Method and device for predicting comprehensive resistance coefficient of river channel

Abstract

The invention relates to the technical field of hydraulic engineering, in particular to a riverway comprehensive resistance coefficient prediction method and device, and the method comprises the steps: obtaining the actual water flow, vegetation information and sediment data of a target region in a riverway, and calculating a vegetation blocking coefficient, a vegetation interface, a riverbed and a riverbank resistance coefficient; obtaining at least one of the interface area of the vegetation group and the water body, the interface area of the riverbed and the water body and the interface area of the river bank and the water body under the unit river channel length; and according to the vegetation blocking coefficient, the vegetation interface, the riverbed and bank resistance coefficient and at least one interface area, predicting a river comprehensive resistance coefficient of the target area. The method can comprehensively consider the influence of different factors on the river resistance, effectively improves the accuracy of the prediction result of the comprehensive resistance coefficient of the river, quantitatively analyzes the contribution of different factors to the change of the river resistance coefficient and the water level flow relationship according to the prediction result, and provides a basis for river and channel management.

Description

Technical Field

[0001] The present application relates to the technical field of water conservancy engineering, and in particular to a method and device for predicting the comprehensive resistance coefficient of a river channel. Background Art

[0002] In related technologies, studies have shown that after the operation of the reservoir, the low-water level of the downstream river has dropped significantly, while the flood level of the downstream river has remained basically unchanged or even increased. Some studies on the driving causes of the change in the water level of the downstream of the Three Gorges Reservoir believe that the scouring and silting changes (scouring and cutting) of the river channel are the main cause of the decline in the low-water level of the downstream river, and the factors that cause the slight rise in the flood level of the downstream river are mainly the increase in river resistance caused by the coarsening of the bed sand and the coverage of shore vegetation. And some studies on the causes of the change in the relationship between the water level and flow in the middle reaches of the Yangtze River are mainly based on qualitative analysis, and only a small number of literature quantifies the specific effects of some factors (such as coarsening of the bed sand or scouring and silting changes) on the change in the water level of the downstream river. For example, the calculation of the resistance coefficient in the water-sediment model of the downstream of the Three Gorges Reservoir usually mainly adopts empirical methods, including inversion method, curve method and table lookup method, and the obtained resistance coefficient is usually the spatiotemporal average value of the entire river.

[0003] However, the research on river resistance coefficient in related technologies is mostly based on experience. When faced with situations such as the downstream riverbed of the river channel is in a state of continuous scouring or the water and sand conditions in the river channel are complex, it is impossible to effectively determine the comprehensive river resistance coefficient and it is difficult to distinguish the specific contribution of changes in various influencing factors to changes in the river resistance coefficient and the water level-flow relationship. How to comprehensively consider the influencing factors of river resistance to calculate an effective comprehensive river resistance coefficient and analyze its impact on changes in the water level-flow relationship needs to be solved urgently. Summary of the invention

[0004] The present application provides a method and device for predicting the comprehensive resistance coefficient of a river channel, in order to solve the problem that the research on the river channel resistance coefficient in the related art is mainly based on experience. When faced with situations such as the downstream riverbed of the river channel is in a state of continuous scouring or the water and sand conditions in the river channel are complex, it is impossible to effectively determine the comprehensive resistance coefficient of the river channel and it is difficult to distinguish the specific contribution of the changes in various influencing factors to the changes in the river channel resistance coefficient and the relationship between water level and flow. How to comprehensively consider the influencing factors of the river channel resistance to calculate the effective comprehensive resistance coefficient of the river channel, and analyze its influence on the changes in the relationship between water level and flow, etc.

[0005] The first aspect of the present application provides a method for predicting the comprehensive resistance coefficient of a river channel, comprising the following steps: obtaining actual water flow, vegetation information and sediment data in a target area in a river channel to calculate a vegetation blocking coefficient, a vegetation interface, and a riverbed and riverbank resistance coefficient; obtaining at least one of the interface areas of a vegetation group and a water body, a riverbed and a water body, and a riverbank and a water body per unit river channel length; and predicting the comprehensive resistance coefficient of the river channel in the target area based on the vegetation blocking coefficient, the vegetation interface, the riverbed and riverbank resistance coefficient and the at least one interface area.

[0006] Optionally, in one embodiment of the present application, the calculation formula of the comprehensive resistance coefficient of the river channel is:

[0007]

[0008] Wherein, n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively. v , C b and C B are the resistance coefficients of the vegetation interface, the riverbed and the riverbank, respectively, v , L b and L B They are respectively the interface area between the vegetation community and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body per unit river channel length.

[0009] Optionally, in one embodiment of the present application, obtaining actual water flow, vegetation information and sediment data of a target area in a river channel includes: collecting basic parameters of the target area, the basic parameters including at least one of river channel length, river channel width and river channel gradient; obtaining actual water flow, vegetation information and sediment data of the target area according to the basic parameters.

[0010] Optionally, in one embodiment of the present application, the actual water flow includes the water level and flow velocity along the river channel, the vegetation information includes at least one of vegetation height, vegetation weight, frontal area, and blocking coefficient, and the sediment data includes bed sediment grading and suspended sediment concentration.

