KR101369815B1 - Method and apparatus for estimating resistance coefficient using field data of natural rivers - Google Patents

Abstract

The present invention uses field measurement data consisting of river data of natural rivers to analyze the flow resistance of rivers, and calculates the relationship between friction coefficient, roughness coefficient, and dimensionless flow velocity. It relates to a method and apparatus for calculating the resistance coefficient used.
According to the present invention, a method of calculating a resistance coefficient using field measurement data of a natural river includes: a first step of inputting field measurement data of a natural river into an input module; A second step of calculating, by the friction coefficient calculation module, the roughness coefficient for the natural river from the field measurement data inputted through the input module; A third step of analyzing, by the coefficient of friction analysis module, a coefficient of friction of the natural river calculated in the second step; A fourth step of the illuminance coefficient calculating module calculating the illuminance coefficient for the natural river from the field measurement data inputted through the input module; A fifth step of analyzing the roughness coefficient of the natural river calculated in the fourth step by the roughness coefficient analyzing module; And a sixth step of outputting each of the analyzed friction coefficients and roughness coefficients by the resistance coefficient output module.

Description

METHOD AND APPARATUS FOR ESTIMATING RESISTANCE COEFFICIENT USING FIELD DATA OF NATURAL RIVERS}

The present invention relates to a method and apparatus for calculating a coefficient of resistance, and more specifically, to a relationship between friction coefficient, roughness coefficient, and dimensionless flow velocity using field measurement data composed of riverbed data of a natural river for analysis of stream resistance. The present invention relates to a method and apparatus for estimating the resistance coefficient using field measurement data of natural rivers, which can be calculated and analyzed.

Resistant to flow in natural rivers consisting mainly of sand and gravel, or vegetation streams in which vegetation such as grass, shrubs, and trees are scattered in flood plains and dikes. It causes the change of flow velocity depending on vegetation and bed data on the overrun. These phenomena are being studied as a major task in hydraulic engineering. The flow resistance can be classified into surface friction of the surface, drag which is a resistance due to shape, wave resistance due to surface distortion, and abnormal state of flow due to local acceleration.

The resistance characteristics of vegetation in rivers are closely related to the flow conditions and vegetation structure, which have various distributions according to the topographical characteristics of rivers, the slope of waterways, and the distribution and range of vegetation species.

The relationship between friction slope and flow rate in a stream is governed by vegetation and stream material resistance to flow, and resistance to stream flow is caused by primitive variability such as friction, bed irregularities, vegetation bed contours, channel alignments, etc. do.

Shear stresses generated by interactions between streams and riverbeds in rivers are the basis for flow analysis and hydraulic stability analysis. In rivers, roughness coefficients are largely classified into vegetation and channel shape and bed data. Roughness coefficients based on riverbed data are mainly determined using empirical formulas obtained through field measurements and model experiments.

In addition, the vegetation of river banks and floodplains ensures the stability of waterways and banks by inhibiting erosion, and serves as habitats for aquatic animals, while it is necessary to predict them hydraulically since it causes disturbance of water due to flow resistance. There is.

Regarding the technique for analyzing the flow of rivers, Korean Patent Laid-Open Publication No. 10-2010-0044371 relates to a method and apparatus for numerical analysis of river fluctuations in natural rivers, which occur in natural streams in which linear and curved channel shapes are mixed. Techniques for accurately simulating bed changes that can occur under various conditions are disclosed.

However, such a conventional technique is a technique for simulating river bed fluctuations that may occur in a river, and a method of estimating a resistance coefficient in consideration of characteristics of the bed bed material cannot be expected. In addition, there is a limit to understanding the underlying variability of all resistance to flow in natural streams.

The present invention has been made to solve the problems described above, by deriving the resistance coefficient of the stream flow through the field measurement data of the natural river resistance coefficient using the field measurement data of the natural river that can be usefully used for manual practice To provide a method and apparatus for calculating

In addition, the present invention analyzes the resistance coefficient of the riverbed data to present the distribution range for each type, the estimation of the roughness coefficient using the actual field data of the natural river that can derive the roughness coefficient relation function as a function of the flow rate and the friction slope It is an object to provide a method and apparatus.

In addition, an object of the present invention is to provide a method and apparatus for estimating roughness coefficients using field measurement data of natural rivers, which can be usefully used for manual practice by deriving a dimensionless flow rate equation as a function of relative diving ratio in natural rivers. do.

