Automatic discrimination method for alluvial river patterns based on river facies coefficient, related equipment

Abstract

The present application discloses a method for automatically discriminating the river pattern of alluvial rivers based on the river facies coefficient and related devices. The method for automatically discriminating the river pattern of alluvial rivers based on the river facies coefficient includes: obtaining the measured flow result data of the target river reach in multiple historical time periods, where the measured flow result data includes the measured flow and the measured hydraulic geometric form parameters; determining the river facies relationship corresponding to each historical time period, where the river facies relationship includes the river facies parameter, and the river facies relationship characterizes the correlation between the measured flow and the measured hydraulic geometric form parameters of the historical time period based on the river facies parameter; and determining the alluvial river pattern information of the target river reach based on the river facies parameters in the river facies relationships corresponding to multiple different historical time periods. The present application can make the discrimination of the alluvial river pattern more efficient, rapid, and simple.

Description

Technical Field

[0001] This application relates to the fields of river evolution simulation, river regulation and protection, and specifically relates to an automatic discrimination method for alluvial river types based on river facies coefficients and related equipment. Background Art

[0002] The alluvial river type is a spatial form formed by alluvial rivers in the long-term automatic adjustment process and adapted to external conditions, which is closely related to the hydrodynamic characteristics of river channels, sediment transport characteristics, and the evolution law of riverbed morphology. Accurately determining its river type category and evolution trend is of great significance for predicting river evolution characteristics, formulating appropriate regulation plans, etc.

[0003] In related technologies, the discrimination of alluvial river types can be achieved by analyzing factors such as the distribution of fluvial facies deposits, the time series characteristics of the main stream swing discharge, the longitudinal transmission mechanism of the water levels and riverbed elevations of the upstream and downstream river channels, and the propagation characteristics of the main stream swing wave in the riverbed medium. However, the data acquisition cost of the fluvial facies deposit distribution is high and the difficulty is great, and the research time and space scales are large. Moreover, the analysis processes of the main stream swing characteristics, longitudinal transmission mechanism, etc. have problems such as complex operations and high requirements for basic data. Thus, it can be seen that the current discrimination process of alluvial river types is complex and has high requirements for the technical level of personnel. Summary of the Invention

[0004] The embodiments of this application provide an automatic discrimination method for alluvial river types based on river facies coefficients and related equipment, aiming to make the discrimination of alluvial river types more efficient, fast, and simple.

[0005] On the one hand, this application provides an automatic discrimination method for alluvial river types based on river facies coefficients, and the method includes:

[0006] Obtain the measured flow result data of the target river reach in multiple historical time periods, where the measured flow result data includes measured flow and measured hydraulic geometric shape parameters;

[0007] Determine the river facies relationship corresponding to each historical time period, where the river facies relationship includes river facies parameters, and the river facies relationship characterizes the correlation between the measured flow and the measured hydraulic geometric shape parameters of the historical time period based on the river facies parameters;

[0008] Based on the river facies parameters in the river facies relationships corresponding to multiple different historical time periods, determine the alluvial river type information of the target river reach.

[0009] In some embodiments, the measured hydraulic geometric parameters include measured river width, measured water depth, and measured flow velocity. The river phase parameter in the river regime formula characterizing the correlation between the measured flow rate and the measured river width during the historical time period is the river width parameter. The river phase parameter in the river regime formula characterizing the correlation between the measured flow rate and the measured water depth during the historical time period is the water depth parameter. The river phase parameter in the river regime formula characterizing the correlation between the measured flow rate and the measured flow velocity during the historical time period is the flow velocity parameter;

[0010] Based on the river phase parameters in the river regime formulas corresponding to multiple different historical time periods, determine the alluvial river type information of the target river reach, including:

[0011] Based on the river width parameters, water depth parameters, and flow velocity parameters corresponding to multiple different historical time periods, determine the alluvial river type information of the target river reach.

[0012] In some embodiments, the river width parameter includes a river width index, the water depth parameter includes a water depth index, and the flow velocity parameter includes a flow velocity index. The determining of the alluvial river type information of the target river reach based on the river width parameters, water depth parameters, and flow velocity parameters corresponding to multiple different historical time periods includes:

[0013] Generate a triangular relationship diagram among the river width index, water depth index, and flow velocity index. The triangular relationship diagram includes multiple position points, and each position point corresponds to the river width index, water depth index, and flow velocity index corresponding to a historical time period;

[0014] Based on the triangular relationship diagram, determine the alluvial river type information of the target river reach.

[0015] In some embodiments, the determining of the alluvial river type information of the target river reach based on the triangular relationship diagram includes:

[0016] In the triangular relationship diagram, determine the dividing lines of different alluvial river types;

[0017] Based on the relative position relationship between the dividing lines and the multiple position points in the triangular relationship diagram, determine the alluvial river type information of the target river reach.

[0018] In some embodiments, the preset historical period includes multiple different river channel morphology adjustment cycles. The alluvial river type information includes the alluvial river type of the target river reach in each river channel morphology adjustment cycle. The determining of the alluvial river type information of the target river reach based on the relative position relationship between the dividing lines and the multiple position points in the triangular relationship diagram includes:

[0019] For each of the river channel form adjustment cycles, among multiple position points in the triangular relationship diagram, determine the position points corresponding to multiple historical time periods within the river channel form adjustment cycle;

[0020] Based on the relative position relationship between the demarcation line and the position points corresponding to multiple historical time periods within the river channel form adjustment cycle, determine the alluvial river type of the target river reach within the river channel form adjustment cycle.