[0011] The second aspect of the present application provides a device for predicting the comprehensive resistance coefficient of a river channel, including: a calculation module for obtaining actual water flow, vegetation information and sediment data of a target area in a river channel to calculate a vegetation blocking coefficient, a vegetation interface, and a riverbed and riverbank resistance coefficient; an acquisition module for obtaining at least one of the interface areas of a vegetation group and a water body, a riverbed and a water body, and a riverbank and a water body per unit river channel length; and a prediction module for predicting the comprehensive resistance coefficient of the river channel in a target area based on the vegetation blocking coefficient, the vegetation interface, the riverbed and riverbank resistance coefficient and the at least one interface area.

[0012] Optionally, in one embodiment of the present application, the calculation formula of the comprehensive resistance coefficient of the river channel is:

[0013]

[0014] Where n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, and B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively, C v , C b and C B are the resistance coefficients of the vegetation interface, the riverbed and the riverbank, respectively, v , L b and L B They are respectively the interface area between the vegetation community and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body per unit river channel length.

[0015] Optionally, in one embodiment of the present application, the calculation module includes: a collection unit for collecting basic parameters of the target area, wherein the basic parameters include at least one of river length, river width and river gradient; an acquisition unit for acquiring actual water flow, vegetation information and sediment data of the target area based on the basic parameters.

[0016] Optionally, in one embodiment of the present application, the actual water flow includes the water level and flow velocity along the river channel, the vegetation information includes at least one of vegetation height, vegetation weight, frontal area, and blocking coefficient, and the sediment data includes bed sediment grading and suspended sediment concentration.

[0017] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for predicting the comprehensive resistance coefficient of a river channel as described in the above embodiment.

[0018] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned method for predicting the comprehensive resistance coefficient of a river channel.

[0019] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned method for predicting the comprehensive resistance coefficient of a river channel.

[0020] The embodiment of the present application can calculate the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient according to the actual water flow, vegetation information and sediment data of the target area in the river channel, and then predict the comprehensive river channel resistance coefficient of the target area by combining at least one of the interface area between the vegetation group and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body under the unit river channel length. In this way, the influence of factors such as bed sand coarsening, river channel scouring and cutting, and vegetation coverage on river channel resistance is comprehensively considered, and the accuracy of the prediction results of the comprehensive river channel resistance coefficient is effectively improved. The contribution of different factors to the river channel resistance coefficient and the change of the water level flow relationship can also be quantitatively analyzed according to the prediction results, so as to analyze the changes in the measured water level flow relationship, the changes in bed sand grading, the changes in river channel scouring and silting, and the changes in the deep line, and provide a basis for river and waterway management. This solves the problem that the research on river resistance coefficient in related technologies is mainly based on experience. When faced with situations such as the downstream riverbed of the river is in a state of continuous scouring or the water and sand conditions in the river are complex, it is impossible to effectively determine the comprehensive river resistance coefficient and it is difficult to distinguish the specific contribution of changes in various influencing factors to changes in the river resistance coefficient and the water level-flow relationship. It also solves the problem of how to comprehensively consider the influencing factors of river resistance to calculate the effective comprehensive river resistance coefficient and analyze its impact on changes in the water level-flow relationship.

[0021] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 A schematic diagram of a framework of a river channel comprehensive resistance coefficient prediction system according to an embodiment of the present application;

[0024] Figure 2 A flow chart of a method for predicting a comprehensive resistance coefficient of a river channel provided according to an embodiment of the present application;

[0025] Figure 3 This is a flow chart of a method for predicting a comprehensive resistance coefficient of a river channel according to an embodiment of the present application;

[0026] Figure 4 This is a schematic diagram of a measured river section according to an embodiment of the present application;

[0027] Figure 5 A schematic diagram showing a comparison between a field observed value and a model calculated value of a drag coefficient according to an embodiment of the present application;

[0028] Figure 6 A generalized map of the geographical location of a hydrological station and a measured cross-sectional map of an embodiment of the present application;

[0029] Figure 7 A schematic diagram of the calculation results of the water level-flow relationship of a hydrological station according to an embodiment of the present application;

[0030] Figure 8 This is a schematic diagram of the measured results of the water level-flow relationship of a hydrological station according to one embodiment of the present application;

[0031] Fig. 9 It is a schematic diagram of the structure of a device for predicting the comprehensive resistance coefficient of a river channel provided in an embodiment of the present application;

[0032] Fig.10 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application.

