CN113585161A - Construction method of alluvial river deep body lateral migration prediction model - Google Patents
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Abstract
The invention discloses a construction method of a alluvial river deep body lateral migration prediction model, which comprises the following steps: collecting topographic data and river hydrological data; calculating the average value of the transverse migration distance of the deep body and the beach river width of the whole river reach by utilizing a river reach average strategy; constructing a dimensionless parameter by using the average value, and taking the dimensionless parameter as the transverse migration rate of the alluvial river deep body; analyzing the correlation among the lateral migration rate of the deep body, the upstream incoming water and sand conditions and the downstream erosion datum plane change value, and constructing a prediction model of the lateral migration of the alluvial river deep body. The invention constructs the lateral migration rate of the river segment deep body to represent the lateral migration amplitude of the alluvial river segment, can better reflect the lateral migration characteristics of the whole river segment deep body, and makes up the defect of roughly determining the lateral migration amplitude of the deep body by adopting a river situation diagram; the prediction model can better predict the adjustment trend of alluvial river deep body lateral migration, and has guiding significance for understanding the alluvial river bed evolution law and river regulation planning.
Description
Technical Field
The invention relates to the technical field of water conservancy and hydropower engineering, in particular to a construction method of a transverse migration prediction model of alluvial river deep body.
Background
The deep body is the line of the lowest point of the river bed in the area of the fluvial main trough, and the lateral swinging of the deep body on the river bed is called the lateral migration of the deep body. The lateral migration of the body is an important component of the lateral deformation of alluvial river, and its influence factors are numerous, so that the prediction of the lateral migration of alluvial river bodies is very difficult. Therefore, the study of the alluvial river deepbody lateral migration prediction model has important significance for understanding the alluvial river bed evolution law and the river regulation and planning.
The research method of the transverse migration prediction model of alluvial river deep body at home and abroad can be mainly divided into two categories: the first type is numerical simulation based on hydrosand dynamics, and the second type is a statistical model based on measured data; numerical simulation based on water-sand dynamics simulates the lateral migration process of a body of water mainly by simplifying the physical process of water-sand-riverbed movement and by using a two-dimensional water-sand mathematical model. The method usually needs detailed soil characteristic data of the river bank and the riverbed of the river reach, parameter values in the model have no unified standard, and the method is not suitable for lateral migration prediction of the deep body of the long-time river reach; the statistical model based on the measured data is a common method in the river bed evolution analysis, the method for predicting the alluvial river deep body lateral migration is relatively few, the magnitude of the deep body lateral migration is mainly determined by comparing the river situation diagrams of the river sections at different times in the prior research, and the method for predicting the deep body lateral migration cannot fully consider the synergistic effect of the upstream water sand and the downstream erosion datum plane.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above-mentioned conventional problems.
Therefore, the technical problem solved by the invention is as follows: the statistical model based on the measured data can not determine the lateral migration distance of alluvial river deep body mainly by comparing river reach maps at different time periods, and the prediction method can not fully consider the problem of the synergistic effect of upstream water sand and downstream erosion datum plane.