[0021] In some embodiments, the river channel form adjustment cycle is determined through the following steps:

[0022] Obtain the runoff, sediment transport volume, and cumulative erosion and deposition volume per unit river length of the target river reach for each historical time period in the preset historical period;

[0023] Based on the runoff, sediment transport volume, and cumulative erosion and deposition volume per unit river length, divide the preset historical period to obtain multiple different river channel form adjustment cycles.

[0024] In some embodiments, the determination of the river regime relationship corresponding to each historical time period includes:

[0025] Obtain a preset power function relationship, which includes undetermined exponents and undetermined coefficients;

[0026] Use the power function relationship to fit the correlation relationship between the measured flow rate and the measured hydraulic geometric form parameters of the historical time period to determine the values of the undetermined exponents and the undetermined coefficients, and obtain the river regime relationship corresponding to the historical time period, where the river regime parameters are at least one of the undetermined exponents and the undetermined coefficients.

[0027] In some embodiments, before determining the river regime relationship corresponding to each historical time period, it further includes:

[0028] Delete the measured flow rate result data that meets the preset conditions, and the preset conditions include at least one of the following:

[0029] The historical time period corresponding to the measured flow rate result data is within the preset low flow period;

[0030] The measured flow rate in the measured flow rate result data is less than the flow rate threshold, and the flow rate threshold is determined based on the floodplain flow rate of the historical time period corresponding to the measured flow rate.

[0031] On the other hand, an embodiment of the present application provides an automatic discriminator for alluvial river types based on river regime coefficients, including:

[0032] A first acquisition module, configured to acquire measured flow result data of a target river reach in multiple historical time periods, where the measured flow result data includes measured flow and measured hydraulic geometric shape parameters;

[0033] A first determination module, configured to determine a river regime formula corresponding to each of the historical time periods, where the river regime formula includes river regime parameters, and the river regime formula characterizes the correlation between the measured flow and the measured hydraulic geometric shape parameters in the historical time period based on the river regime parameters;

[0034] A second determination module, configured to determine alluvial river type information of the target river reach based on the river regime parameters in the river regime formulas corresponding to multiple different historical time periods.

[0035] On the other hand, the present application further provides a computer device, where the computer device includes:

[0036] One or more processors;

[0037] A memory; and

[0038] One or more applications, where the one or more applications are stored in the memory and are configured to be executed by the processor to implement the steps in any one of the above-mentioned alluvial river type automatic discrimination methods based on river regime coefficients.

[0039] On the other hand, the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is loaded by a processor to execute the steps in any one of the above-mentioned alluvial river type automatic discrimination methods based on river regime coefficients.

[0040] On the other hand, the embodiments of the present application provide a computer program product, including a computer program or instruction, and the computer program or instruction is executed by a processor to implement the alluvial river type automatic discrimination method based on river regime coefficients as described in any one of the above.

[0041] The alluvial river type automatic discrimination method and related devices provided by the embodiments of the present application, by acquiring the measured flow and measured hydraulic geometric shape parameters of a target river reach in multiple historical time periods, then determining a river regime formula that characterizes the correlation between the measured flow and the measured hydraulic geometric shape parameters in the historical time period, and determining the alluvial river type information of the target river reach based on the river regime parameters in the river regime formulas corresponding to multiple different historical time periods, compared with the river type analysis schemes based on river facies sediment distribution, mainstream swing characteristics, longitudinal transfer mechanism, etc., can make the discrimination of alluvial river types more efficient, fast, simple, and have lower requirements for the technical level of technicians. Description of the Drawings

[0042] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0043] Figure 1 It is a schematic diagram of an embodiment of the automatic discrimination method for alluvial river patterns based on the river facies coefficient provided in the embodiments of the present application;

[0044] Figure 2 It is a schematic diagram of the variation process of the river width index, water depth index, and flow velocity index corresponding to multiple different historical time periods provided in the embodiments of the present application;

[0045] Figure 3 It is a schematic diagram of a triangular relationship diagram including multiple position points in the embodiments of the present application;

[0046] Figure 4 It is a schematic diagram of the variation process of the runoff and sediment transport volume of the target river reach over time in a preset historical period in the embodiments of the present application;

[0047] Figure 5 It is a schematic diagram of the variation process of the cumulative erosion and deposition volume per unit river length of the target river reach over time in a preset historical period in the embodiments of the present application;

[0048] Figure 6 It is a schematic diagram of the structure of an embodiment of the automatic discrimination device for alluvial river patterns based on the river facies coefficient provided in the embodiments of the present application;

[0049] Figure 7 It is a schematic diagram of the terminal structure of an embodiment of the computer device provided in the embodiments of the present application.

[0050] Among them, Figure 2 、 3 4 are color pictures to facilitate the distinction of different objects in the same picture. Specific embodiments

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0052] In the description of the present application, the terms "first" and "second" are used only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present application, "a plurality of" means two or more, unless otherwise specifically defined.