[0033] Reference numerals:

[0034] 10-River channel comprehensive resistance coefficient prediction device: 100-calculation module, 200-acquisition module and 300-prediction module; 1001-memory, 1002-processor and 1003-communication interface. DETAILED DESCRIPTION

[0035] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0036] The following describes the method and device for predicting the comprehensive resistance coefficient of a river channel in an embodiment of the present application with reference to the accompanying drawings. In view of the fact that the research on the resistance coefficient of a river channel in the related technologies mentioned in the above background technology is mostly based on experience, when the downstream riverbed of the river channel is in a state of continuous scouring or the water and sand conditions in the river channel are complex, it is impossible to effectively determine the comprehensive resistance coefficient of the river channel and it is difficult to distinguish the specific contribution of the changes in various influencing factors to the changes in the river channel resistance coefficient and the water level flow relationship. How to comprehensively consider the influencing factors of the river channel resistance to calculate an effective comprehensive resistance coefficient of the river channel and analyze its influence on the changes in the water level flow relationship, the present application provides a method for predicting the comprehensive resistance coefficient of a river channel, in which the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient can be calculated based on the actual water flow, vegetation information and sediment data of the target area in the river channel, and then the comprehensive resistance coefficient of the river channel in the target area is predicted by combining at least one of the interface area between the vegetation group and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body under the unit river channel length. Thus, it is possible to comprehensively consider the influence of factors such as bed sand coarsening, river scouring and incision, and vegetation coverage on river resistance, effectively improve the accuracy of the prediction results of the comprehensive resistance coefficient of the river, and quantitatively analyze the contribution of different factors to the river resistance coefficient and the change of the water level-flow relationship based on the prediction results, so as to analyze the changes in the measured water level-flow relationship, bed sand grading changes, river scouring and silting, and deep-sea line changes, and provide a basis for river and waterway management. Thus, it solves the problem that the research on the river resistance coefficient in related technologies is mostly based on experience. When faced with the situation that the downstream riverbed of the river is in a state of continuous scouring or the water and sand conditions in the river are complex, it is impossible to effectively determine the comprehensive resistance coefficient of the river and it is difficult to distinguish the specific contribution of the changes of various influencing factors to the changes in the river resistance coefficient and the water level-flow relationship. How to comprehensively consider the influencing factors of the river resistance to calculate the effective comprehensive resistance coefficient of the river, and analyze its influence on the change of the water level-flow relationship.

[0037] Before explaining the method for predicting the comprehensive resistance coefficient of a river channel according to an embodiment of the present application, the framework of the system for predicting the comprehensive resistance coefficient of a river channel according to an embodiment of the present application is first explained.

[0038] Figure 1 This is a schematic diagram of the framework of a river channel comprehensive resistance coefficient prediction system according to an embodiment of the present application. Figure 1 As shown, the river channel comprehensive resistance coefficient prediction system in the embodiment of the present application mainly includes but is not limited to: a data acquisition module M1, a data processing module M2 and a prediction result module M3.

[0039] Among them, the data acquisition module M1 is used to obtain basic information of the river channel and water flow, vegetation and sediment observation data, wherein the basic information of the river channel includes but is not limited to information such as the length, width and gradient of the river channel, the water flow monitoring data includes data such as water depth and average flow velocity of the cross section, the vegetation monitoring data includes but is not limited to data such as the interface area between the vegetation group and the water body and the projected area of ​​the vegetation area occupying the water body, and the sediment monitoring data includes but is not limited to data such as the median particle size of the bed sand and the density of the sediment particles.

[0040] The data processing module M2 processes the acquired data and calculates the vegetation interface resistance coefficient, riverbed resistance coefficient, riverbank resistance coefficient, vegetation blocking coefficient, etc.

[0041] The prediction result module M3 predicts the comprehensive resistance coefficient of the river channel based on the results of the data processing module, and then predicts the contribution of various factors, including but not limited to changes in vegetation coverage, changes in bed sand particle size, and changes in river channel morphology. It can also further analyze changes in the measured water level-discharge relationship, changes in bed sand gradation, changes in river channel scouring and silting, and changes in the deep channel line, providing a basis for river and waterway management.

[0042] Specifically, Figure 2 A flow chart of a method for predicting the comprehensive resistance coefficient of a river provided in an embodiment of the present application.

[0043] like Figure 2 As shown in FIG. 1 , the method for predicting the comprehensive resistance coefficient of a river channel includes the following steps:

[0044] In step S201, the actual water flow, vegetation information and sediment data of the target area in the river channel are obtained to calculate the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient.

[0045] In some embodiments, the water level-flow relationship is an important part of river research and has important application value for shipping planning and management, water conservancy project construction, and ecological protection. When a large reservoir is put into operation, the downstream water and sediment flow process will change significantly, and the clean water scouring will cause the riverbed to coarsen and adjust its shape, and the water level-flow relationship of the downstream river section will change accordingly.

[0046] Based on this, considering that multiple factors such as coarsening of riverbed sand, river scouring and incision, and vegetation coverage have a certain impact on the resistance coefficient, this application can, but is not limited to, obtaining actual water flow information, vegetation information, and some sediment data in the target area of ​​the river channel as the main data, so as to calculate the corresponding vegetation blocking coefficient, vegetation interface resistance coefficient, riverbed resistance coefficient, and riverbank resistance coefficient.

[0047] The target area in the river channel can be understood as the river channel area where the comprehensive resistance coefficient needs to be calculated. After calculating the resistance coefficients such as the vegetation blocking coefficient, the vegetation interface resistance coefficient, the riverbed resistance coefficient and the riverbank resistance coefficient, the embodiment of the present application can use these data to calculate the subsequent river channel resistance coefficient.

[0048] For example, the vegetation blocking coefficient can be determined by the cross-sectional area of ​​the water flow and the projected area of ​​the vegetation area on the water body, which can be expressed as follows:

[0049]

[0050] Among them, B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively.