However, the object of the present invention is not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, the calculation method of the resistance coefficient using the field measurement data of the natural river according to the present invention comprises the first step of inputting the field measurement data of the natural river to the input module; A second step of calculating, by the friction coefficient calculation module, the roughness coefficient for the natural river from the field measurement data inputted through the input module; A third step of analyzing, by the coefficient of friction analysis module, a coefficient of friction of the natural river calculated in the second step; A fourth step of the illuminance coefficient calculating module calculating the illuminance coefficient for the natural river from the field measurement data inputted through the input module; A fifth step of analyzing the roughness coefficient of the natural river calculated in the fourth step by the roughness coefficient analyzing module; And a sixth step of outputting each of the analyzed friction coefficients and roughness coefficients by the resistance coefficient output module.

The method of calculating the resistance coefficient using the field measurement data according to the present invention is characterized in that the field measurement data of the natural river is riverbed data for sand, gravel, pebbles and amber stones.

In the method of calculating the resistance coefficient using field measurement data according to the present invention, the riverbed data is in the range of the minimum and maximum values for the flow rate, friction inclination, median particle size, average flow rate and depth for sand, gravel, pebbles and amber stones. Characterized in that made.

In the method of calculating the resistance coefficient using the field measurement data according to the present invention, the friction coefficient of the natural river in the second step of the power function type as a function of the flow rate and the friction inclination through the regression analysis for the riverbed data, respectively It is characterized by calculating by the curve joining method.

In the third step, the method of calculating the resistance coefficient using field measurement data is characterized in that the friction coefficient of the natural river is analyzed using a box-whisker quartile method.

In the method of calculating the resistance coefficient using field measurement data according to the present invention, the third step is a friction coefficient of the natural river calculated in the second step and the parameter (fQ ^1/4 / S _f ^{1) / 3} ) to be analyzed.

(Where f is friction coefficient, Q is flow rate (㎥ / s), and S _f is friction inclination)

In the fourth step, the roughness coefficient of the natural river is a power-of-function function having a flow rate and a friction slope as a function of regression analysis on the riverbed data. It is characterized by calculating by the curve joining method.

In the method of calculating the resistance coefficient using field measurement data according to the present invention, in the fifth step, the roughness coefficient of the natural river is characterized in that it is analyzed using a box-whisker quartile analysis method.

In the method of calculating the resistance coefficient using field measurement data according to the present invention, the fifth step includes the roughness coefficient of the natural river calculated in the fourth step and a parameter for the roughness coefficient (nQ ^1/8 / S _f). ^1/6 ).

(Where n is roughness coefficient, Q is flow rate (㎥ / s), and S _f is friction inclination)

In addition, the method of calculating the resistance coefficient using the field measurement data according to the present invention, after the fifth step, characterized in that for calculating the dimensionless flow rate for the relative diving ratio of the field measurement data using the curve fit.

An apparatus for calculating a coefficient of resistance using field measurement data of a natural river according to the present invention includes: a measurement data input module for inputting field measurement data including riverbed data for sand, gravel, pebbles, and amber stones of a natural river; A coefficient of friction calculation module for calculating a coefficient of friction for the field measurement data input to the measurement data input module; A coefficient of friction analysis module for analyzing a coefficient of friction calculated through the coefficient of friction calculation module; An illuminance coefficient calculation module for calculating an illuminance coefficient for the field measurement data inputted to the actually measured data input module; An illuminance coefficient analysis module for analyzing the illuminance coefficient calculated by the illuminance coefficient calculation module; And a resistance coefficient output module for outputting the friction coefficient and the roughness coefficient analyzed by the friction coefficient analysis module and the roughness coefficient analysis module.

In addition, the calculation device of the resistance coefficient using the field measurement data of the natural river according to the present invention, further comprising a dimensionless flow rate calculation module for calculating the dimensionless flow rate for the relative diving ratio of the field measurement data using a regression analysis method It is characterized by.

According to the method and apparatus for calculating the resistance coefficient using the field data of the natural river of the present invention, the friction coefficient and roughness coefficient of the natural stream flow can be derived from the field measurement data, and the friction coefficient and the roughness coefficient of the river data By analyzing and suggesting the distribution range for each type, there is an advantage that can derive the relation of resistance coefficient as a function of flow rate and friction inclination.

