CN111104746B - River flood beach elevation determination method based on wavelet analysis - Google Patents
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Abstract
The invention discloses a river flood plain elevation based on wavelet analysisA method of determination, the method employingS‑KAnd (4) obtaining the vertical flow velocity distribution of the river cross section through model simulation, and calculating the kinetic energy correction coefficients under different water levels. And (4) performing discrete wavelet decomposition on the water level-kinetic energy correction coefficient function to obtain coefficient absolute values of the high-frequency signal layer and each corresponding layer. And analyzing the absolute value of the coefficient of the highest frequency layer, determining the position of the kinetic energy correction coefficient where mutation occurs, and determining the elevation of the flood plain through comprehensive analysis. The method overcomes the defect of manually judging the beach groove boundary point in the traditional method in the implementation process, has weak subjectivity, is proved by tests to have accurate calculation result and strong operability, and provides a more accurate mode for acquiring the flood beach elevation of the compound cross section river channel.
Description
Technical Field
The invention relates to a river flood beach elevation determination method based on wavelet analysis, in particular to a method for determining river flood beach elevation by dividing a river flood beach and a main trough under the condition of mutation based on a kinetic energy correction coefficient of a compound section river channel, and belongs to the technical field of beach trough division in river bed evolution analysis.
Background
The river flood beach elevation refers to the elevation of the water level of the river course when the river flood beach is level with the river flood beach. In northern China, a sediment-rich river has a section form which is a compound section with a beach and a main trough. The analysis of the measured data shows that the water flow bed making capacity is strong when the water level of the beach is flat, and the water flow is dispersed when the water flow is larger and overflows the side beach, so that the bed making effect is reduced. With the rapid development of economy, in order to better utilize river beach resources and water resources, it is necessary to clearly demarcate the groove beach boundaries, and river beach elevation is an important parameter in the research of demarcating the groove beach boundaries, and has a very important role in determining the beach water level and the beach flow.
At present, the methods for determining the elevation of the flood plain mainly include the following two methods: one is to use certain geometric criteria for estimation based on the cross-sectional morphology of the bed. For example, the flow-water level relation before and after the flood beach in the measured data is used for determining the elevation of the flood beach. Because the water level change amplitude is obviously different when the unit flow is increased before and after the flood beach, the beach elevation can be determined by searching the position where the slope changes. However, in the actual river channel, the shape change of the river bed is large, and if the upper part of the main channel of the river is in a gradually enlarged shape, a natural dike with a certain gradient also exists outside the main channel, so that the flow-water level relation found by using the method is relatively inaccurate. Yet another is to use a mathematical model to solve. For the river with much sediment in northern China, particularly for the river with the yellow river, which has the section type, the composite section river channel consists of the main channel and the flood plain, and the numerical difference of the hydraulic elements of the river channel and the flood plain in the composite section is large, so a two-dimensional mathematical model is usually adopted for calculation and solution. However, the premise of solving the mathematical model is to divide the beach groove, namely drawing a river channel section topographic map through field exploration, and then manually dividing the beach groove according to the landform characteristics, wherein the landform characteristics comprise the tail of a beach, the abrupt change point of a bank slope and the change of a bank plant, but the method has no specific standard, has certain manual property in the dividing process and has strong subjectivity. Resulting in a large deviation of the beach groove boundary from the engineering expectation during actual operation. In addition, the method needs more parameters, and when the current rear section parameter is changed, manual dividing and other operations need to be carried out, so that the workload is large.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the river flood beach elevation determination method based on wavelet analysis is simple to operate, weak in subjectivity and high in precision.