[0051] Furthermore, the vegetation interface resistance coefficient, riverbed resistance coefficient and riverbank resistance coefficient C v , C b and V C It can be converted to Manning's drag coefficient m:

[0052]

[0053] Among them, C i (i=v,b,B) are the vegetation interface resistance coefficient, riverbed resistance coefficient and riverbank resistance coefficient respectively, m is the Manning resistance coefficient, g is the acceleration due to gravity, and H is the water depth.

[0054] Specifically, the vegetation interface resistance coefficient can be determined based on existing data to be in the range of 0.005 to 0.13. For example, in autumn when the vegetation is dense, the value can be 0.079. It can also be obtained by simulation experiments conducted by professionals in this field based on actual conditions. The embodiments of this application are only illustrative and not specifically limited.

[0055] Riverbed resistance coefficient C b In addition to formula (2), it can also be expressed as:

[0056]

[0057] Among them, D 50 is the median particle size of bed sediment.

[0058] Riverbank resistance coefficient C BThe empirical formula of the bed surface can be used for estimation. If there is no data, the river bank resistance coefficient value recommended by the sediment manual and other related data can also be used. For example, in the embodiment of the present application, the river bank resistance coefficient can be taken as a constant of 0.020 to 0.023, or the river bank resistance coefficient can be calculated by formula (2), which can be expressed as follows:

[0059]

[0060] Where m is the Manning drag coefficient, g is the acceleration due to gravity, H is the water depth, c B is the river bank resistance coefficient.

[0061] Optionally, in one embodiment of the present application, obtaining the actual water flow, vegetation information and sediment data of the target area in the river channel includes: collecting basic parameters of the target area, the basic parameters including at least one of the river channel length, river channel width and river channel gradient; obtaining the actual water flow, vegetation information and sediment data of the target area according to the basic parameters. The actual water flow includes the water level and water flow velocity along the river channel, the vegetation information includes at least one of the vegetation height, vegetation weight, water frontage area and barrier coefficient, and the sediment data includes bed sediment gradation and suspended sediment concentration.

[0062] Based on the relevant descriptions of other embodiments, it can be understood that the present application can calculate the relevant resistance coefficient by obtaining the actual water flow, vegetation information and sediment data of the target area in the river channel, and then calculate the comprehensive resistance coefficient of the river channel.

[0063] Specifically, the embodiment of the present application needs to first obtain the basic parameters of the target area in the river channel, including but not limited to at least one of the river channel length, river channel width and river channel gradient (the ratio of the elevation difference between the upstream and downstream of the river channel to the river channel length (or horizontal distance)).

[0064] Then, the acquired river channel length, river channel width or river channel gradient is used to obtain the actual water flow, vegetation information and sediment data of the target area. The actual water flow includes but is not limited to the water level and flow velocity along the river channel, the vegetation information includes but is not limited to at least one of the vegetation height, vegetation weight, water frontage area and barrier coefficient, and the sediment data includes but is not limited to the bed sediment gradation, suspended sediment concentration, etc.

[0065] Step S202, obtaining at least one of the interface area of ​​the vegetation group and the water body, the interface area of ​​the riverbed and the water body, and the interface area of ​​the river bank and the water body per unit river channel length.

[0066] It can be understood that the resistance coefficients such as the vegetation interface resistance coefficient, riverbed resistance coefficient and riverbank resistance coefficient obtained above are all resistance coefficients per unit area.

[0067] During the actual implementation process, in the target area of ​​the river channel, the size of the vegetation, the size of the riverbed and the size of the riverbank may have different resistances. Therefore, before calculating the comprehensive resistance coefficient of the river channel in the target area of ​​the river channel, the embodiment of the present application also needs to obtain at least one of the interface areas of the vegetation group and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body per unit river channel length, and then combine them with resistance coefficients such as the vegetation interface resistance coefficient, the riverbed resistance coefficient and the riverbank resistance coefficient, so as to calculate the comprehensive resistance coefficient of the river channel.

[0068] Step S203, predicting the comprehensive resistance coefficient of the river channel in the target area according to the vegetation blocking coefficient, the vegetation interface, the riverbed and riverbank resistance coefficients and at least one interface area. The calculation formula of the comprehensive resistance coefficient of the river channel is:

[0069]

[0070] Among them, n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, and B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively, C v , C b and C B are the resistance coefficients of the vegetation interface, riverbed and riverbank, L v , L b and L B They are the interface area between vegetation and water body, the interface area between riverbed and water body, and the interface area between riverbank and water body per unit river length.

[0071] Based on the relevant descriptions of other embodiments, it can be understood that the present application can comprehensively consider the impact of multiple factors such as coarsening of river bed sand, river scouring and incision, and vegetation coverage on the resistance coefficient, that is, combining the vegetation blocking coefficient, vegetation interface resistance coefficient, riverbed resistance coefficient, riverbank resistance coefficient and at least one interface area to comprehensively predict the comprehensive resistance coefficient of the river in the target area.