In addition, according to the present invention, there is an advantage that can be utilized in manual practice by deriving a dimensionless flow rate relation for the relative diving ratio.

1 is a block diagram illustrating a device for calculating a resistance coefficient using field data of a natural river according to the present invention.
2 is a flowchart illustrating a method of calculating a resistance coefficient using field data of a natural river according to the present invention.
3 is a view showing an example of the relationship analysis of the flow rate-friction coefficient of the natural river induced by the curve fitting method according to the present invention.
4 is a view showing an example of the relationship analysis of the friction inclination-friction coefficient of the natural river induced by the curve fitting method according to the present invention.
5 is an exemplary view showing an analysis of a friction coefficient according to the present invention.
6 is an exemplary view showing an analysis of parameters according to the present invention.
7 is a view showing an example of the relationship analysis of the flow rate-roughness coefficient of the natural river induced by the curve fitting method according to the present invention.
8 is a view showing an example of the relationship analysis of the friction gradient roughness coefficient of the natural river induced by the curve fitting method according to the present invention.
9 is an exemplary view showing the analysis of the roughness coefficient according to the present invention.
10 is an exemplary view showing an analysis of parameters according to the present invention.
11 is an exemplary view showing the relationship of the dimensionless flow rate to the relative diving ratio in the field data of the natural river of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a detailed description of preferred embodiments of the present invention will be given with reference to the accompanying drawings. In the following description of the present invention, detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

Embodiments in accordance with the concepts of the present invention can make various changes and have various forms, so that specific embodiments are illustrated in the drawings and described in detail in this specification or application. It is to be understood, however, that it is not intended to limit the embodiments according to the concepts of the present invention to the particular forms of disclosure, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, the terms "comprises ",or" having ", or the like, specify that there is a stated feature, number, step, operation, , Steps, operations, components, parts, or combinations thereof, as a matter of principle.

1 is a block diagram illustrating a device for calculating a resistance coefficient using field data of a natural river according to the present invention, and FIG. 2 is a flowchart illustrating a method of calculating a resistance coefficient using field data of a natural river according to the present invention.

Referring to the drawings, the device for calculating the coefficient of resistance using the actual measurement data of natural and vegetation stream 10, the measurement data input module 110, friction coefficient calculation module 120, friction coefficient analysis module 130, The illumination coefficient calculation module 140, the illumination coefficient analysis module 150, the dimensionless flow rate calculation module 160, and the resistance coefficient output module 150 may be included.

The measurement data input module 110 receives field measurement data including riverbed data consisting of sand, gravel, pebbles, and amber stones of natural rivers (S101). The bed data consists of a range of minimum and maximum values for sand, gravel, pebbles and amber stones, friction slope, median particle diameter, mean velocity and depth, and vegetation data for vegetation, shrubs and trees. It can consist of a range of minimum and maximum values for the median diameter, average velocity and depth.

Friction coefficient calculation module 120 may calculate a friction coefficient (f) for the field measurement data of the natural river input to the measurement data input module 110 (S102). The coefficient of friction coefficient can be derived from the curve fitting method of power function type, which is a function of flow rate and friction inclination, through regression analysis for sand, gravel, pebble and amber stone, respectively.

In the coefficient of friction analysis module 130, the coefficient of friction for natural rivers and the friction of natural rivers are analyzed through a box-whisker quartile method on the data of natural rivers from the coefficient of friction calculated by the coefficient of friction calculation module 120. the distribution of the intermediate characteristic in the coefficient variable _{^{(fQ 1/4 / S f}} 1/3) can be analyzed (S103).

In addition, the illuminance coefficient calculation module 140 may calculate an illuminance coefficient (n) for the field actual measurement data of the natural river input to the actual measurement data input module 110 (S104). The relation of roughness coefficient can be derived from the curve fitting method of power function type, which is a function of flow rate and friction inclination, through regression analysis for sand, gravel, pebble and amber stone, respectively.

In the roughness coefficient analysis module 150, the roughness coefficient for natural rivers and the roughness coefficient for natural rivers are analyzed through a box-whisker quartile method for the data of natural rivers from the roughness coefficient calculated by the roughness coefficient calculation module 140. the distribution of the intermediate characteristic in the variable number _{^{(fQ 1/8 / S f}} 1/6) can be analyzed (S105).

The data analyzed through the friction coefficient analysis module 130 and the roughness coefficient analysis module 150 are output through the resistance coefficient output module 170 (S106).