In order to solve the technical problems, the invention provides the following technical scheme: collecting topographic data and river hydrological data; extracting the transverse migration distance and the beach river width of each silted section according to the topographic data, and calculating the average value of the transverse migration distance and the beach river width of the whole river reach by utilizing a river reach average strategy; constructing a dimensionless parameter by using the average value, and taking the dimensionless parameter as the transverse migration rate of the alluvial river deep body; and analyzing the correlation among the lateral migration rate of the deep body, the upstream incoming water and sand conditions and the downstream erosion datum plane change value to construct a prediction model of the lateral migration of the alluvial river deep body.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: the topographic data comprises measured topographic data of each silted section of the river reach after flood, and the water level data comprises daily average sand content of an upstream hydrological station and water level of a downstream hydrological station.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: the average flat beach width of the river reach
Comprises the steps of (a) preparing a mixture of a plurality of raw materials,
wherein L represents the total length of the river reach, K represents the number of actually measured sections in the river reach, and DeltaxjRepresents the distance between two adjacent sections (j, j +1),
represents the average flat beach width of the river reach, Bj、Bj+1Respectively showing the flat beach widths of the j and j +1 sections.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: the average deep body lateral migration distance of the river reach
Comprises the steps of (a) preparing a mixture of a plurality of raw materials,
wherein the content of the first and second substances,
representing the mean lateral migration distance, Δ D, of the body of the riverj、ΔDj+1The lateral migration distance of the body of section j, j +1 is shown.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: seeking the lateral migration rate of the river segment deep body based on the average lateral migration distance of the river segment, the average flat beach river width of the current year river segment and the average flat beach river width of the previous year river segment includes,
wherein the content of the first and second substances,
the average flat beach river width of the river reach of the current year and the previous year respectively, and eta represents the lateral migration rate of the river reach deep body.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: the method for constructing the prediction model of the alluvial river depth body lateral migration comprises the following steps,
calculating the average sand content 4 years before the hydrological station according to the daily average sand content of the upstream hydrological station
Calculating the annual average change value delta Z of the downstream erosion datum plane according to the water level data of the downstream hydrological station of the river reacht；
Analyzing the average sand content of the previous 4 years
And the annual average change value Delta Z of the downstream erosion datum planetEstablishing a alluvial river deep body lateral migration prediction model according to the correlation relation;
and (3) calibrating relevant parameters of the alluvial river deep body lateral migration prediction model by adopting hydrological data of hydrological stations at upstream and downstream of the river reach and measured topographic data of the silted observation section after the flood.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: obtaining a lateral migration prediction model of the alluvial river deep body based on the average sand content in the previous 4 years and the average change value of the downstream erosion datum plane,
wherein k represents a coefficient, alpha and beta represent indexes, eta represents the lateral migration rate of the river reach body of the prediction model,
represents the average sand content, Δ Z, in the previous 4 yearstIndicating the annual mean change value of the downstream erosion datum.
As a preferable scheme of the construction method of the alluvial river deep body lateral migration prediction model, the method comprises the following steps: and calibrating and verifying k, alpha and beta parameters in the prediction model by adopting a multiple linear regression analysis strategy according to the sand content data of the upstream hydrological station, the water level data of the downstream hydrological station and the deep body migration rate data obtained by actually measuring topographic data after a flood.
The invention has the beneficial effects that: the method accurately calculates the annual transverse migration distance of each silted section deep body based on actually measured topographic data, and adopts a river reach averaging strategy to construct the river reach deep body transverse migration rate to represent the transverse migration amplitude of the alluvial river deep body, so that the transverse migration characteristics of the deep body of the whole river reach can be better reflected, and the defect that the traditional river situation graph is adopted to roughly determine the transverse migration amplitude of the deep body is overcome; the method considers the synergistic effect of the upstream water and sand conditions and the downstream erosion datum plane, and the established prediction model can better predict the adjustment trend of the transverse migration of the alluvial river deep body, and has guiding significance for knowing the alluvial river bed evolution law and river regulation planning.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
FIG. 1 is a basic flowchart of a method for constructing a lateral migration prediction model of a alluvial river deep body according to an embodiment of the present invention;
FIG. 2 is a graph of cross-sectional depth body lateral migration distance and beach width of a method for constructing a alluvial river depth body lateral migration prediction model according to an embodiment of the present invention;
FIG. 3 is a diagram of the change of the sand content of the hydrological station (gantry) at the upstream of the dry river reach of the yellow river, the north, the yellow river and the method for constructing the lateral migration prediction model of the alluvial river deep body according to one embodiment of the present invention;
FIG. 4 is a diagram illustrating a variation of erosion datum level (Tongguan elevation) at the downstream of the dry flow section of the yellow river, the North China, according to the method for constructing a lateral migration prediction model of alluvial river depth body according to an embodiment of the present invention;
FIG. 5 is a diagram showing the correlation between the lateral migration rate of the small north main stream river reach and the average sand content and the elevation change value of Tongguan in 4 years before the gantry according to the method for constructing the lateral migration prediction model of alluvial river depth according to an embodiment of the present invention;
fig. 6 is a comparison graph of the calculated value and the measured value of the lateral migration rate of the small north dry-run body according to the method for constructing the lateral migration prediction model of the alluvial river depth body according to one embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1 to 4, a method for constructing a lateral migration prediction model of a alluvial river deep body is provided as an embodiment of the present invention, and includes:
s1: collecting topographic data and river hydrological data. It should be noted that:
the topographic data comprises measured topographic data after flood of each silted section of the river reach, and the water level data comprises daily average sand content of an upstream hydrological station and water level of a downstream hydrological station; in this example, the dry flow of the small north of the yellow river is used as a research river reach, and measured topographic data after flood of 25 deposition observation cross sections in the continuous deposition period (1986-2001) of the yellow river are collected, the daily average sand content of the gantry hydrological station and the flow of the Tongguan hydrological station at 1000m are collected3The water level (stroke height) at/s is the downstream erosion reference surface in this embodiment.