[0072] Specifically, the embodiment of the present application can distinguish three types of resistance, namely vegetation, riverbed, and riverbank, establish a comprehensive resistance coefficient model based on the momentum equation, and then consider the influence of three factors, namely, bed sand coarsening, river channel scouring and incision, and vegetation coverage, so as to obtain the final calculation formula for the comprehensive resistance coefficient of the river channel. The process can be expressed as follows:

[0073] In natural rivers, the one-dimensional Saint-Venant equations can generally be used to solve the water level and flow problems. In the case of a one-dimensional constant uniform flow without side inflow, the inertia term and the additional gradient term in the Saint-Venant equation can be ignored. At this time, the cross-sectional flow Q formula of the stable uniform flow in the river can be expressed as:

[0074]

[0075] Among them, A is the cross-sectional water area, R is the hydraulic radius of the river section, S is the river gradient, and m is the Manning coefficient. The momentum equation of the vegetation-free area per unit river length can be expressed as:

[0076] 0 = ρgS(AA′)-τ v L v -τ b L b -τ B L B (6)

[0077] Where ρ is the water density, g is the gravitational acceleration, A and A′ are the cross-sectional area of ​​water and the projection area of ​​vegetation area on the water body, respectively. v , L b and L B are the interface area between vegetation and water, the interface area between riverbed and water, and the interface area between riverbank and water per unit river channel length, respectively. v , τ b and τ B They are the shear stress at the interface between vegetation and non-vegetated areas, and the shear stress of the riverbed and riverbank in non-vegetated areas. The shear stress can be expressed as:

[0078]

[0079] Among them, τ i is the shear stress in the specified area, C i is the resistance coefficient of the specified area, and U0 is the average flow velocity of the section in the non-vegetated area.

[0080] Combining formulas (7) and (8), we can get the flow velocity U0 in the vegetation-free area, which can be expressed as follows:

[0081]

[0082] Among them, C v , C b and C B are the resistance coefficients of vegetation interface, riverbed and riverbank respectively.

[0083] The average flow velocity U of the river section can be expressed as:

[0084] U=U0(1-B x )+U v B x (9)

[0085] Among them, B xis the vegetation blocking coefficient, Due to the flow velocity U in the vegetation area v Much smaller than the velocity U in the non-vegetated area o , and in general B x <(1-B x ), so the average flow velocity U of the river section can be simplified as:

[0086] U≈U0(1-B x ) (10)

[0087] Combining the previously calculated vegetation blocking coefficient, vegetation interface resistance coefficient, riverbed resistance coefficient, riverbank resistance coefficient and at least one interface area, the final calculation formula for the comprehensive resistance coefficient of the river channel can be obtained, which can be expressed as:

[0088]

[0089] Among them, n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, and B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively, C v , C b and C B are the resistance coefficients of the vegetation interface, riverbed and riverbank, L v , L b and L B They are the interface area between vegetation and water body, the interface area between riverbed and water body, and the interface area between riverbank and water body per unit river channel length.

[0090] Additionally, the embodiments of the present application also take into account that in natural rivers, the factors that affect the resistance coefficient and the water level-flow relationship are intertwined. Therefore, the embodiments of the present application may, but are not limited to, adopt the idea of ​​separating variables, and assume that a certain factor has changed in the analysis, thereby quantitatively generalizing the contribution of the three factors to the changes in the resistance coefficient and the water level-flow relationship, and then further analyze the changes in the measured water level-flow relationship, bed sand grading, river scouring and siltation, and deep-sea line changes in combination with the prediction results, to provide a basis for river and waterway management.

[0091] For example, the embodiment of the present application may assume that the function under the action of multiple factors can be expressed as F=f(X1, X2, X3, ..) using Taylor series expansion and ignoring high-order small quantities, then the increment ΔF of the dependent variable can be approximated as the sum of the increments caused by the individual changes of each factor. Therefore, the contribution of each factor in formula (11) can be calculated as follows:

[0092]

[0093]

[0094] Among them, F is the dependent variable, X1, X2, and X3 represent various factors, such as vegetation cover change L v and B x , bed sand particle size change D 50 、Changes in river channel morphology B and L b wait.

[0095] The present application is described in detail below with two specific embodiments.

[0096] Figure 3 This is a flow chart of a method for predicting the comprehensive resistance coefficient of a river channel according to an embodiment of the present application. Figure 3 As shown:

[0097] First, obtain the basic parameters of the target area, such as river length, width, and river gradient;

[0098] Next, obtain field observation data of the target area in the river at different time periods, such as water flow, vegetation and sediment parameters in the river;

[0099] Then, according to the water flow, vegetation and sediment parameters in the river channel, the resistance coefficients of the vegetation interface, riverbed and riverbank are calculated, and the interface area of ​​the vegetation group and the water body, the interface area of ​​the riverbed and the water body, the interface area of ​​the riverbank and the water body and the vegetation blocking coefficient per unit river channel length are obtained;

[0100] Finally, the comprehensive resistance coefficient of the river channel is calculated by combining the obtained vegetation interface, riverbed, riverbank resistance coefficient, vegetation blocking coefficient, and the interface area between vegetation group and water body, the interface area between riverbed and water body, and the interface area between riverbank and water body.

