estimation according to claim 1, wherein: in step S5, the calculation formula of the correction ratio a is as follows:
a＝P1/P2
Wherein a represents a correction ratio; p 1 represents the measured surface average rainfall of the target basin Z 3; p 2 represents the average of the QPE lattice rainfall in the area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310659300.XA CN116679357B (en) | 2023-06-05 | 2023-06-05 | Method for carrying out water balance treatment on radar quantitative precipitation estimation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310659300.XA CN116679357B (en) | 2023-06-05 | 2023-06-05 | Method for carrying out water balance treatment on radar quantitative precipitation estimation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116679357A CN116679357A (en) | 2023-09-01 |
| CN116679357B true CN116679357B (en) | 2024-04-19 |
Family
ID=87788536
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310659300.XA Active CN116679357B (en) | 2023-06-05 | 2023-06-05 | Method for carrying out water balance treatment on radar quantitative precipitation estimation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116679357B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102289570A (en) * | 2011-07-23 | 2011-12-21 | 浙江大学 | Flood forecast method based on rainfall-runoff-flood routing calculation |
| CN112070286A (en) * | 2020-08-25 | 2020-12-11 | 贵州黔源电力股份有限公司 | Rainfall forecast early warning system for complex terrain watershed |
| CN113128067A (en) * | 2021-05-06 | 2021-07-16 | 大连理工大学 | Distributed time-varying landform unit line-based hilly area small watershed flood forecasting method |
| CN113281754A (en) * | 2021-07-26 | 2021-08-20 | 中国水利水电科学研究院 | WRF-Hydro key parameter calibration method for quantitatively estimating rainfall by integrating rainfall station with radar |
| CN113742910A (en) * | 2021-08-26 | 2021-12-03 | 北京七兆科技有限公司 | Reservoir water inflow early warning and forecasting method and system based on flood forecasting of medium and small watershed |
-
2023
- 2023-06-05 CN CN202310659300.XA patent/CN116679357B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102289570A (en) * | 2011-07-23 | 2011-12-21 | 浙江大学 | Flood forecast method based on rainfall-runoff-flood routing calculation |
| CN112070286A (en) * | 2020-08-25 | 2020-12-11 | 贵州黔源电力股份有限公司 | Rainfall forecast early warning system for complex terrain watershed |
| CN113128067A (en) * | 2021-05-06 | 2021-07-16 | 大连理工大学 | Distributed time-varying landform unit line-based hilly area small watershed flood forecasting method |
| CN113281754A (en) * | 2021-07-26 | 2021-08-20 | 中国水利水电科学研究院 | WRF-Hydro key parameter calibration method for quantitatively estimating rainfall by integrating rainfall station with radar |
| CN113742910A (en) * | 2021-08-26 | 2021-12-03 | 北京七兆科技有限公司 | Reservoir water inflow early warning and forecasting method and system based on flood forecasting of medium and small watershed |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116679357A (en) | 2023-09-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111582755B (en) | Mountain torrent disaster comprehensive risk dynamic assessment method based on multi-dimensional set information | |
| Chen et al. | Impacts of weighting climate models for hydro-meteorological climate change studies | |
| CN107730151B (en) | Basin design flood calculation method based on conceptual hydrological model | |
| Noto et al. | Use of L-moments approach for regional flood frequency analysis in Sicily, Italy | |
| CN110598290B (en) | Method and system for predicting future hydropower generation capacity of basin considering climate change | |
| CN113887972A (en) | Comprehensive drought monitoring and evaluating method based on hydrological process | |
| CN110134907B (en) | Rainfall missing data filling method and system and electronic equipment | |
| Ravazzani et al. | Review of time-of-concentration equations and a new proposal in Italy | |
| CN116910041B (en) | Daily correction method for remote sensing precipitation product based on scale analysis | |
| CN113281754A (en) | WRF-Hydro key parameter calibration method for quantitatively estimating rainfall by integrating rainfall station with radar | |
| CN110515139B (en) | Multi-scale terrain representative quantitative analysis system and method for meteorological hydrological station | |
| CN117436619B (en) | Cascade reservoir flood control reservoir capacity combined reservation method based on equivalent flood control effect | |
| CN106546958B (en) | A kind of radar data assimilation method of optimization | |
| CN116679357B (en) | Method for carrying out water balance treatment on radar quantitative precipitation estimation | |
| CN117787081A (en) | Hydrological model parameter uncertainty analysis method based on Morris and Sobol methods | |
| CN109948175B (en) | Satellite remote sensing albedo missing value inversion method based on meteorological data | |
| CN112084643A (en) | Drainage basin extraction method based on digital elevation and soil parameters | |
| CN109919362B (en) | Medium-and-long-term runoff forecasting method considering hydraulic engineering scheduling influence | |
| CN116523189A (en) | Soil moisture content site planning method, device and storage medium considering hydrologic characteristics | |
| CN113361114B (en) | Multi-scale non-point source pollutant river entering coefficient measuring and calculating method based on runoff path | |
| CN115453664A (en) | Rainfall runoff forecasting method suitable for data-free areas | |
| CN109408604B (en) | Grid processing method, device and system for data of weather factors associated with power transmission line | |
| CN110751398A (en) | Regional ecological quality evaluation method and device | |
| CN116167655B (en) | Method, system and medium for evaluating power generation capacity based on radar short-term supplementary wind measurement | |
| Warusavitharana et al. | Evaluating the potential of an open sensor network to support reservoir pre-release decision making. |
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 |