The box-whisker method uses a box to display statistically analyzed data, with the bottom and top of the box always positioned at the first and third quarters, with 2 / in the middle of the box. Place the median, which is the quartile. The maximum and minimum values are at the bottom and top. Such analytical methods not only facilitate the statistical analysis of many data, but also facilitate the identification of data variability.

In addition, in the dimensionless flow rate calculation module 160 of the roughness coefficient calculating device 10 of the present invention, it is possible to calculate the relationship between the dimensionless flow rate according to the relative diving ratio of the natural river stream data using the curve fitting method.

Field measurement data of natural rivers according to the present invention consisted of 1,875 stream data. These data were used to analyze the distribution of friction coefficients (f) and roughness coefficients (n) for flow rate and friction slope, and to derive relations and to derive the dimensionless flow relations for relative diving ratios.

Riverbed data are classified into sand, gravel, cobble and boulder. As shown in Table 1, these bed data and vegetation data are presented in the ranges of the minimum and maximum values of flow rate, friction slope, median diameter, average flow velocity, and depth.

[Table 1]

In the present invention, using the field actually measured data shown in Table 1, coefficient of friction (f) and friction slope of the roughness number (n) (S _f) and flow rate (Q), as well as respective parameters (fQ ^{1/4 /} S _f and performs an analysis of the ^1/3 and ^{_{nQ 1/8 / S f 1}} /6) and the relational expression of the non-dimensional flow rate for the external diving ratio _{(h / d s ~V / u} *) , respectively.

In particular, the coefficient of friction (f), roughness (n), and parameters are performed by box-whisker quartile analysis, where the quartile (%) analysis is represented by the bottom horizontal line with the minimum value of the top 1% of the subject data. , In the center of the box, the median is displayed, and above and below the top 25% and 75%, with the top horizontal line at 100%.

In addition, the following relational expression (Equation 1) is used to derive a relational expression for resistance coefficients such as friction coefficient and roughness coefficient.

[Formula 1]

인 전단속도, V는 평균유속, R_h는 동수반경, g는 중력가속도, ρ는 물의 밀도이다)
(here,

Phosphorus shear rate, V is the mean velocity, R _h is the hydraulic radius, g is the gravitational acceleration, ρ is the density of the water)

The dimensionless flow rate can be approximated by the following equation (Equation 2) at a hydraulically rough boundary without bed deformation.

[Formula 2]

Here, k _s ' ≒ 3d ₉₀ or k _s ' ≒ 6d ₅₀ can be approximated, where k _s ' is the particle roughness and d ₅₀ and d ₉₀ correspond to 50% and 90% of the weight percent of the particles. the particle diameter, R _h represents a hydraulic radius.

Dimensional flow rates can be applied to a wide range of relative depth ratios (h / d ₅₀ ) for practical purposes, which can be approximated using the following equation (Equation 3).

[Formula 3]

Moreover, Manning - in the case of streaming cluster power function equation is n = 0.064d ₅₀ ^1/6 roughness meter number with respect to the center of the particle diameter d ₅₀ (Manning-Strickler) may be used in the following relation (equation 4).

[Formula 4]

Therefore, the relational expression (Equation 2) at the hydraulically rough boundary can be used as the relational expression (Equation 5) of the relative diving ratio (h / d ₅₀ ) and the dimensionless flow rate (V / v _* ).

[Formula 5]

Experimental Example 1 Friction Coefficient of Natural River (f)

The relationship between the friction coefficient (f) is a function of the flow rate (Q) and the friction slope (S _f ) through the regression analysis for the sand, gravel, pebble and amber stone data constituting the bed material as shown in Figs. It is derived by the curve fitting of power function type.

)의 변동성을 분석한 결과이다.5 and 6 and Table 2 below show friction coefficients (f) and parameters (for natural river measurement data) by box-whisker analysis.

) Is the result of analyzing the variability of.

[Table 2]

)에 대한 분석결과를 비교할 때 평균값/중앙값과 상위(3/4)/상위(1/4)의 평균값에서 각각 2.8, 3.9 및 1.6, 2.4로 나타났다.
As a result of the box-whisker analysis in the natural river data for the coefficient of friction (f) of FIG. 4, the 179 sand data are 0.001 to 2.188, and the 992 gravel data are 0.006 to 6.121 and 651 pebble data. 0.015 to 21.462 and 53 amber stones were 0.034 to 14.592 and 1,875 to 0.001 to 21.462, respectively, and the friction coefficient (f) and the parameters (

), 2.8, 3.9, 1.6, and 2.4 were found for the mean / median and upper (3/4) and upper (1/4) mean values, respectively.