The invention adopts the following technical scheme for solving the technical problems:
a method for determining the elevation of a flood plain based on wavelet analysis comprises the following steps:
step 1, collecting digital topographic data of a river reach, selecting a river cross section, and sequentially arranging measuring points from left to right along the river cross section, wherein the starting point distance of each measuring point is D i Corresponding elevation is z bi I is 1, …, n, n represents the number of stations, andD 1 the width between the i-th and the i + 1-th measuring points is B i ，i＝1,…,n-1；
step 3, setting the lowest calculation water level L of the selected river cross section min And the highest calculated water level L max The distance from the lowest calculated water level to the highest calculated water level is divided into 80 levels in the vertical direction, and the water level of each level is recorded as L j ，
j＝1,2,…,80，L 80 ＝L max ；
Step 5, calculating to obtain each level of water level L according to the topographic data in the step 1 j The lower flow cross-sectional area is A j Dividing the flow by the corresponding flow cross-section area to obtain the average flow velocity v of the flow cross-section j Finally, calculating the water level L of each stage j Coefficient of kinetic energy correction of alpha j ；
Step 6, according to the water level sequence of 1 to 80 levels, using the water level L j Correcting the coefficient alpha for independent variable and kinetic energy j For dependent variables, a relational table is formed corresponding to the functional relationships, which are denoted as alpha j (L j )；
Step 7, for the function alpha in step 6 j (L j ) Discrete wavelet transform is carried out by adopting db6 wavelet to obtain transformed function space W m And outputs a function alpha j (L j ) After discrete wavelet transform, in function space W m Obtaining a relation graph of the lower coefficient, the number of high-frequency signal layers and the water level so as to obtain the absolute value of the coefficient corresponding to each high-frequency signal layer;
step 8, setting the water level L of each stage j The absolute value of the coefficient of the corresponding highest frequency signal is recorded into the relation table in step 6, and all the highest frequency signals in the table are recordedAnd sorting the coefficient absolute values of the frequency signals from large to small, taking the coefficient absolute value corresponding to the 8 th% sorted position as a threshold, and taking the water level elevation corresponding to the coefficient absolute value before the 8 th% sorted position as the first-stage flood plain elevation in the multi-stage flood plain of the river channel section.
As a preferred embodiment of the present invention, the expression of the S-K model in step 4 is:
wherein g is the acceleration of gravity, h ji Is the water level L j Depth of water, s, at ith measuring point of lower river section 0 Is the riverbed slope, z bi Is the elevation of the ith measuring point of the river cross section, c is the roughness of the river, u ij Is the water level L j The average flow velocity of the vertical line of the ith measuring point is lower, lambda is a dimensionless diffusion coefficient, and y represents the transverse direction of the section.
As a preferred embodiment of the present invention, the overflow Q in step 4 j The calculation formula of (2) is as follows:
wherein u is ij Is the water level L j Average flow velocity of vertical line of the lower ith measuring point, h ji Is the water level L j Depth of water at ith measuring point of lower river section, B i The width from the ith measuring point to the (i + 1) th measuring point.
In a preferred embodiment of the present invention, the kinetic energy correction factor α in step 5 j The calculation formula of (c) is:
wherein u is ij Is the water level L j Average flow velocity of vertical line of the ith measuring point, h ji Is the water level L j Depth of water at ith measuring point of lower river section, B i Is the width from the ith measuring point to the (i + 1) th measuring point, v j Is the water level L j The average flow velocity of the lower flow cross section,
Q j is the water level L j Lower flow rate, A j Is the water level L j The area of the lower flow cross section,
compared with the prior art, the technical scheme adopted by the invention has the following technical effects:
the invention uses the kinetic energy correction coefficient as an index, quantitatively distinguishes the main trough and the flood plain of the compound section, and has weak subjectivity; the technical method of discrete wavelet transform is applied, the physical concept is clear, the calculation result is accurate, and the operability is strong. Therefore, the method for calculating the elevation of the flood plain is feasible, simple to operate and accurate in result.
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Fig. 1 is a flowchart of a method for determining elevation of flood plain based on wavelet analysis according to the present invention.
FIG. 2 is a cross-sectional view of a river hydrology and measurement point according to an embodiment of the present invention.
FIG. 3 is a diagram showing the distribution of absolute values of the water level-kinetic energy correction coefficient function after discrete wavelet transform according to the embodiment of the present invention.
FIG. 4 shows d after wavelet transform according to an embodiment of the present invention 1 Layer transform coefficient value-water level relationship line graph.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, a method for determining elevation of flood plain based on wavelet analysis includes the following specific steps:
step 1, collecting digital topographic data of river reach and arranging measuring pointsThe measuring points are marked as D from left to right in turn i (i-1, 2, …, n) with corresponding elevation z bi (i-1, 2, …, n) wherein D 1 When it is 0, note D i To D i+1 The width between two measuring points is B i (i＝1，2，…，n-1)；
step 3, setting the lowest calculated water level L of the section of the river reach min And the highest calculated water level L max Given 80 sets of calculated levels of water
(wherein j ═ 1, 2, …, 80), wherein L 80 ＝L max ；
The expression of the S-K model is:
wherein g is the acceleration of gravity (unit: m/s) 2 )；h ji Is the water level L j The water depth (unit: m) of a lower river section measuring point; s 0 For riverbed slope, 0.00005 can be selected; c is the roughness of the river channel, and can be 0.025; u. of ji The average flow velocity (unit: m/s) of the vertical line of the measuring point; λ is dimensionless diffusion coefficient, and can be 0.001, z bi For local bed elevation (step 1 measured), y represents the cross-section in the cross-section, corresponding to the starting point distance in step 1. The equation can be solved discretely by a characteristic difference method.