[0053] In the present application, the phrase "in some embodiments" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "in some embodiments" in the present application is not necessarily construed as being more preferred or having more advantages than other embodiments. In order for any person skilled in the art to implement and use the present application, the following description is given. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present application can also be implemented without using these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present application with unnecessary details. Therefore, the present application is not intended to be limited to the illustrated embodiments, but is to be accorded the widest scope consistent with the principles and features disclosed in the present application.

[0054] It should be noted that since the system of the embodiments of the present application is executed in a computer device, the processing objects of each computer device exist in the form of data or information. For example, time, which is actually time information. It can be understood that in subsequent embodiments, if dimensions, quantities, positions, etc. are mentioned, they are all corresponding data existences for the computer device to process, and specific details are not elaborated here.

[0055] The embodiments of the present application provide a method and related devices for automatically discriminating the river types of alluvial rivers based on the river phase coefficient. The aim is to, based on the measured flow result data of the hydrological observation stations of the target river reach, on the basis of analyzing the adjustment rules of the measured river width B, measured water depth H, and measured flow velocity V at different times, adopt the cross-sectional river phase relationship formula in the form of a classical power function, and obtain the relationship between the measured hydraulic geometric shape parameters (measured river width B, measured water depth H, measured flow velocity V) and the measured flow rate Q through non-linear fitting (y = αQ β ), and determine the alluvial river type information of the target river reach by identifying the triangular relationship between the river width index β1, water depth index β2, and flow velocity index β3, and identify the river type adjustment direction of the target river reach, so as to achieve efficient, rapid, and simple discrimination of the alluvial river type and its evolution trend. The following will be described in detail respectively.

[0056] In one embodiment, referring to Figure 1 , the method for automatically discriminating the alluvial river type based on the river phase coefficient includes:

[0057] 101. Obtain the measured flow result data of the target river section in multiple historical time periods. The measured flow result data includes measured flow and measured hydraulic geometric form parameters.

[0058] In the embodiments of the present application, a hydrological observation station is set up at the target river section. The hydrological observation station can obtain the measured flow result data through actual observation. Each historical time period can be an observation year of the hydrological observation station. The measured flow result data of multiple observation years forms a long sequence of measured flow result data.

[0059] In some embodiments of the present application, the measured hydraulic geometric form parameters include at least one of measured river width B, measured water depth H, and measured flow velocity V.

[0060] In some embodiments of the present application, step 101 is illustrated by way of example. Specifically, step 101 may include:

[0061] Step 1.1. Collect and collate the long sequence of measured flow result data of the representative hydrological observation station of the target river section. For a specific hydrological observation station, setting the observation year as yy and the number of observation points as nn, the measured flow result data can be obtained, including the two-dimensional array of measured flow Q, measured river width B, measured water depth H, and measured flow velocity V:

[0062]

[0063] Among them, Q is the measured flow; B is the measured river width; H is the measured water depth; V is the measured flow velocity; i is the observation year; j is the number of observation points of the measured flow result data of each observation year. Where i = 1, 2,..., yy; j = 1, 2,..., nn.

[0064] Step 1.2. Standardize the measured flow result data. Specifically, the measured flow result data of different observation years of the same hydrological observation station is stored in the same Excel file (forming a long sequence of measured flow result table) in the format of observation year i, measured flow Q, measured river width B, measured water depth H, and measured flow velocity V, while the measured flow result data of different hydrological observation stations is named after the hydrological observation station name and stored in different Excel files.

[0065] 102. Determine the river relationship corresponding to each historical time period. The river relationship includes river phase parameters, and the river relationship characterizes the correlation between the measured flow and the measured hydraulic geometric form parameters of the historical time period based on the river phase parameters.

[0066] In an embodiment of the present application, for each historical time period, it is necessary to determine the correlation between the measured flow rate and the measured hydraulic geometric parameters of the historical time period. Therefore, the corresponding river regime formula can be determined by fitting the formula of the correlation.

[0067] Among them, if the measured hydraulic geometric parameters include at least one of the measured river width B, the measured water depth H, and the measured flow velocity V, the river regime parameter in the river regime formula characterizing the correlation between the measured flow rate Q and the measured river width B of the historical time period is the river width parameter, the river regime parameter in the river regime formula characterizing the correlation between the measured flow rate Q and the measured water depth H of the historical time period is the water depth parameter, and the river regime parameter in the river regime formula characterizing the correlation between the measured flow rate Q and the measured flow velocity V of the historical time period is the flow velocity parameter.

[0068] In some embodiments of the present application, the river regime formula may be, for example, in the form of a power function formula, and the river regime parameter in the river regime formula may be at least one of the undetermined exponents and undetermined coefficients in the preset power function formula. Specifically, step 102 may include: obtaining a preset power function formula, which includes undetermined exponents and undetermined coefficients. For example, the power function formula may be y = αQ β , where y is the measured hydraulic geometric parameter, Q is the measured flow rate, α is the undetermined coefficient, and β is the undetermined exponent; using the power function formula to fit the correlation between the measured flow rate and the measured hydraulic geometric parameters of the historical time period to determine the value of the undetermined coefficient α and the value of the undetermined exponent β, and obtaining the river regime formula corresponding to the historical time period.