S2: and extracting the transverse migration distance and the beach river width of each siltation section according to the topographic data, and calculating the average value of the transverse migration distance and the beach river width of the whole river reach by utilizing a river reach averaging strategy. It should be noted that:
in this embodiment, as shown in fig. 2, the lateral migration distance and the width of the flat river of the deep body of 25 siltation observation sections of the dry flow river reach of the north and the south of the yellow river are determined according to the above method. 1986 and 1987, the transverse migration distance of the garden mouth section deep body was 241m, and the width of the flat river was increased from 1265m in 1986 to 1378m in 1987.
Calculating the average flat beach river width of 25 siltation sections of the main flow river section in the small north of the yellow river
Comprises the steps of (a) preparing a mixture of a plurality of raw materials,
wherein L represents the total length of the river reach, K represents the number of actually measured sections in the river reach, and DeltaxjRepresents the distance between two adjacent sections (j, j +1),
represents the average flat beach width of the river reach, unit: m, Bj、Bj+1The flat beach river width of the j and j +1 th sections is respectively expressed as the following unit: and m is selected.
Average deep body lateral migration distance of 25 silted cross sections of yellow river small north main flow river reach
Comprises the steps of (a) preparing a mixture of a plurality of raw materials,
wherein the content of the first and second substances,
represents the average deepbody lateral migration distance of the river reach, unit: m, Delta Dj、ΔDj+1The lateral migration distance of a deep body of the j, j +1 th section is expressed as: and m is selected.
S3: and constructing a non-dimensionalized parameter by using the average value, and reflecting the change characteristics of the lateral migration of the river section deep body by using the non-dimensionalized parameter as the alluvial river deep body lateral migration rate. It should be noted that:
seeking the lateral migration rate of the deep body of the river reach based on the average lateral migration distance of the river reach, the average flat beach river width of the current river reach and the average flat beach river width of the river reach of the previous year,
wherein the content of the first and second substances,
the average flat beach river width of the river reach of the current year and the previous year respectively is represented by the following units: m, η represents the lateral migration rate of the river body.