In natural rivers, friction coefficient relations were derived as power function functions as a function of flow rate and friction inclination, as shown in FIGS. 3 and 4, and the results are shown in more detail in Table 3.

[Table 3]

As shown in Table 3, the resistance coefficient relation derived from each of the four bed materials shows that the smaller the grain size, the smaller the coefficient of crystal coefficient, which is less effective in terms of statistics because of the large distribution range of repair amount. The crystal coefficient is relatively good, so it is useful to estimate the friction coefficient for preliminary investigations in the case of the planned flooding due to precipitation-runoff in the hand practice or the channel slope or friction slope. In addition, friction coefficient calculation using flow rate data is more useful than friction inclination.

Experimental Example 2 Roughness Coefficient of Natural River (n)

1,875 riverbeds of natural streams consist of sand, gravel, pebbles, and amber stones. Using these data, the roughness coefficient relation can be derived by the curve fitting method of power function type as a function of flow rate (Q) and friction slope (S _f ) through regression analysis, as shown in FIGS. 7 and 8. have.

)의 변동성을 분석한 결과이다.9 and 10 and Table 4 below show roughness coefficients (n) and parameters (for natural river data by box-whisker analysis).

) Is the result of analyzing the variability of.

[Table 4]

As shown in Table 4, the box-whisker analysis results for natural river data for roughness coefficient (n) of FIG. 9 are 0.004 to 0.151 for 179 sand data, 0.008 to 0.250 for 992 gravel data, and 651 for pebble data. The data of 0.015 to 0.327 and 53 amber stones were 0.023 to 0.444 and 1,875 data of 0.004 to 0.444 respectively.

)에 대한 분석결과를 비교할 때, 평균값/중앙값과 상위(3/4)/상위(1/4)의 평균값에서 각각 1.3, 1.9 및 1.6, 4.3으로 나타났다.
Roughness coefficient (n) and parameters (

), 1.3, 1.9, 1.6, and 4.3 were found in the mean value, the median value, and the upper value (3/4) and the upper value (1/4), respectively.

In natural rivers, roughness coefficient relations were derived as power function functions as a function of flow rate and friction inclination, as shown in FIGS. 7 and 8, and the results are shown in detail in Table 5 below.

[Table 5]

As shown in Table 5, the relationship between the roughness coefficients derived from the four bed materials is similar to that of the friction coefficient. This is because the distribution of hydraulic volume is considerably large and the measured roughness coefficient is smaller than that of friction coefficient, so the coefficient of determination is slightly lower and is less effective in terms of statistics. It may be useful to calculate roughness coefficients for preliminary investigations in the course of determining water slope or friction slope.

In addition, the calculation of roughness coefficient by the relational coefficient of roughness coefficient can be similarly obtained by using either flow rate data or friction inclination data.

[Relationship of Dimensionless Flow Rate by Relative Diving Cost]

11 is an exemplary diagram derived from the curve fitting method of the relationship between the dimensionless flow rate (V / v _* ) according to the relative diving ratio (h / d ₅₀ ) of each stream data of the natural river.

로 유도되었고, 또한, 자연하천에서 상대 잠수비(h/d₅₀)에 대한 무차원 유속(V/v_*)과의 관계식은 실용 목적 및 수리학적 거친 경계인 식보다 우수한 값을 갖는

로 유도되었다.
As shown, the Manning-Strickler relation in natural streams has an intercept of 5.4 with the intercept being slightly larger than 5, and the slope being 1/10 smaller than 1/6.

In addition, the relationship between the dimensionless flow rate (V / v _* ) for the relative diving ratio (h / d ₅₀ ) in natural streams has a better value than the equation for practical purpose and hydraulic rough boundary.

Was induced.

[Experiment result]

The data of natural rivers consisting of sand, gravel, pebbles and amber stones used in the present invention were analyzed to have resistance coefficient values as shown in Table 6.