River cross-section overflow Q j The calculation formula of (2) is as follows:
wherein u is ji Is the water level L j Average flow velocity (unit: m/s) of vertical line of ith measuring point of lower river cross section, h ji Is the water level L j Depth of water (unit: m) at ith measuring point of lower river section, B i Is D i To D i+1 The width (unit: m) between two measuring points, n is the number of measuring points of the section, and the value range of j is 1-80.
Step 5, calculating to obtain each given water level L according to the topographic data in the step 1 j The lower flow cross-sectional area is A j Dividing the flow by the corresponding flow cross-section area to calculate the average flow velocity v of the flow cross-section j Finally, calculating the water level L of each stage j Coefficient of kinetic energy correction of alpha j ；
The formula of the kinetic energy correction coefficient is as follows:
wherein u is ji 、h ji The meaning of (a) is the same as that described above, v j Is a given water level L j The lower section average flow velocity (unit: m/s) is calculated by the formula
A j For a given water level L j Lower flow cross-sectional area (unit: m) 2 ) The calculation formula is
Step 6, using water level L j Correcting the coefficient alpha for independent variable and kinetic energy j For dependent variables, a relational table is formed corresponding to the functional relationships, which are denoted as alpha j (L j )；
Step 7, for the function alpha in step 6 j Discrete wavelet transform is carried out by adopting db6 wavelet to obtain transformed function space W m The output primitive function is subjected to discrete wavelet transform and then is in function space W m Coefficient of-a number of layers-water level relation graph, and absolute values of coefficients under corresponding time layers;
step 8, the resulting highest frequency layer (d) 1 ) Coefficient absolute value of (2) corresponds to the independent variable (water level L) j ) Recording the highest frequency layer (d) in the relation table in step 6 1 ) The absolute values of the coefficients of the signals are arranged from large to small, the value corresponding to the 8 th percent coefficient value is taken as a threshold value, and the corresponding independent variable (water level L) larger than the threshold value row is recorded j )；
Step 9, the water level L obtained in step 8 j The corresponding water level elevation is the first-level river flood beach elevation in the river channel section multi-level river flood beach.
Taking the section of the high village downstream of the yellow river as an example, the method for determining the elevation of the flood plain based on the wavelet analysis, provided by the invention, has the following specific implementation steps:
(1) the starting point distance, the elevation data and the hydrological data of the high village section are collected, each measuring point is numbered, and a section diagram is obtained and is shown in figure 2.
(2) Finding the lowest calculated water level L of the section min 101.32m and the highest calculated water level L max 112.92m, between them, 80 height points are selected as the calculated water level and filled in table 1.
(3) And calculating the kinetic energy correction coefficient alpha under different water levels according to the steps, and correspondingly filling the coefficient alpha into the table 1.
(4) The data of table 1 is subjected to a discrete wavelet decomposition as shown in fig. 3. Outputting the highest frequency signal layer (d) 1 ) The absolute values of the coefficients of (a) are filled in table 1.
(5) The highest frequency signal layer (d) 1 ) The absolute values of the coefficients are arranged from large to small, the line 8% of the front coefficient value is taken, and the corresponding water level L is recorded j . In this example, the 8 th% of the discrete wavelet coefficient is the threshold, and the water level L corresponding to the first 8% of the coefficient value j 105.11, 107.59, 109.05, respectively, as shown in FIG. 4.
(6) The cross section has 3 grades of river floodbeaches, and the elevation of the river floodbeaches is respectively from low to high: 105.11m, 107.59m and 109.05 m.
TABLE 1
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical solution according to the technical idea of the present invention fall within the protection scope of the present invention.
