Seepage river vegetation water flow structure simulation system and method

Abstract

According to the seepage riverway vegetation water flow structure simulation system and method, a model prediction unit establishes a seepage riverway vegetation resistance coefficient equation and a water depth model based on the Saint-Venant equation, and predicted water depth values under different vegetation densities and different seepage intensities are obtained through prediction; the experiment measurement unit is provided with a seepage water tank experiment to obtain actually measured water depth values under different vegetation densities and different seepage intensities; the result comparison unit compares the predicted water depth value with the actually measured water depth value to obtain a prediction precision conclusion of the water depth model; and the result analysis unit obtains the seepage river vegetation resistance coefficient through analysis according to the prediction precision conclusion of the water depth model, and analyzes factors influencing the seepage river vegetation resistance coefficient. The method is helpful to understand seepage river vegetation water flow structure characteristics, and provides a certain reference for river bed or river bank ecological restoration practice.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental hydraulics, and more specifically, to a system and method for simulating water flow structure in vegetation in a seepage river channel. Background Art

[0002] Aquatic vegetation is widely distributed in riverbanks, streams and channels, changing the flow characteristics of rivers. For example, changes in river flow structure caused by plants significantly affect hydrodynamics, and the impact of vegetation depends largely on the additional resistance it provides. Therefore, it is of great significance to study the physical processes of the complex interaction between water flow and vegetation. The impact of vegetation on hydrodynamics depends largely on the additional resistance it provides.

[0003] In the prior art, there have been many studies on the flow characteristics of open channel water flow with vegetation. In a stable non-uniform flow, the drag coefficient presents a parabolic shape along the vegetation path. The non-uniformity of water flow leads to the parabolic characteristics. The impact of vegetation on water flow depends not only on the characteristics of the river channel, but also on the characteristics of the vegetation. Flexible vegetation plays an important role in natural river channels and riverbank ecology. There are two effects in emergent vegetation patches: shielding and shading: the shielding effect increases the drag coefficient, while the shading effect, especially at the leading edge and tail of the vegetation patch, reduces the resistance caused by the bending deformation of the flexible canopy.

[0004] Water percolates through the boundaries of alluvial channels, rivers, and streams in the form of infiltration due to the porosity of the granular material and the water level difference between the river and groundwater levels. Although there have been many studies in the prior art on the flow characteristics of open channel water flow with vegetation, the flow characteristics of emergent rigid vegetation with downward infiltration have not been studied.

[0005] Therefore, the problems existing in the prior art need to be further improved and developed. Summary of the invention

[0006] (I) Purpose of the invention: To solve the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a system and method for simulating water flow structure in a seepage channel with vegetation, and to study the water flow characteristics in a seepage channel with vegetation.

[0007] (II) Technical solution: In order to solve the above technical problems, the present technical solution provides a seepage channel vegetation water flow structure simulation system, including a model prediction unit, an experimental measurement unit, a result comparison unit and a result analysis unit; the model prediction unit establishes a seepage channel vegetation resistance coefficient equation and a water depth model based on the Saint-Venant equation, and predicts the predicted water depth values ​​under different vegetation densities and different seepage intensities;

[0008] The experimental measurement unit includes a seepage experiment module, and the seepage experiment module is used to set a seepage flume experiment to obtain measured water depth values ​​under different vegetation densities and different seepage intensities;

[0009] The result comparison unit compares the predicted water depth value with the measured water depth value to obtain a prediction accuracy conclusion of the water depth model;

[0010] The result analysis unit obtains the seepage channel vegetation resistance coefficient according to the prediction accuracy conclusion of the water depth model, and analyzes the factors affecting the seepage channel vegetation resistance coefficient.

[0011] Preferably, for a constant non-uniform gradient flow, when the vegetation is not submerged, the assumption of local uniform flow is used to analyze the force of the water flow, and the vegetation resistance coefficient of the seepage channel is The water depth prediction value h under any vegetation density is predicted by water depth H = c1ln|x+c2|+c3 Predicted ;

[0012] Among them, C d is the drag coefficient of vegetation; m is the density of vegetation distribution; D is the width of vegetation; g is the acceleration of gravity, φ veg is the density of vegetation, H is the water depth, x is the direction of water flow; c1, c2, c3 are parameters, which are determined by robust regression analysis using MATLAB software.