[0069] In some embodiments of the present application, before performing step 102, it may further include: deleting the measured flow rate result data that meets the preset conditions to filter the measured flow rate result data. Among them, the preset conditions include at least one of the following: the historical time period corresponding to the measured flow rate result data is within the preset low-flow period, and the preset low-flow period may be, for example, from January to April and December; the measured flow rate in the measured flow rate result data is less than the flow rate threshold, and the flow rate threshold is determined based on the bankfull flow rate of the historical time period corresponding to the measured flow rate. For example, the bankfull flow rate may be multiplied by a preset ratio to obtain the flow rate threshold, and the preset ratio may be, for example, 15%. Filtering the measured flow rate result data through the preset conditions can further improve the accuracy of the discrimination of the alluvial river type.

[0070] In some embodiments of the present application, an example is given for the filtering of step 102 and the measured flow result data. Specifically, considering that there are relatively many measured flow result data with small measured flows in the measured flow result data, which will affect the fitting result of the river regime formula. Therefore, before using the non-linear fitting function to solve the river regime formula by the least squares fitting method, the measured flow result data from January to April and December and the measured flow result data with the measured flow less than 15% of the bankfull discharge are excluded. Based on the measured flow result data from May to November and with the measured flow greater than 15% of the bankfull discharge, the undetermined exponents and undetermined coefficients in the power function formula are determined (i.e., B = α1Q β1 、H = α2Q β2 、V = α3Q β3 in the river width exponent β1, water depth exponent β2, flow velocity exponent β3, river width coefficient α1, water depth coefficient α2, and flow velocity coefficient α3, where the above river width parameters include at least one of the river width exponent β1 and the river width coefficient α1, the above water depth parameters include at least one of the water depth exponent β2 and the water depth coefficient α2, and the above flow velocity parameters include at least one of the flow velocity exponent β3 and the flow velocity coefficient α3). Using the for loop statement in the programming language, the values of the undetermined exponents and undetermined coefficients in the power function formula for the measured flow Q, measured river width, measured water depth, and measured flow velocity in different observation years are calculated.

[0071] In addition, using the river regime formula corresponding to the specified historical time period, based on the values of the river regime parameters in the river regime formula, the specific hydraulic geometric shape parameters (such as specific river width, specific water depth, and specific flow velocity) at a specific flow (such as 3000 m 3 / s) in the specified historical time period can also be calculated in reverse.

[0072] 103. Determine the alluvial river type information of the target river section based on the river regime parameters in the river regime formulas corresponding to multiple different historical time periods.

[0073] In the embodiments of the present application, the alluvial river type information of the target river section can be determined based on the magnitude of the values of the river regime parameters in the river regime formulas corresponding to multiple different historical time periods, that is, the alluvial river type information of the target river section is related to the river regime parameters.

[0074] In some embodiments of the present application, step 103 may include: determining the alluvial river type information of the target river section based on the river width parameters, water depth parameters, and flow velocity parameters corresponding to multiple different historical time periods, that is, the alluvial river type information of the target river section is related to the river width parameters, water depth parameters, and flow velocity parameters. Taking the river width index β1 included in the river width parameters, the water depth index β2 included in the water depth parameters, and the flow velocity index β3 included in the flow velocity parameters as an example, a schematic diagram of the changes over time of the river width index β1, water depth index β2, and flow velocity index β3 corresponding to multiple different historical time periods is as follows Figure 2 as shown.

[0075] In some embodiments of the present application, in order to more conveniently determine the alluvial river type information of the target river section, the form of a triangular relationship diagram can be used for analysis. Specifically, determining the alluvial river type information of the target river section based on the river width parameters, water depth parameters, and flow velocity parameters corresponding to multiple different historical time periods may include: generating a triangular relationship diagram among the river width index, water depth index, and flow velocity index (such as Figure 3 as shown), where the coordinate axes corresponding to the river width index, water depth index, and flow velocity index are respectively one side of the triangle in the triangular relationship diagram. The triangular relationship diagram includes multiple position points, and each position point corresponds to the river width index, water depth index, and flow velocity index corresponding to a historical time period, that is, the specific position of each position point is determined based on the values of the river width index, water depth index, and flow velocity index corresponding to the corresponding historical time period; determining the alluvial river type information of the target river section based on the triangular relationship diagram, so that the determination of the alluvial river type information is more simple and intuitive.

[0076] In some embodiments of the present application, determining the alluvial river type information of the target river section based on the triangular relationship diagram may include: in the triangular relationship diagram, determining the dividing line between different alluvial river types, and this dividing line can be set based on experience. For example, when the alluvial river types include wandering type and non-wandering type, the line where the river width index is equal to the water depth index (i.e., β1 = β2) in the triangular relationship diagram can be used as the dividing line between the wandering type and the non-wandering type (such as Figure 3 shown by the dashed line in); based on the relative position relationship between the dividing line and the multiple position points in the triangular relationship diagram, determining the alluvial river type information of the target river section. For example, it can be determined that Figure 3 the historical time periods corresponding to the position points in the area (β1 > β2) to the left of the dashed line in, and determine the alluvial river type of the target river section during these historical time periods as the wandering type. Another example is that it can be determined that Figure 3 the historical time periods corresponding to the position points in the area (β1 < β2) to the right of the dashed line in, and determine the alluvial river type of the target river section during these historical time periods as the non-wandering type.