Claims (3)
1. A river flood beach elevation determination method based on wavelet analysis is characterized by comprising the following steps:
step 1, collecting digital topographic data of a river reach, selecting a river cross section, and sequentially arranging measuring points from left to right along the river cross section, wherein the starting point distance of each measuring point is D i Corresponding elevation z bi I is 1, …, n, n represents the number of stations, and D 1 The width between the i-th and the i + 1-th measuring points is B i ，i＝1,…,n-1；
Step 2, setting the river course roughness according to the selected river course section, and determining the river bed slope;
step 3, setting the lowest calculation water level L of the selected river cross section min And the highest calculated water level L max The distance from the lowest calculated water level to the highest calculated water level is divided into 80 levels in the vertical direction, and the water level of each level is recorded as L j ，
Step 4, at each stage of water level L j Then, the average flow velocity u of the vertical line of each measuring point is calculated by adopting an S-K model ji Will u ji The horizontal integral is obtained to obtain the water level L j Lower excess flow rate Q j ；
The expression of the S-K model is as follows:
wherein g is the acceleration of gravity, h ji Is the water level L j Depth of water, s, at ith measuring point of lower river section 0 Is the riverbed slope, z bi Is the elevation of the ith measuring point of the river cross section, c is the roughness of the river, u ji Is the water level L j The average flow velocity of the vertical line of the ith measuring point is lower, lambda is a dimensionless diffusion coefficient, and y represents the transverse direction along the section;
step 5, calculating to obtain the water level L of each stage according to the topographic data in the step 1 j The lower flow cross-sectional area is A j Dividing the flow by the corresponding flow cross-section area to obtain the average flow velocity v of the flow cross-section j Finally, calculating the water level L of each stage j Coefficient of kinetic energy correction alpha j ；
Step 6, according to the water level sequence of 1 to 80 levels, using the water level L j Correcting the coefficient alpha for independent variable and kinetic energy j For dependent variables, a relational table is made corresponding to the functional relationships, which are denoted as alpha j (L j )；
Step 7, for the function alpha in step 6 j (L j ) Adopting db6 wavelet to make discrete wavelet transformation to obtain transformed function space W m And outputs a function alpha j (L j ) After discrete wavelet transform, in function space W m Obtaining a relation graph of the lower coefficient, the number of high-frequency signal layers and the water level so as to obtain the absolute value of the coefficient corresponding to each high-frequency signal layer;
step 8, setting the water level L of each stage j And (4) recording the coefficient absolute values of the corresponding highest-frequency signals into the relation table in the step (6), sequencing the coefficient absolute values of all the highest-frequency signals in the table from large to small, taking the coefficient absolute value corresponding to the 8 th percent position in the sequence as a threshold, and taking the water level elevation corresponding to the coefficient absolute value before the 8 th percent position in the sequence as the first-stage river floodbeach elevation in the river cross section multi-stage river floodbeach.
2. The method for determining the elevation of a flood beach based on wavelet analysis of claim 1,step 4 the flow Q j The calculation formula of (2) is as follows:
wherein, B i The width from the ith measuring point to the (i + 1) th measuring point.
3. The method for determining the elevation of a flood plain based on wavelet analysis as claimed in claim 1, wherein the kinetic energy correction factor α of step 5 j The calculation formula of (2) is as follows:
wherein, B i Is the width from the ith measuring point to the (i + 1) th measuring point, v j Is the water level L j The average flow velocity of the lower flow cross section,
A j is the water level L j The area of the lower flow cross section,
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106295056A (en) * | 2016-08-22 | 2017-01-04 | 河海大学 | A kind of river with compound section alluvial flat and the automatic identifying method of major trough |
| CN106320255A (en) * | 2016-08-22 | 2017-01-11 | 河海大学 | Overbank flow floodplain and channel excess flow computing method |
| CN106682317A (en) * | 2016-12-29 | 2017-05-17 | 武汉大学 | Construction method of flat shoal flow prediction model based on joint control of upstream-downstream borders over lower reach |
| CN109360271A (en) * | 2018-10-16 | 2019-02-19 | 长江水利委员会长江科学院 | It is a kind of to determine method with the repeatable flood land line water level based on section scale |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106295056A (en) * | 2016-08-22 | 2017-01-04 | 河海大学 | A kind of river with compound section alluvial flat and the automatic identifying method of major trough |
| CN106320255A (en) * | 2016-08-22 | 2017-01-11 | 河海大学 | Overbank flow floodplain and channel excess flow computing method |
| CN106682317A (en) * | 2016-12-29 | 2017-05-17 | 武汉大学 | Construction method of flat shoal flow prediction model based on joint control of upstream-downstream borders over lower reach |
| CN109360271A (en) * | 2018-10-16 | 2019-02-19 | 长江水利委员会长江科学院 | It is a kind of to determine method with the repeatable flood land line water level based on section scale |
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