S4: and analyzing the correlation among the lateral migration rate of the deep body, the average sand content of the longmen in 4 years and the variation value of the Tongguan elevation erosion datum plane, and constructing a prediction model of the lateral migration of the alluvial river deep body. It should be noted that:
constructing a prediction model of alluvial river deepbody lateral migration includes,
(1) calculating the average sand content 4 years before the dragon according to the daily average sand content of the upstream hydrological station
(2) Calculating the annual average variation value delta Z of the standard erosion surface of the gate of the mill according to the water level data of the hydrological station at the downstream of the river reacht；
(3) Analysis of lateral Density of deep bodies versus average Sand content 4 years before gantry
Annual average variation value delta Z of Tongtong height erosion datum planetAnd establishing a model for predicting the lateral migration of the underscored river deep body under the synergistic influence of the water and sand and the erosion datum plane. It should be noted that:
constructing a model for predicting the lateral migration of the undershot river channel body under the synergistic effect of the water sand and the erosion datum surface by taking the average sand content and the annual average change value of the Tongguan elevation erosion datum surface of 4 years before the gantry as independent variables and the lateral migration rate of the deep body of the dry river channel of the North Xiao as dependent variables,
wherein k represents a coefficient, alpha and beta represent indexes, eta represents the lateral migration rate of the river reach body of the prediction model,
represents the average sand content, Δ Z, in the previous 4 yearstRepresenting the annual average change value of the downstream erosion datum surface;
(4) and (3) calibrating relevant parameters of the alluvial river deep body lateral migration prediction model by adopting hydrological data of hydrological stations at upstream and downstream of the river reach and measured topographic data of the silted observation section after flood. It should be noted that:
calibrating parameters of a lateral migration prediction model of the undershoot accumulated river body under the synergistic influence of the water sand and the erosion datum plane according to the sand content data of the upstream hydrological station, the water level data of the downstream hydrological station and the migration rate data of the body obtained by actually measuring terrain data after a flood; and calibrating and verifying k, alpha and beta parameters in the prediction model by adopting a multiple linear regression analysis strategy according to the Longmen sand content data, Tongguan elevation erosion datum surface annual average change data and deep body lateral mobility data obtained by actually measured topographic data in 1986-2001.
The method accurately calculates the annual transverse migration distance of each silted section deep body based on actually measured topographic data, and adopts a river reach averaging strategy to construct the river reach deep body transverse migration rate to represent the transverse migration amplitude of the alluvial river deep body, so that the transverse migration characteristics of the deep body of the whole river reach can be better reflected, and the defect that the traditional river situation graph is adopted to roughly determine the transverse migration amplitude of the deep body is overcome; the method considers the synergistic effect of the upstream water and sand conditions and the downstream erosion datum plane, and the established prediction model can better predict the adjustment trend of the transverse migration of the alluvial river deep body, and has guiding significance for knowing the alluvial river bed evolution law and river regulation planning.
Example 2
Referring to fig. 5 to 6, a second embodiment of the present invention is different from the first embodiment in that a verification test of a method for constructing a alluvial river depth lateral migration prediction model is provided, in order to verify and explain the technical effects adopted in the method, parameters k, α and β in the model are calibrated based on the sand content data, the elevation change data of sandguan and the lateral migration rate data of the great river at the longmen dry river reach in the yellow river, the north of yellow river, the year 1998 and the measured terrain data, and the model is verified by using the data in the year 1999, the year 2001.
The results of the model calibration and verification show that: FIG. 5 shows that the correlation coefficient between the lateral migration rate of deep body in the dry river reach 0.65 and the average sand content and the elevation change value of Tongguan in the first 4 years, so the model can better predict the adjustment trend of the lateral migration of alluvial river deep body.
Table 1: data comparison table of measured value and calculated value of lateral migration rate of the young Honghu of the dry river reach of the North Xiao in 1987-2001.
| Year of year | Measured value | Calculated value | Year of year | Measured value | Calculated value |
| 1987 | 0.126 | 0.115 | 1995 | 0.221 | 0.298 |
| 1988 | 0.169 | 0.182 | 1996 | 0.300 | 0.274 |
| 1989 | 0.290 | 0.254 | 1997 | 0.168 | 0.154 |
| 1990 | 0.284 | 0.255 | 1998 | 0.220 | 0.212 |
| 1991 | 0.411 | 0.319 | 1999 | 0.216 | 0.169 |
| 1992 | 0.343 | 0.346 | 2000 | 0.146 | 0.195 |
| 1993 | 0.230 | 0.300 | 2001 | 0.227 | 0.230 |
| 1994 | 0.171 | 0.231 |
In order to verify the empirical formula, table 1 shows the comparison between the measured value and the calculated value of the lateral migration rate of the body of the young north dry-run river reach from 1987 to 2001, and it can be seen from fig. 6 that the change trend of the calculated value and the measured value of the lateral migration rate of the body of the deep body is basically consistent.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (8)
1. A method for constructing a alluvial river deepwater lateral migration prediction model is characterized by comprising the following steps:
collecting topographic data and river hydrological data;
extracting the transverse migration distance and the beach river width of each silted section according to the topographic data, and calculating the average value of the transverse migration distance and the beach river width of the whole river reach by utilizing a river reach average strategy;
constructing a dimensionless parameter by using the average value, and taking the dimensionless parameter as the transverse migration rate of the alluvial river deep body;
and analyzing the correlation among the lateral migration rate of the deep body, the upstream incoming water and sand conditions and the downstream erosion datum plane change value to construct a prediction model of the lateral migration of the alluvial river deep body.