[0077] In some embodiments of the present application, since the alluvial river pattern determined based on the position points corresponding to a single historical time period may not be accurate enough, and the alluvial river pattern is formed during the long-term adjustment of the target river section, multiple position points corresponding to multiple historical time periods can be comprehensively considered to determine a more accurate alluvial river pattern. Specifically, all historical time periods are within a preset historical period (for example, from 1965 to 2015). Therefore, the preset historical period can be divided to obtain multiple different river channel pattern adjustment cycles within the preset historical period (for example, five river channel pattern adjustment cycles: from 1965 to 1973, from 1974 to 1980, from 1981 to 1985, from 1986 to 1999, and from 2000 to 2015). That is, it is considered that the alluvial river pattern of the target river section is the same within the same river channel pattern adjustment cycle. Therefore, the alluvial river pattern information can include the alluvial river pattern of the target river section in each river channel pattern adjustment cycle. Correspondingly, based on the relative position relationship between the demarcation line and multiple position points in the triangular relationship diagram, determining the alluvial river pattern information of the target river section can include: for each river channel pattern adjustment cycle, among the multiple position points in the triangular relationship diagram, determining the position points corresponding to multiple historical time periods within this river channel pattern adjustment cycle; based on the relative position relationship between the demarcation line and the position points corresponding to multiple historical time periods within this river channel pattern adjustment cycle, determining the alluvial river pattern of the target river section in this river channel pattern adjustment cycle. For example, in Figure 3 most (for example, more than 50%) of the position points corresponding to multiple historical time periods within the river channel pattern adjustment cycle from 1965 to 1973 are located in the area (β1>β2) to the left of the dotted line. Therefore, it can be determined that the alluvial river pattern of the target river section from 1965 to 1973 is a wandering type. For the four river channel pattern adjustment cycles from 1974 to 1980, from 1981 to 1985, from 1986 to 1999, and from 2000 to 2015, most (for example, more than 50%) of the position points corresponding to multiple historical time periods within each river channel pattern adjustment cycle are located in the area (β1<β2) to the right of the dotted line. Therefore, it can be determined that the alluvial river patterns of the target river section in the four river channel pattern adjustment cycles from 1974 to 1980, from 1981 to 1985, from 1986 to 1999, and from 2000 to 2015 are all non-wandering types.

[0078] In addition, the alluvial river pattern information of the target river section can also include the adjustment direction of the alluvial river pattern. For example, based on the alluvial river patterns of the target river section in multiple river channel pattern adjustment cycles, the adjustment direction of the alluvial river pattern can be determined. This adjustment direction can be, for example, that the alluvial river pattern of the target river section changes from a wandering type before 1973 to a non-wandering type after 1973.

[0079] In some embodiments of the present application, the division method of a preset historical period is described. Specifically, the river channel form adjustment period is determined through the following steps: obtaining the runoff, sediment transport volume, and cumulative scouring and silting volume per unit river length of the target river reach in each historical time period within the preset historical period. Among them, the runoff and sediment transport volume of the target river reach in each historical time period within the preset historical period are as shown, for example, Figure 4 as shown in, and the cumulative scouring and silting volume per unit river length of the target river reach in each historical time period within the preset historical period is as shown, for example, Figure 5 as shown in; based on the runoff, sediment transport volume, and cumulative scouring and silting volume per unit river length, the preset historical period is divided to obtain multiple different river channel form adjustment periods. For example, based on the runoff, sediment transport volume, and cumulative scouring and silting volume per unit river length, combined with the human activity conditions of the target river reach in each historical time period within the preset historical period, relevant technical personnel can identify the stage change characteristics of the water-sediment conditions and riverbed evolution of the target river reach, and then divide the preset historical period into multiple different river channel form adjustment periods (such as 5 river channel form adjustment periods from 1965 to 1973, from 1974 to 1980, from 1981 to 1985, from 1986 to 1999, and from 2000 to 2015).

[0080] In the technical solution disclosed in this embodiment, by obtaining the measured flow rate and measured hydraulic geometric form parameters of the target river reach in multiple historical time periods, and then determining the river regime formula that characterizes the correlation between the measured flow rate and the measured hydraulic geometric form parameters of the historical time period, based on the river regime parameters in the river regime formulas corresponding to multiple different historical time periods, the alluvial river type information of the target river reach is determined. Compared with the river type analysis scheme based on river facies sediment distribution, mainstream swing characteristics, longitudinal transfer mechanism, etc., it can make the discrimination of alluvial river types more efficient, rapid, and simple, and has lower requirements for the technical level of technicians.

[0081] Next, with reference to Figure 1 , an example description of the automatic discrimination method for alluvial river types based on the river regime coefficient is given. Specifically, to discriminate the evolution trend of the alluvial river type of the target river reach under changing water-sediment conditions, the following steps are included:

[0082] Step S1, standardize the long-sequence measured flow rate result table to form a data set including measured flow rate Q, measured river width B, measured water depth H, and measured flow velocity V.