TABLE 6

As shown in Table 6, the coefficients of friction for natural stream data are 0.001 to 2.188 for 179 sand data, 0.006 to 6.121 for 992 gravel data and 0.015 to 21.462 for 651 pebble data and 0.034 to 14.592 for 53 amber stone data. A total of 1,875 data showed 0.001 to 21.462, and roughness coefficients ranged from 0.004 to 0.151 for 179 sand data and 0.008 to 0.250 for 992 gravel data and 0.015 to 0.327 for 651 pebble data and 0.023 to 0.444 for 53 amber stones. , 1,875 data shows 0.004-0.444.

In the box-whisker analysis, the coefficient of friction is 0.061 to 0.209 for the top 25% and 75% of the sand data, 0.061 to 0.209 for the gravel data, 0.071 to 0.299 for the pebble data, 0.128 to 0.632 for the amber stone, and natural river data. The average of the whole was 0.08 to 0.32. In addition, the roughness coefficient was 0.025 to 0.042 in the sand data, 0.029 to 0.051 in the gravel data, 0.032 to 0.057 in the pebble data, 0.044 to 0.101 in the amber stone, and 0.03 to 0.06.

The results of the analysis of friction coefficient, roughness coefficient and average / median and upper (3/4) and upper (1/4) of the parameters are shown in Table 7 below.

[Table 7]

As shown in Table 7, the mean / median and upper (3/4) / high (1/4) mean values of friction coefficients and parameters were 2.8, 3.9 and 1.6 2.4, and the mean values of roughness coefficients and parameters / Median and upper (3/4) / high (1/4) mean values were 1.3, 1.9, 1.6, and 4.3.

The relationship between friction coefficient and roughness coefficient as a function of flow rate and friction slope can be used to roughly calculate the coefficient of resistance such as preliminary investigation of planned flood and friction slope.

As described above, according to the present invention, it is possible to derive the resistance coefficient of the stream flow through the field measurement data of the natural river, and also to analyze the flow data and the resistance coefficient and present the distribution range for each type to calculate the flow rate and friction inclination. Through the relationship between friction coefficient and roughness coefficient as a function, it can be used to roughly calculate resistance coefficients such as preliminary investigations in which planned flooding and friction inclination have been determined.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. will be. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

10: roughness coefficient calculation device 110: measured data input module
120: coefficient of friction calculation module 130: coefficient of friction analysis module
140: roughness coefficient calculation module 150: roughness coefficient analysis module
160: dimensionless flow rate calculation module 170: roughness coefficient output module

Claims (16)