[0101] Additionally, the inputs are fed into the result prediction module, which can predict the contribution of each factor and analyze changes in the measured water level-discharge relationship, bed sediment grading, river channel scouring and siltation, and deep-sea line changes, providing a basis for river and waterway management.

[0102] Embodiment 1:

[0103] The present application embodiment selects a field observation experiment based on an artificially excavated river channel. Figure 4 This is a schematic diagram of a measured river section according to an embodiment of the present application. Figure 4 As shown in the figure, the river is 850m long, 0.5-7.0m wide, and has a gradient range of 0.001-0.002. The flow, vegetation, and sediment parameters in the river were observed at five typical time periods, where the flow parameters include the water level and flow velocity along the river, the vegetation parameters include vegetation height, vegetation weight, frontage area, and barrier coefficient, and the sediment parameters include bed sediment gradation and suspended sediment concentration.

[0104] Assuming that the water flow in the river is a constant uniform flow, n (called the measured value) is obtained by back-calculation based on the measured water flow, cross-sectional parameters and the Manning formula.

[0105] Figure 5 This is a schematic diagram comparing the field observation value and the model calculation value of the resistance coefficient. To facilitate the model calculation, the measured section is simplified to Figure 4 From the figure, it can be seen that the results calculated by the river channel comprehensive resistance coefficient prediction method in the embodiment of the present application are basically consistent with the measured results.

[0106] Embodiment 2:

[0107] Figure 6 This is a generalized map of the geographical location of a hydrological station and a measured cross-sectional map of an embodiment of the present application. Figure 6 As shown, the present embodiment takes the Shashi section of the Jingjiang River as the main area ( Figure 6 a), collected data on water level, flow, bed sediment gradation and other aspects of the Shashi hydrological station in 2003, 2013 and 2016 (data from the Hydrological Bureau of the Yangtze River Water Conservancy Commission), combined with relevant literature, first analyzed the changes in the measured water level-flow relationship, bed sediment gradation, channel scouring and siltation, and deep-sea line changes, and further applied the comprehensive resistance coefficient model to explore the contribution of bed sediment coarsening, channel scouring and incision, and vegetation cover to the changes in the water level-flow relationship after reservoir operation.

[0108] Table 1 is a design table of eight typical operating condition parameter values ​​for an embodiment of the present application, as shown below:

[0109] Table 1

[0110]

[0111] Among them, "B" is the basic working condition, indicating no coarsening, no scouring, and no vegetation; "A" indicates bed sand coarsening; "E" indicates river channel scouring and incision; "V" indicates vegetation cover, the river channel scour depth a is the scour value relative to working condition B, and "-" indicates no vegetation growth.

[0112] Different combinations indicate comprehensive consideration of multiple factors, such as "AE" indicates that the working condition includes the effects of bed sand coarsening and river channel scouring and incision. Since the Jingjiang River section carried out the waterway regulation project from 2013 to 2015, during which ecological revetment was vigorously developed, in order to compare the impact of vegetation factors, the embodiment of this application uses the waterway regulation of the Jingjiang River section as the time boundary, that is, it is assumed that there were relatively few riverbank vegetation before 2013 and it can be ignored; after 2013, ecological revetment was vigorously developed, and the riverbank was covered with vegetation and grew lushly. In addition, in the waterway regulation project, the construction water level controlled by the elevation design of the ecological revetment section is generally a low-water platform. Therefore, in the working condition design, the starting position of vegetation growth is considered to correspond to the low-water level of the Shashi Station, that is, z=32.7m, and the vegetation is emergent vegetation represented by reeds.

[0113] It can be seen that the working conditions B, AE and AEV correspond to the conditions of Shashi Hydrological Station in 2003, 2013 and 2016 respectively. The purpose of designing other working conditions is to use the control variable method to analyze the influence of single factor changes on the resistance coefficient. In addition, in order to simplify the calculation, the complex measured cross-section is generalized into a regular polygon in the actual calculation process ( Figure 6 b).

[0114] Figure 7 This is a schematic diagram of the calculation results of the water level-flow relationship of a hydrological station according to an embodiment of the present application. Figure 7 As shown in Figure 1, the calculation results of working condition B (2003), working condition AE (2013) and working condition (2016) are shown, respectively. The calculation of resistance coefficient is based on formula (10), and the solution of water level flow relationship is based on formula (1). Figure 8 This is a schematic diagram of the measured results of the water level-flow relationship of a hydrological station according to an embodiment of the present application. Figure 7 and Figure 8 It can be seen that the calculated flow-water level relationship is consistent with the trend of the measured data in the embodiment of the present application, that is, the same flow-low water level decreases, and the same flow-flood level rises.

[0115] That is, the calculation results of the same flow-water level change trend of the river channel comprehensive resistance coefficient prediction method in the embodiment of the present application are basically consistent with the measured results, which proves the accuracy of the river channel comprehensive resistance coefficient prediction method proposed by the present invention.