[0013] Preferably, the seepage experiment module includes a seepage trough, a water pump is provided upstream of the seepage trough, water is supplied from the water reservoir to the seepage trough by the water pump, a honeycomb-shaped energy dissipation pipe is provided at the upstream water inlet to smooth the water flow, an adjustable tail gate is provided at the end of the seepage trough to ensure that the water flows evenly into the water reservoir, different vegetation densities are provided in the seepage trough, so as to measure the water depth under different vegetation densities; a seepage trough groove is provided in the lower part of the seepage trough, and holes are evenly drilled at the bottom of the seepage trough groove to simulate a uniform seepage process.

[0014] Preferably, an aluminum cylindrical rod with a height of 0.4 m and a diameter of d=0.007 m is used to simulate rigid water-emergent vegetation. By adjusting the distance between the aluminum cylindrical rods to simulate the spacing between vegetation, different vegetation densities are obtained to be 0.267, 0.150, and 0.096, respectively. The measured water depth values ​​h of 27 working conditions with different vegetation densities are obtained. Measured .

[0015] Preferably, the measured values ​​of vegetation water depth under different seepage intensities are compared with the predicted values ​​of water depth, and the fitting degree between the measured values ​​of water depth and the predicted values ​​of water depth is analyzed by the root mean square error:

[0016] Where: h Predicted is the predicted water depth; h Measured is the measured value of water depth; N is the number of measuring points under each working condition.

[0017] Preferably, The overall RMSE of the 9 groups of measured water depth values ​​is 0.00042; The overall RMSE of the 9 groups of measured water depth values ​​is 0.00023; The overall RMSE of the 9 groups of measured water depth values ​​is 0.00026.

[0018] Preferably, the vegetation resistance coefficient of the seepage channel is obtained by analyzing the water depth prediction value of the water depth model; and the variation law of the vegetation resistance coefficient under different seepage intensities is obtained according to the seepage channel vegetation resistance coefficient equation, and the vegetation resistance coefficient under different seepage intensities is analyzed to obtain the influencing factors affecting the vegetation resistance coefficient of the seepage channel.

[0019] Preferably, under different seepage intensities, the seepage channel vegetation resistance coefficient presents three changing trends along the way, and the seepage channel vegetation resistance coefficients of the three changing curves at the end of the vegetation zone will be concentrated in a certain value range; When , the value range of vegetation resistance coefficient along the seepage channel is [0.1, 0.4]; when When , the value range of vegetation resistance coefficient along the seepage channel is [0.11, 0.21]; when When the vegetation resistance coefficient along the seepage channel is in the range of [0.08, 0.22]; the value of the vegetation resistance coefficient of the seepage channel changes with the vegetation density. decreases with the decrease of;

[0020] The vegetation resistance coefficient of the seepage channel shows three changing trends along the way: under low seepage intensity: the vegetation resistance coefficient of the seepage channel decreases monotonically along the way; under medium seepage intensity: the vegetation resistance coefficient of the seepage channel increases first and then decreases; under high seepage intensity: the vegetation resistance coefficient of the seepage channel decreases first and then increases.

[0021] Preferably, the larger the variation range of the vegetation resistance coefficient n of the seepage channel, the more significant the resistance effect on the water flow, especially under the condition of high seepage intensity; the vegetation resistance coefficient of the seepage channel is Among them: Bed slope effect term: S0 * =0; Flow pressure item: Convection term: Seepage term: The change of n is given by (P * -A * +S * )Decide.