[0083] Collect and organize the data of the long-sequence measured flow results table of representative hydrological observation stations in the target river section, set the observation time and observation point number, record the observation year yy=1965 to 2015, the number of observation points nn=142, and form a two-dimensional array including measured flow Q, measured river width B, measured water depth H and measured flow velocity V. The two-dimensional array can be, for example, Q(1965,142), B(1965,142), H(1965,142), V(1965,142). The measured flow results data of the same hydrological observation station in different observation years are stored in the same Excel file in the format of year, month, day, measured flow Q, measured river width B, measured water depth H and measured flow velocity V, as shown in Table 1 below:

[0084] Table 1 Measured flow results Standardized data sets for each observation year

[0085]

[0086] Step S2, river channel morphology adjustment period identification.

[0087] Collect and organize data on the long-term water and sediment conditions of the target river section (such as runoff and sediment transport), riverbed erosion and siltation (such as the cumulative erosion and siltation per unit river length), and human activities. Figure 4 As shown in the figure, the cumulative scouring and silting volume per unit river length of the target river section length sequence is as follows: Figure 5 As shown in the figure, combined with human activities such as reservoir construction in the target river section, the river channel evolution process of the target river section from 1965 to 2015 is divided into five different river channel morphology adjustment periods: 1965 to 1973, 1974 to 1980, 1981 to 1985, 1986 to 1999 and 2000 to 2015.

[0088] Step S3, fitting determines the values ​​of the exponents (such as the river width index β1, the water depth index β2, and the flow velocity index β3) and coefficients (such as the river width coefficient α1, the water depth coefficient α2, and the flow velocity coefficient α3) of the long sequence of river phase relationship equations, as well as the hydraulic geometric parameters under a specific flow rate.

[0089] Considering that there are too many data with smaller measured flow in the measured flow results data, which will affect the fitting results of the river phase relationship, the measured flow results data from January to April and December and the measured flow results data with a measured flow less than 15% of the flat beach flow are eliminated before solving the river phase relationship equation using the least squares fitting method using the nonlinear fitting function. Based on the measured flow results data from May to November with a measured flow greater than 15% of the flat beach flow, the undetermined exponent and undetermined coefficient in the power function relationship (i.e. B=α1Q β1 、H=α2Q β2, V = α3Q β3 The river width index β1, water depth index β2, flow velocity index β3, river width coefficient α1, water depth coefficient α2, and flow velocity coefficient α3 in β3 . Among them, the above river width parameters include at least one of the river width index β1 and the river width coefficient α1, the above water depth parameters include at least one of the water depth index β2 and the water depth coefficient α2, and the above flow velocity parameters include at least one of the flow velocity index β3 and the flow velocity coefficient α3). Using the for loop statement in the programming language MATLAB, calculate the values of the undetermined exponents and undetermined coefficients of the measured flow rate Q, measured river width, measured water depth, and measured flow velocity in the power function relationship for different observation years. In addition, according to the river relationship corresponding to different observation years, the specific hydraulic geometric shape parameters (such as specific river width, specific water depth, and specific flow velocity) of the target river section at a specific flow rate (such as 3000 m 3 / s) for different observation years can also be calculated.

[0090] Step S4, plot the time variation process of the river regime parameters corresponding to different observation years.

[0091] Using the plot function in the programming language MATLAB, a schematic diagram of the variation of the river width index β1, water depth index β2, and flow velocity index β3 with time, such as Figure 2 shown.

[0092] Step S5, determine the adjustment direction of the river channel type (i.e., the alluvial river channel type).

[0093] According to the river channel morphology adjustment period determined in step S2, divide the river width index β1, water depth index β2, and flow velocity index β3 into five different stages: 1965 - 1973, 1974 - 1980, 1981 - 1985, 1986 - 1999, and 2000 - 2015.

[0094] Plot the river width index β1, water depth index β2, and flow velocity index β3 of each observation year in the above five stages into a triangular relationship diagram between the river width index β1, water depth index β2, and flow velocity index β3, as shown in Figure 3 . Using the dashed line β1 = β2 as the characteristic line to distinguish between the wandering type and the non - wandering type, the area to the left of the dashed line (β1 > β2) is the wandering type, and the area to the right of the dashed line (β1 < β2) is the non - wandering type. It can be seen that the alluvial river channel type of the target river section has basically changed from the wandering type before 1973 to the non - wandering type after 1973.

[0095] The automatic discrimination method of alluvial river types based on river regime coefficients provided by the embodiments of the present application is based on the variation characteristics of the exponents in the classical river regime relationship in the form of a power function among the measured flow, measured river width, measured water depth, and measured flow velocity of the cross-section in a long sequence. By using the triangular relationship among the exponents in each river regime relationship, the adjustment direction of alluvial river types is explored. This technology is based on the measured flow result data of hydrological observation stations, with low data acquisition difficulty, low cost, high accuracy, low requirement for the level of technical personnel, and the selected characteristic factors (such as river width exponent, water depth exponent, flow velocity exponent) taking into account the lateral, vertical adjustment characteristics of the river channel and the longitudinal water flow dynamic characteristics, which can realize the efficient, rapid, and simple discrimination of alluvial river types and their evolution trends, and is of great significance for predicting river channel evolution characteristics and formulating appropriate regulation schemes.