[0116] Furthermore, based on the prediction results of the embodiments of the present application, the changes in the measured water level-flow relationship, changes in bed sand gradation, river channel scouring and silting, and changes in the deep water line can be further analyzed to provide a basis for river and waterway management. For example, under low-flow conditions: river channel scouring and cutting is the main controlling factor causing the same-flow-low-water level drop at the Shashi station, and bed sand coarsening has suppressed the downward trend of the same-flow-low-water level to a certain extent. Under high-flow conditions, the increase in the resistance coefficient caused by bed sand coarsening and vegetation coverage is the main controlling factor causing the same-flow-flood level rise at the Shashi station. When vegetation does not exist, bed sand coarsening contributes the most to water level rise; when vegetation exists, vegetation contributes the most to water level rise, followed by bed sand coarsening.

[0117] According to the method for predicting the comprehensive resistance coefficient of a river channel proposed in the embodiment of the present application, the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient can be calculated based on the actual water flow, vegetation information and sediment data of the target area in the river channel, and then the comprehensive resistance coefficient of the river channel in the target area can be predicted by combining at least one of the interface area between the vegetation group and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body under the unit river channel length. In this way, the influence of factors such as bed sand coarsening, river channel scouring and cutting, and vegetation coverage on the river channel resistance is comprehensively considered, and the accuracy of the prediction results of the comprehensive resistance coefficient of the river channel is effectively improved. The contribution of different factors to the river channel resistance coefficient and the change of the water level-flow relationship can also be quantitatively analyzed based on the prediction results, so as to analyze the changes in the measured water level-flow relationship, the changes in the bed sand grading, the changes in the river channel scouring and silting, and the changes in the deep channel line, and provide a basis for river and waterway management. This solves the problem that the research on river resistance coefficient in related technologies is mainly based on experience. When faced with situations such as the downstream riverbed of the river is in a state of continuous scouring or the water and sand conditions in the river are complex, it is impossible to effectively determine the comprehensive river resistance coefficient and it is difficult to distinguish the specific contribution of changes in various influencing factors to changes in the river resistance coefficient and the water level-flow relationship. It also solves the problem of how to comprehensively consider the influencing factors of river resistance to calculate the effective comprehensive river resistance coefficient and analyze its impact on changes in the water level-flow relationship.

[0118] Next, a device for predicting the comprehensive resistance coefficient of a river channel proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0119] Fig. 9 It is a structural schematic diagram of a device for predicting a comprehensive resistance coefficient of a river channel according to an embodiment of the present application.

[0120] like Fig. 9 As shown, the river channel comprehensive resistance coefficient prediction device 10 includes: a calculation module 100, an acquisition module 200 and a prediction module 300.

[0121] The calculation module 100 is used to obtain the actual water flow, vegetation information and sediment data of the target area in the river channel to calculate the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient.

[0122] The acquisition module 200 is used to obtain at least one of the interface areas of the vegetation group and the water body, the interface area of ​​the riverbed and the water body, and the interface area of ​​the river bank and the water body per unit river channel length.

[0123] The prediction module 300 is used to predict the comprehensive resistance coefficient of the river channel in the target area according to the vegetation blocking coefficient, the vegetation interface, the riverbed and riverbank resistance coefficients and at least one interface area.

[0124] Optionally, in one embodiment of the present application, the calculation formula of the comprehensive resistance coefficient of the river channel can be expressed as:

[0125]

[0126] Among them, n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, and B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively, Cv, C b and C B are the resistance coefficients of the vegetation interface, riverbed and riverbank, L v , L b and L B They are the interface area between vegetation and water body, the interface area between riverbed and water body, and the interface area between riverbank and water body per unit river length.

[0127] Optionally, in one embodiment of the present application, the computing module 100 includes: a collection unit and an acquisition unit.

[0128] The acquisition unit is used to acquire basic parameters of the target area, and the basic parameters include at least one of the river length, river width and river gradient.

[0129] The acquisition unit is used to obtain the actual water flow, vegetation information and sediment data of the target area according to the basic parameters.

[0130] Optionally, in one embodiment of the present application, the actual water flow includes the water level and flow velocity along the river channel, the vegetation information includes at least one of vegetation height, vegetation weight, frontal area, and blocking coefficient, and the sediment data includes bed sediment grading and suspended sediment concentration.

[0131] It should be noted that the aforementioned explanation of the embodiment of the method for predicting the comprehensive resistance coefficient of a river channel is also applicable to the device for predicting the comprehensive resistance coefficient of a river channel of this embodiment, and will not be repeated here.

[0132] According to the comprehensive resistance coefficient prediction device for a river channel proposed in the embodiment of the present application, the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient can be calculated based on the actual water flow, vegetation information and sediment data of the target area in the river channel, and then the comprehensive resistance coefficient of the river channel in the target area can be predicted by combining at least one of the interface area between the vegetation group and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body under the unit river channel length. In this way, the influence of factors such as bed sand coarsening, river channel scouring and cutting, and vegetation coverage on the river channel resistance is comprehensively considered, and the accuracy of the prediction results of the comprehensive resistance coefficient of the river channel is effectively improved. The contribution of different factors to the river channel resistance coefficient and the change of the water level-flow relationship can also be quantitatively analyzed based on the prediction results, so as to analyze the changes in the measured water level-flow relationship, the changes in the bed sand grading, the changes in the river channel scouring and silting, and the changes in the deep well line, and provide a basis for the management of rivers and waterways. This solves the problem that the research on river resistance coefficient in related technologies is mainly based on experience. When faced with situations such as the downstream riverbed of the river is in a state of continuous scouring or the water and sand conditions in the river are complex, it is impossible to effectively determine the comprehensive river resistance coefficient and it is difficult to distinguish the specific contribution of changes in various influencing factors to changes in the river resistance coefficient and the water level-flow relationship. It also solves the problem of how to comprehensively consider the influencing factors of river resistance to calculate the effective comprehensive river resistance coefficient and analyze its impact on changes in the water level-flow relationship.