[0022] The method for simulating water flow structure of vegetation in a seepage channel is applicable to the water flow structure simulation system of vegetation in a seepage channel, and specifically comprises the following steps:

[0023] Step 1: Based on the Saint-Venant equation, the seepage channel vegetation resistance coefficient equation and water depth model are established, and the predicted water depth values ​​under different vegetation densities and different seepage intensities are predicted;

[0024] Step 2: Set up a seepage flume experiment to obtain measured water depth values ​​under different vegetation densities and different seepage intensities;

[0025] Step 3: Compare the predicted water depth value with the measured water depth value to obtain the prediction accuracy conclusion of the water depth model;

[0026] Step 4: Analyze the prediction accuracy conclusion of the water depth model to obtain the seepage channel vegetation resistance coefficient, and analyze the factors that affect the seepage channel vegetation resistance coefficient.

[0027] (III) Beneficial effects: The system and method for simulating the structure of vegetation flow in seepage channels of the present invention establishes the vegetation resistance coefficient equation and water depth model under seepage conditions through the Saint-Venant equation, and uses cylindrical aluminum rods to simulate rigid vegetation. By conducting indoor seepage experiments, the water depth distribution along the vegetation flow under seepage conditions is simulated and verified, thereby analyzing and obtaining the structural characteristics and resistance characteristics of emergent vegetation flow under different vegetation densities and different seepage intensities, obtaining the vegetation flow resistance coefficient under seepage conditions with different vegetation densities and different seepage intensities, and studying the changing law of the vegetation flow resistance coefficient under seepage conditions, which is helpful to understand the structural characteristics of vegetation flow in seepage channels and provide a certain reference for the practice of ecological restoration of riverbeds or riverbanks. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a structural diagram of the water flow structure simulation system of the vegetation in the seepage river channel of the present invention;

[0029] Figure 2 It is a flow chart of the method for simulating water flow structure of vegetation in seepage river channel of the present invention;

[0030] Figure 3 It is a schematic diagram of the seepage tank structure;

[0031] Figure 4 It is a schematic diagram comparing the measured water depth and the predicted water depth under the vegetation density of 0.267;

[0032] Figure 5 It is a schematic diagram comparing the measured water depth and the predicted water depth under the vegetation density of 0.150;

[0033] Figure 6 It is a schematic diagram comparing the measured water depth and the predicted water depth under the vegetation density of 0.096;

[0034] Figure 7 It is a schematic diagram of the distribution of vegetation resistance coefficient along the seepage channel with different seepage intensities under the vegetation density of 0.267;

[0035] Figure 8 It is a schematic diagram of the distribution of vegetation resistance coefficient along the seepage channel with different seepage intensities under the vegetation density of 0.150;

[0036] Fig. 9 It is a schematic diagram of the distribution of vegetation resistance coefficient along the seepage channel with different seepage intensities under the vegetation density of 0.096;

[0037] Fig.10 It is a schematic diagram of the interaction between the streamwise pressure term P*, the convection term A* and the seepage term S* at a vegetation density of 0.267;

[0038] Fig.11 It is a schematic diagram of the interaction between the streamwise pressure term P*, the convection term A* and the seepage term S* at a vegetation density of 0.150;

[0039] Fig.12 It is a schematic diagram of the interaction between the streamwise pressure term P*, the convection term A* and the seepage term S* at a vegetation density of 0.096;

[0040] Fig.13 This is a schematic diagram of the distribution of P*-A* along the route under a vegetation density of 0.267;

[0041] Fig.14 This is a schematic diagram of the distribution of P*-A* along the route under a vegetation density of 0.150;

[0042] Fig.15 This is a schematic diagram of the distribution of P*-A* along the route under a vegetation density of 0.096;

[0043] Fig.16 This is a schematic diagram of the distribution of P*-A*-S* along the route under a vegetation density of 0.267;

[0044] Fig.17 This is a schematic diagram of the distribution of P*-A*-S* along the route under a vegetation density of 0.150;

[0045] Fig.18 This is a schematic diagram of the along-the-route distribution of P*-A*-S* under a vegetation density of 0.096. DETAILED DESCRIPTION

[0046] The present invention is further described in detail below in conjunction with preferred embodiments. More details are elaborated in the following description to facilitate a full understanding of the present invention. However, the present invention can obviously be implemented in a variety of other ways different from the description. Those skilled in the art can make similar generalizations and deductions based on actual application situations without violating the connotation of the present invention. Therefore, the protection scope of the present invention should not be limited by the content of this specific embodiment.