[0096] To better implement the automatic discrimination method of alluvial river types based on river regime coefficients in the embodiments of the present application, on the basis of the automatic discrimination method of alluvial river types based on river regime coefficients, the embodiments of the present application also provide an automatic discrimination device for alluvial river types based on river regime coefficients, as Figure 6 shown. The automatic discrimination device 600 for alluvial river types based on river regime coefficients includes:

[0097] A first acquisition module 601, configured to acquire the measured flow result data of the target river section in multiple historical time periods, where the measured flow result data includes measured flow and measured hydraulic geometric form parameters;

[0098] A first determination module 602, configured to determine the river regime relationship corresponding to each historical time period, where the river regime relationship includes river regime parameters, and the river regime relationship characterizes the correlation between the measured flow and the measured hydraulic geometric form parameters of the historical time period based on the river regime parameters;

[0099] A second determination module 603, configured to determine the alluvial river type information of the target river section based on the river regime parameters in the river regime relationships corresponding to multiple different historical time periods.

[0100] The embodiments of the present application also provide a computer device, which integrates any one of the automatic discrimination devices for alluvial river types based on river regime coefficients provided by the embodiments of the present application. As Figure 7 shown, it shows the structural schematic diagram of the computer device involved in the embodiments of the present application. Specifically:

[0101] The computer device may include a processor 701 with one or more processing cores, a memory 702 with one or more computer-readable storage media, a power supply 703, an input unit 704, and other components. Those skilled in the art can understand, Figure 7The computer device structure shown in the figure does not limit the construction of the computer device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Among them:

[0102] The processor 701 is the control center of the computer device, connecting various parts of the entire computer device through various interfaces and lines. By running or executing software programs and / or modules stored in the memory 702, and calling the data stored in the memory 702, it executes various functions of the computer device and processes data, thereby monitoring the computer device as a whole. Optionally, the processor 701 may include one or more processing cores; preferably, the processor 701 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the processor 701.

[0103] The memory 702 can be used to store software programs and modules. The processor 701 executes various functional applications and data processing by running the software programs and modules stored in the memory 702. The memory 702 mainly includes a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function (such as the sound playback function, image playback function, etc.); the data storage area can store data created according to the use of the computer device. In addition, the memory 702 can include high-speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 702 can also include a memory controller to provide the processor 701 with access to the memory 702.

[0104] The computer device also includes a power supply 703 that powers each component. Preferably, the power supply 703 can be logically connected to the processor 701 through a power management system, so as to realize functions such as charging management, discharging management, and power consumption management through the power management system. The power supply 703 can also include any components such as one or more DC or AC power supplies, a recharge system, a power failure detection circuit, a power converter or inverter, and a power status indicator.

[0105] The computer device may also include an input unit 704, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.

[0106] Although not shown, the computer device may further include a display unit and the like, which will not be elaborated herein. Specifically, in this embodiment, the processor 701 in the computer device will, according to the following instructions, load the executable files corresponding to the processes of one or more application programs into the memory 702, and the processor 701 will run the application programs stored in the memory 702 to implement various functions as follows:

[0107] Obtain the measured flow result data of the target river section in multiple historical time periods, where the measured flow result data includes the measured flow and the measured hydraulic geometric shape parameters; determine the river regime relationship corresponding to each historical time period, where the river regime relationship includes river regime parameters, and the river regime relationship characterizes the correlation between the measured flow and the measured hydraulic geometric shape parameters of the historical time period based on the river regime parameters; based on the river regime parameters in the river regime relationships corresponding to multiple different historical time periods, determine the alluvial river type information of the target river section.

[0108] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions or by controlling related hardware through instructions. The instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0109] For this reason, the embodiments of the present application provide a computer-readable storage medium, which may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), a magnetic disk or an optical disc, etc. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any one of the alluvial river type automatic discrimination methods based on river regime coefficients provided by the embodiments of the present application. For example, the computer program loaded by the processor may execute the following steps:

[0110] Obtain the measured flow result data of the target river section in multiple historical time periods, where the measured flow result data includes the measured flow and the measured hydraulic geometric shape parameters; determine the river regime relationship corresponding to each historical time period, where the river regime relationship includes river regime parameters, and the river regime relationship characterizes the correlation between the measured flow and the measured hydraulic geometric shape parameters of the historical time period based on the river regime parameters; based on the river regime parameters in the river regime relationships corresponding to multiple different historical time periods, determine the alluvial river type information of the target river section.

[0111] Embodiments of the present application also provide a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes to implement the automated discrimination method for alluvial river types based on the river facies coefficient as described in any one of the above, for example:

[0112] Obtain the measured flow result data of the target river reach in multiple historical time periods. The measured flow result data includes measured flow and measured hydraulic geometric shape parameters; determine the river facies relationship corresponding to each historical time period. The river facies relationship includes river facies parameters, and the river facies relationship characterizes the correlation between the measured flow and the measured hydraulic geometric shape parameters in the historical time period based on the river facies parameters; based on the river facies parameters in the river facies relationships corresponding to multiple different historical time periods, determine the alluvial river type information of the target river reach.

[0113] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For parts not detailed in a certain embodiment, reference may be made to the detailed descriptions of other embodiments above, and details will not be repeated here.