[0133] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0134] A memory 1001 , a processor 1002 , and a computer program stored in the memory 1001 and executable on the processor 1002 .

[0135] When the processor 1002 executes the program, the method for predicting the comprehensive resistance coefficient of a river channel provided in the above embodiment is implemented.

[0136] Furthermore, the electronic device further comprises:

[0137] The communication interface 1003 is used for communication between the memory 1001 and the processor 1002 .

[0138] The memory 1001 is used to store computer programs that can be executed on the processor 1002 .

[0139] The memory 1001 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0140] If the memory 1001, the processor 1002 and the communication interface 1003 are implemented independently, the communication interface 1003, the memory 1001 and the processor 1002 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.10 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0141] Optionally, in a specific implementation, if the memory 1001, the processor 1002 and the communication interface 1003 are integrated on a chip, the memory 1001, the processor 1002 and the communication interface 1003 can communicate with each other through an internal interface.

[0142] The processor 1002 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0143] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for predicting the comprehensive resistance coefficient of a river channel.

[0144] An embodiment of the present application also provides a computer program product, including a computer program, which can run computer instructions. When the computer instructions are executed by a processor, the method for predicting the comprehensive resistance coefficient of a river provided in the embodiment of the present application is implemented.

[0145] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0146] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0147] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0149] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0150] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0151] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0152] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for predicting the comprehensive resistance coefficient of a river channel, characterized in that: The following steps are involved: Obtain the actual water flow, vegetation information and sediment data of the target area in the river channel to calculate the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient; Obtaining at least one of the interface areas of the vegetation group and the water body, the interface area of ​​the riverbed and the water body, and the interface area of ​​the river bank and the water body per unit river channel length; The comprehensive resistance coefficient of the river channel in the target area is predicted based on the vegetation blocking coefficient, the vegetation interface, the riverbed and riverbank resistance coefficients and the at least one interface area.

2. The method according to claim 1, characterized in that: The calculation formula of the comprehensive resistance coefficient of the river channel is: Where n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, and B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively, C v , C b and C B are the resistance coefficients of the vegetation interface, the riverbed and the riverbank, respectively, v , L b and L B They are respectively the interface area between the vegetation community and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body per unit river channel length.

3. The method according to claim 1, characterized in that The actual water flow, vegetation information and sediment data of the target area in the river channel are obtained, including: Collecting basic parameters of the target area, wherein the basic parameters include at least one of river length, river width and river gradient; The actual water flow, vegetation information and sediment data of the target area are obtained according to the basic parameters.

4. The method according to claim 1, characterized in that: The actual water flow includes the water level and flow velocity along the river channel, the vegetation information includes at least one of vegetation height, vegetation weight, water frontage area, and blocking coefficient, and the sediment data includes bed sediment grading and suspended sediment concentration.

5. A device for predicting the comprehensive resistance coefficient of a river channel, characterized in that: include: The calculation module is used to obtain the actual water flow, vegetation information and sediment data of the target area in the river channel to calculate the vegetation blocking coefficient, vegetation interface, riverbed and riverbank resistance coefficient; An acquisition module, used to acquire at least one of the interface areas of the vegetation group and the water body, the interface area of ​​the riverbed and the water body, and the interface area of ​​the river bank and the water body per unit river channel length; The prediction module is used to predict the comprehensive resistance coefficient of the river channel in the target area according to the vegetation blocking coefficient, the vegetation interface, the riverbed and riverbank resistance coefficients and the area of ​​at least one interface.

6. The device according to claim 5, characterized in that The calculation formula of the comprehensive resistance coefficient of the river channel is: Where n is the comprehensive resistance coefficient of the river channel, H is the water depth, g is the acceleration of gravity, and B x is the vegetation blocking coefficient, A and A′ are the cross-sectional area of ​​water flow and the projection area of ​​vegetation area on the water body, respectively, C v , C b and C B are the resistance coefficients of the vegetation interface, the riverbed and the riverbank, respectively, v , L b and L B They are respectively the interface area between the vegetation community and the water body, the interface area between the riverbed and the water body, and the interface area between the riverbank and the water body per unit river channel length.

7. The device according to claim 5, characterized in that The computing module comprises: A collection unit, used for collecting basic parameters of the target area, wherein the basic parameters include at least one of river length, river width and river gradient; The acquisition unit is used to acquire the actual water flow, vegetation information and sediment data of the target area according to the basic parameters.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for predicting the comprehensive resistance coefficient of a river channel as described in any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for predicting the comprehensive resistance coefficient of a river channel as described in any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed, it is used to implement the method for predicting the comprehensive resistance coefficient of a river channel as described in any one of claims 1 to 4.

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