[0047] The accompanying drawings are schematic diagrams of embodiments of the present invention. It should be noted that the drawings are only examples and are not drawn to scale, and should not be used to limit the actual protection scope of the present invention.

[0048] Seepage river vegetation water flow structure simulation system, such as Figure 1 As shown, it includes a model prediction unit, an experimental measurement unit, a result comparison unit and a result analysis unit. The model prediction unit establishes a seepage channel vegetation resistance coefficient equation and a water depth model based on the Saint-Venant equation, and predicts the predicted water depth values ​​under different vegetation densities and different seepage intensities. The experimental measurement unit includes a seepage experiment module, and the seepage experiment module sets a seepage flume experiment to obtain the measured water depth values ​​under different vegetation densities and different seepage intensities. The result comparison unit compares the predicted water depth value with the measured water depth value to obtain the prediction accuracy conclusion of the water depth model. The result analysis unit analyzes the seepage channel vegetation resistance coefficient based on the prediction accuracy conclusion of the water depth model, and analyzes the factors affecting the seepage channel vegetation resistance coefficient.

[0049] The method for simulating water flow structure of vegetation in seepage river channel is applicable to the water flow structure simulation system of vegetation in seepage river channel, such as Figure 2 As shown, the specific steps include:

[0050] Step 1: Based on the Saint-Venant equation, the seepage channel vegetation resistance coefficient equation and water depth model are established, and the predicted water depth values ​​under different vegetation densities and different seepage intensities are predicted.

[0051] Step 2: Set up a seepage flume experiment to obtain the measured water depth values ​​under different vegetation densities and different seepage intensities.

[0052] Step 3: Compare the predicted water depth value with the measured water depth value to obtain the prediction accuracy conclusion of the water depth model.

[0053] Step 4: Analyze the prediction accuracy conclusion of the water depth model to obtain the seepage channel vegetation resistance coefficient, and analyze the factors that affect the seepage channel vegetation resistance coefficient.

[0054] More specifically, the specific operation of the model prediction unit in step 1 is:

[0055] As shown in formula (1), the equation of motion of the classic Saint-Venant equation (SVE) under constant flow conditions is:

[0056]

[0057] In the presence of vegetation, the water flow mechanism of the vegetation and river channel is very complex, and the vegetation resistance coefficient of the seepage river channel is difficult to determine. The present invention seeks the energy slope S by force analysis. f For the steady non-uniform gradually varying flow, when the vegetation is not submerged, the assumption of local uniform flow is adopted to analyze the force of the water flow.

[0058] As shown in formula (2) and formula (3), in the case of seepage, considering the influence of seepage, the continuity equation and motion equation are obtained from the Saint-Venant equation:

[0059]

[0060] Among them, x is the direction of water flow, U is the average velocity of water depth, H is the water depth, K is the rainfall intensity, S f is the energy slope, S0 is the riverbed bottom slope; g is the gravitational acceleration.

[0061] As shown in formula (4) and formula (5), the flow rate of the water in the river is constant and the seepage intensity is also constant, so the partial derivative of the time term is removed, and the continuity equation and the motion equation are simplified to:

[0062]

[0063] As shown in formula (6), we can get:

[0064]

[0065] As shown in formula (7), the expression of energy slope in vegetation flow is:

[0066]

[0067] As shown in formula (8), the drag coefficient of vegetation under seepage conditions can be obtained from formula (6) and formula (7):

[0068]

[0069] When vegetation exists, the effective water-passing width of the river channel becomes narrower, as shown in formula (9). At this time, the relationship between the average flow velocity U and the water depth H is:

[0070]

[0071] Among them, Q xis the flow in the x direction in the vegetation area, B is the width of the river channel, and B e is the effective water-passing section width; H is the water depth, φ veg is the density of vegetation. veg =mπd 2 / 4; the effective water-passing section width B of the vegetation water flow e =B(1-φ veg ).