2. The method of constructing a alluvial river body lateral migration prediction model as claimed in claim 1, wherein: the topographic data comprises measured topographic data of each silted section of the river reach after flood, and the water level data comprises daily average sand content of an upstream hydrological station and water level of a downstream hydrological station.
3. The method of constructing a prediction model of the lateral migration of alluvial river body as claimed in claim 1 or 2, wherein: the average flat beach width of the river reach
Comprises the steps of (a) preparing a mixture of a plurality of raw materials,
wherein L represents the total length of the river reach, K represents the number of actually measured sections in the river reach, and DeltaxjRepresents the distance between two adjacent sections (j, j +1),
represents the average flat beach width of the river reach, Bj、Bj+1Respectively showing the flat beach widths of the j and j +1 sections.
4. The method of constructing a alluvial river body lateral migration prediction model as claimed in claim 3, wherein: the average deep body lateral migration distance of the river reach
Comprises the steps of (a) preparing a mixture of a plurality of raw materials,
wherein the content of the first and second substances,
representing the mean lateral migration distance, Δ D, of the body of the riverj、ΔDj+1The lateral migration distance of the body of section j, j +1 is shown.
5. The method of constructing a alluvial river body lateral migration prediction model as claimed in claim 4, wherein: seeking the lateral migration rate of the river segment deep body based on the average lateral migration distance of the river segment, the average flat beach river width of the current year river segment and the average flat beach river width of the previous year river segment includes,
wherein the content of the first and second substances,
the average flat beach river width of the river reach of the current year and the previous year respectively, and eta represents the lateral migration rate of the river reach deep body.
6. The method of constructing a alluvial river body lateral migration prediction model as claimed in claim 1, wherein: the method for constructing the prediction model of the alluvial river depth body lateral migration comprises the following steps,
calculating the average sand content 4 years before the hydrological station according to the daily average sand content of the upstream hydrological station
Calculating the annual average change value delta Z of the downstream erosion datum plane according to the water level data of the downstream hydrological station of the river reacht；
Analyzing the average sand content of the previous 4 years
And the annual average change value Delta Z of the downstream erosion datum planetPhase ofEstablishing a correlation, and establishing a alluvial river deep body lateral migration prediction model;
and (3) calibrating relevant parameters of the alluvial river deep body lateral migration prediction model by adopting hydrological data of hydrological stations at upstream and downstream of the river reach and measured topographic data of the silted observation section after the flood.
7. The method of constructing a alluvial river body lateral migration prediction model as claimed in claim 6, wherein: obtaining a lateral migration prediction model of the alluvial river deep body based on the average sand content in the previous 4 years and the average change value of the downstream erosion datum plane,
wherein k represents a coefficient, alpha and beta represent indexes, eta represents the lateral migration rate of the river reach body of the prediction model,
represents the average sand content, Δ Z, in the previous 4 yearstIndicating the annual mean change value of the downstream erosion datum.
8. The method of constructing a lateral migration prediction model of alluvial river body as claimed in any one of claims 1, 2 and 6, wherein: and calibrating and verifying k, alpha and beta parameters in the prediction model by adopting a multiple linear regression analysis strategy according to the sand content data of the upstream hydrological station, the water level data of the downstream hydrological station and the deep body migration rate data obtained by actually measuring topographic data after a flood.
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