In the calculation method of the resistance coefficient using the actual field data of the natural river,
The first step of inputting the riverbed data consisting of the minimum value and the maximum value range for the flow rate, friction slope, median particle size, average flow rate, depth for the sand, gravel, pebble and amber stones which are actual measurement data of the natural river ;
A second step of calculating, by the coefficient of friction calculation module, a coefficient of friction for natural rivers from the field measurement data inputted through the input module;
A third step of analyzing, by the coefficient of friction analysis module, a coefficient of friction of the natural river calculated in the second step;
A fourth step of the illuminance coefficient calculating module calculating the illuminance coefficient for the natural river from the field measurement data inputted through the input module;
A fifth step of analyzing the roughness coefficient of the natural river calculated in the fourth step by the roughness coefficient analyzing module;
And a sixth step of outputting each friction coefficient and roughness coefficient analyzed by the resistance coefficient output module.
Friction coefficient calculation in the second step,
F _bou = 2.56Q ^-0.56 and f _bou = 51.6S _f ^{1.06 for} amber, f _cob = 0.68Q ^-0.41 and f _cob = 4.48S _f ^0.58 for cobblestone, f _gra = 0.31Q ^-0.28 and gravel If f _san = 0.16S _f ^-0.19 ,
In the fourth step, the roughness coefficient is calculated,
For amber, use the relationship n _bou = 0.41Q ^-0.20 and n _bou = 0.59S _f ^0.45 , for pebble n _cob = 0.07Q ^-0.14 and n _cob = 0.17S _f ^0.23 ,
In the third and fifth stages, the resistance coefficients are calculated by using the field measurement data, characterized in that the minimum, maximum, and average values of the coefficients of friction and roughness calculated in the second and fourth stages are analyzed, respectively. Way.
(Where Q is the flow rate and S _f is the friction slope)
delete delete The method of claim 1,
In the second step, the friction coefficient of the natural stream is calculated by a power-of-function curve bonding method, which is a function of flow rate and friction inclination, respectively, through the regression analysis on the riverbed data. Method of calculating coefficients.
The method of claim 1,
In the third step, the coefficient of friction of the natural river is calculated using the box-whisker (quartile) quartile method.
The method of claim 5, wherein
The Box-Whisker Quartile Analysis method uses a parameter (fQ ^1/4 / S _f ^1/3 ) to calculate a resistance coefficient using field measurement data.
(Where f is friction coefficient, Q is flow rate (㎥ / s), and S _f is friction inclination)
The method of claim 1,
In the fourth step, the roughness coefficient of the natural stream is calculated by a power-of-function curve joint method, which is a function of flow rate and friction inclination, respectively, through regression analysis on the riverbed data. Method of calculating coefficients.
The method of claim 1,
In the fifth step, the roughness coefficient of the natural river is analyzed using a box-whisker quartile method.
The method of claim 8,
The Box-Whisker Quartile Analysis method uses a parameter (nQ ^1/8 / S _f ^1/6 ) to calculate a resistance coefficient using field measurement data.
(Where n is roughness coefficient, Q is flow rate (㎥ / s), and S _f is friction inclination)
The method of claim 1,
And after the fifth step, calculates a dimensionless flow rate for the relative diving ratio of the field measurement data using curve fitting.
In calculating device of resistance coefficient using field measurement data of natural river,
Input field measurement data including riverbed data consisting of the minimum and maximum ranges for the flow rate, friction slope, median particle size, average velocity, and depth for sand, gravel, pebble, and amber stones, which are field measurement data of the natural river. Measured data input module;
A coefficient of friction calculation module for calculating a coefficient of friction for the field measurement data input to the measurement data input module;
A coefficient of friction analysis module for analyzing a coefficient of friction calculated through the coefficient of friction calculation module;
An illuminance coefficient calculation module for calculating an illuminance coefficient for the field measurement data inputted to the actually measured data input module;
An illuminance coefficient analysis module for analyzing the illuminance coefficient calculated by the illuminance coefficient calculation module; And
And a resistance coefficient output module configured to output the friction coefficient and the roughness coefficient analyzed by the friction coefficient analysis module and the roughness coefficient analysis module.
The friction coefficient calculation module,
F _bou = 2.56Q ^-0.56 and f _bou = 51.6S _f ^{1.06 for} amber, f _cob = 0.68Q ^-0.41 and f _cob = 4.48S _f ^0.58 for cobblestone, f _gra = 0.31Q ^-0.28 and gravel In the case of, the coefficient of friction is calculated using the relation of f _san = 0.16S _f ^-0.19 ,
The illuminance coefficient calculation module,
For coarse stones, roughness coefficients are calculated using the relations n _bou = 0.41Q ^-0.20 and n _bou = 0.59S _f ^0.45 , and for pebble n _cob = 0.07Q ^-0.14 and n _cob = 0.17S _f ^0.23
The friction coefficient analysis module and roughness coefficient analysis module is a device for calculating the coefficient of resistance using the actual measurement data, characterized in that for analyzing the minimum, maximum and average value for the calculated friction coefficient and roughness coefficient, respectively.
(Where Q is the flow rate and S _f is the friction slope)
delete The method of claim 11,
The friction coefficient calculation module calculates the friction coefficient of the natural river by a curve-joining method of the power function type, which is a function of flow rate and friction inclination, respectively, through regression analysis on the riverbed data. Counting device for coefficients.
The method of claim 11,
The roughness coefficient calculation module calculates roughness coefficients of natural rivers by a curve-joining method of power function type, which functions as a function of flow rate and friction inclination, respectively, through regression analysis on the riverbed data. Counting device for coefficients.
The method of claim 11,
The friction coefficient analysis module and roughness coefficient analysis module uses a box-whisker quartile analysis method for the friction coefficient and the roughness coefficient calculated through the friction coefficient calculation module and the roughness coefficient calculation module, respectively,
The box-whisker quartile method for friction coefficients uses a parameter (fQ ^1/4 / S _f ^1/3 ), and the box-whisker quartile method for roughness coefficients uses a parameter (nQ ^1/8 / S _f ^1/6 ) A device for calculating the coefficient of resistance using field measurement data, characterized in that using.
The method of claim 11,
And a dimensionless flow rate calculation module for calculating a dimensionless flow rate for the relative diving ratio of the field measurement data using a regression analysis method.

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