[0072] Assume that the total seepage intensity in the vegetation area is Q S , the length of the vegetation area is L veg , and considering the existence of uniform seepage in the vegetation area, as shown in formula (10), the seepage intensity K is:

[0073]

[0074] As shown in formula (11), assuming that the flow rate of open channel water is constant at Q0, solving the continuity equation yields:

[0075]

[0076] Where 0≤x≤L veg .

[0077] As shown in formula (12), according to the Manning formula The vegetation resistance coefficient of the seepage channel is obtained as follows:

[0078]

[0079] Among them, C d is the drag coefficient of vegetation; m is the density of vegetation distribution; D is the width of vegetation; g is the acceleration of gravity, φ veg is the density of vegetation, H is the water depth, and x is the direction of water flow.

[0080] For constant non-uniform water flow with seepage, the water surface line will fluctuate slightly due to the influence of vegetation and seepage. A continuous and smooth curve function is used to simulate the water surface line to reduce the error. It can be obtained that in the case of seepage, the water surface is still a downward convex curve similar to the S2 type, as shown in formula (13). The logarithmic equation is used to simulate the water depth:

[0081] H=c1 ln|x+c2|+c3(13),

[0082] Thus, the water depth model is obtained, and the water depth prediction value h under any vegetation density is predicted by the water depth model. Predicted Among them, c1, c2, and c3 are parameters, which can be determined by robust regression analysis using MATLAB software.

[0083] More specifically, the specific operations of the experimental verification unit in step 2 are:

[0084] The seepage experiment module comprises a seepage flume, in which different vegetation densities are arranged, so as to measure the water depth under different vegetation densities.

[0085] The seepage flume experiment was conducted in the seepage flume of the State Key Laboratory of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research. Figure 3 As shown, the seepage water trough is a rectangular circulating glass water trough, 4m long, 0.5m wide, 0.4m high, with a bottom slope S0=0, and the side wall material is tempered glass. A water pump is provided upstream of the seepage water trough, through which water is supplied from the water reservoir to the seepage water trough. A honeycomb energy dissipation pipe is provided at the upstream water inlet to smooth the water flow. An adjustable tail gate is provided at the end of the seepage water trough to ensure that the water flows evenly into the water reservoir. A seepage water trough groove is provided in the lower part of the seepage water trough. The seepage water trough groove is 1.0m long and 0.4m deep, and is filled with pebbles to simulate a real riverbed. Holes are evenly drilled at the bottom of the seepage water trough groove to simulate a uniform seepage process. The inflow flow rate and seepage intensity are both displayed by an electromagnetic flowmeter.

[0086] A perforated plastic plate was placed on the upper surface of the seepage tank groove filled with pebbles, and an aluminum cylindrical rod with a height of 0.4m and a diameter of d=0.007m was used to simulate rigid water-emergent vegetation. The aluminum cylindrical rods were evenly fixed on the 0.01m thick perforated plastic plate. The distance between the aluminum cylindrical rods was adjusted to simulate the spacing between vegetation, and different vegetation densities were obtained to be 0.267, 0.150, and 0.096, respectively. The water flow rate during the entire experiment remained constant, which was Q=40.3m 3 / h, as shown in Table 1, the measured water depth values ​​h of 27 working conditions with different vegetation densities were obtained. Measured And other parameters.

[0087] Table 1 Experimental parameters for each working condition

[0088]

[0089]

[0090] More specifically, the specific operation of the result comparison unit in step 3 is:

[0091] like Figure 4 , Figure 5 , Figure 6As shown in Figure 1, the measured water depth of vegetation under different seepage intensities is compared with the predicted water depth. In general, the predicted water depth along the flow direction is consistent with the measured water depth. The root mean square error (RMSE) is used to analyze the degree of fit between the measured water depth and the predicted water depth; if the root mean square error is smaller, the degree of fit is higher. As shown in formula (14), it can be expressed as:

[0092]

[0093] Among them, h Predicted is the predicted water depth; h Measured is the measured value of water depth; N is the number of measuring points under each working condition.