[0114] In specific implementation, the above-mentioned respective units or structures can be implemented as independent entities, or can be combined arbitrarily to be implemented as the same or several entities. For the specific implementation of the above-mentioned respective units or structures, reference may be made to the method embodiments above, and details will not be repeated here.

[0115] For the specific implementation of each of the above operations, reference may be made to the foregoing embodiments, and details will not be repeated here.

[0116] The above has introduced in detail an automated discrimination method for alluvial river types based on the river facies coefficient and related devices provided by the embodiments of the present application. Specific examples are used herein to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. An automatic identification method of alluvial river type based on river phase coefficient, characterized in that: The method comprises: Obtaining measured flow results data of a target river section in multiple historical time periods, wherein the measured flow results data includes measured flow and measured hydraulic geometry parameters; Determine a river phase relationship equation corresponding to each of the historical time periods, wherein the river phase relationship equation includes a river phase parameter, and the river phase relationship equation characterizes the correlation between the measured flow and the measured hydraulic geometry parameters of the historical time period based on the river phase parameter; Determining the alluvial river type information of the target river section based on the river phase parameters in the river phase relationship equations corresponding to the multiple different historical time periods; Wherein, the measured hydraulic geometric morphological parameters include the measured river width, the measured water depth, and the measured flow velocity; the river phase parameter in the river phase relationship equation representing the correlation between the measured flow rate and the measured river width in the historical time period is a river width parameter; the river phase parameter in the river phase relationship equation representing the correlation between the measured flow rate and the measured water depth in the historical time period is a water depth parameter; the river phase parameter in the river phase relationship equation representing the correlation between the measured flow rate and the measured flow velocity in the historical time period is a flow velocity parameter; The river width parameter includes a river width index, the water depth parameter includes a water depth index, and the flow velocity parameter includes a flow velocity index; Based on the river phase parameters in the river phase relationship equations corresponding to the multiple different historical time periods, the alluvial river type information of the target river section is determined, including: generating a triangular relationship diagram between the river width index, the water depth index, and the flow velocity index, wherein the coordinate axes corresponding to the river width index, the water depth index, and the flow velocity index are respectively one side of the triangle in the triangular relationship diagram, and the triangular relationship diagram includes multiple position points, each of which corresponds to a river width index, a water depth index, and a flow velocity index corresponding to the historical time period; in the triangular relationship diagram, a dividing line of different alluvial river types is determined, and the dividing line is used to characterize a relative numerical value relationship between the river width index, the water depth index, and the flow velocity index; based on the relative position relationship between the dividing line and the multiple position points in the triangular relationship diagram, the alluvial river type of the target river section is determined; The alluvial river type information of the target river section includes the adjustment direction of the alluvial river type in the time dimension.

2. The method for automatically distinguishing the alluvial river type based on the river phase coefficient according to claim 1, characterized in that: The preset historical period includes a plurality of different river morphology adjustment cycles, the alluvial river type information includes the alluvial river type of the target river section in each of the river morphology adjustment cycles, and the alluvial river type of the target river section is determined based on the relative position relationship between the dividing line and a plurality of position points in the triangular relationship diagram, including: For each of the river channel morphology adjustment cycles, determining, among the multiple position points in the triangular relationship diagram, position points corresponding to multiple historical time periods within the river channel morphology adjustment cycle; Based on the relative position relationship between the dividing line and the position points corresponding to multiple historical time periods within the river channel morphology adjustment cycle, the alluvial river type of the target river section in the river channel morphology adjustment cycle is determined.

3. The method for automatically distinguishing the alluvial river type based on river phase coefficient according to claim 2, characterized in that: The river channel morphology adjustment period is determined by the following steps: Obtaining the runoff, sediment transport and cumulative scouring and silting volume per unit river length of the target river section in each historical time period in the preset historical period; Based on the runoff, the sediment transport and the cumulative scouring and silting amount per unit river length, the preset historical period is divided to obtain a plurality of different river channel morphology adjustment cycles.

4. The method for automatically distinguishing the alluvial river type based on river phase coefficient according to claim 1, characterized in that: Determining the river phase relationship corresponding to each of the historical time periods includes: Obtaining a preset power function relationship, wherein the power function relationship includes an undetermined exponent and an undetermined coefficient; The power function relationship is used to fit the correlation between the measured flow and the measured hydraulic geometric parameters of the historical time period to determine the value of the unknown index and the value of the unknown coefficient, and the river phase relationship corresponding to the historical time period is obtained, and the river phase parameter is at least one of the unknown index and the unknown coefficient.

5. The method for automatically distinguishing the alluvial river type based on the river phase coefficient according to claim 1, characterized in that: Before determining the river phase relationship equation corresponding to each of the historical time periods, the method further includes: Delete the measured flow results data that meets the preset conditions, wherein the preset conditions include at least one of the following: The historical time period corresponding to the measured flow results data is within the preset dry season; The measured flow in the measured flow result data is less than a flow threshold, and the flow threshold is determined based on the flat beach flow in a historical time period corresponding to the measured flow.

6. A computer device, characterized in that: The computer device comprises: one or more processors; Memory; And one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the steps in the method for automatic identification of alluvial river types based on river phase coefficients as described in any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the method for automatically distinguishing the alluvial river type based on river phase coefficient described in any one of claims 1 to 5.

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