[0094] The calculation results of RMSE are shown in Table 2. The seepage flume test in this study has a total of 27 working conditions, with vegetation density The corresponding working conditions are A0-A8, B0-B8, and C0-C8 respectively. The overall RMSE of the 9 groups of measured water depth values ​​is 0.00042; The overall RMSE of the 9 groups of measured water depth values ​​is 0.00023; The overall RMSE of the 9 groups of measured water depth values ​​is 0.00026. The results show that, through the comparison of the measured water depth values ​​and the predicted water depth values, the simulation results of the flume test of the present invention have a small deviation, proving that the water depth model and the seepage channel vegetation resistance coefficient equation have good applicability under different seepage conditions and can be used to predict the water depth distribution along the vegetation water flow under seepage conditions.

[0095] Table 2 Root mean square error (RMSE) of simulation

[0096]

[0097] More specifically, the specific operations of the result analysis unit in step 4 are:

[0098] The water depth prediction value of the water depth model is analyzed to obtain the vegetation resistance coefficient of the seepage channel; and the variation law of the vegetation resistance coefficient under different seepage intensities is obtained according to the vegetation resistance coefficient equation of the seepage channel, and the vegetation resistance coefficient under different seepage intensities is analyzed to obtain the influencing factors affecting the vegetation resistance coefficient of the seepage channel.

[0099] Under different seepage intensities, the vegetation resistance coefficient of the seepage channel presents three changing trends along the way, and the vegetation resistance coefficient of the seepage channel at the end of the vegetation zone of these three changing curves will be concentrated in a certain value range. The values ​​of the vegetation resistance coefficient of the seepage channel with different vegetation densities are different. When , the value range of vegetation resistance coefficient along the seepage channel is [0.1, 0.4]; when When , the value range of vegetation resistance coefficient along the seepage channel is [0.11, 0.21]; when When the vegetation resistance coefficient along the seepage channel is in the range of [0.08, 0.22]. decreases with the decrease of .

[0100] Under different seepage intensities, the seepage channel vegetation resistance coefficient shows three changing trends along the way: Under low seepage intensity (Qs = 0-35% Q0): the seepage channel vegetation resistance coefficient decreases monotonically along the way. Under medium seepage intensity (Qs = 35% -70% Q0): the seepage channel vegetation resistance coefficient increases first and then decreases. Under high seepage intensity (Qs = 70% -95% Q0): the seepage channel vegetation resistance coefficient decreases first and then increases.

[0101] like Figure 7 As shown, when the water flow rate Q0 is 42.3m 3 / h, vegetation density is The variation of the vegetation resistance coefficient n of the seepage channel with x along the way under different seepage intensities. During the whole test process, the range of x was 0-0.7. When the seepage intensity was 0-70% Q0, the variation of the vegetation resistance coefficient n of the seepage channel with x along the way roughly showed the variation of the decreasing function "convex curve"; when the seepage intensity was 70%-95% Q0, the variation of the vegetation resistance coefficient n of the seepage channel with x along the way roughly showed the variation of the "concave curve" that first decreased and then increased to a certain value. The general variation process is: at the initial position on the left side of the image, that is, the front end of the vegetation area, when the seepage intensity was 0-70% Q0, the vegetation resistance coefficient n of the seepage channel decreased continuously with the increase of x along the way; when the seepage intensity was 70%-95% Q0, the vegetation resistance coefficient n of the seepage channel decreased first and then increased with the increase of x along the way; when reaching the end of the vegetation area, the vegetation resistance coefficient n of the seepage channel reached 0.15-0.2.

[0102] like Figure 8 As shown, when the water flow rate Q0 is 42.3m 3 / h, the vegetation density is The variation of vegetation resistance coefficient n of seepage channel with x along the way under different seepage intensities. During the whole test process, the range of x was 0-0.7. When the seepage intensity was 0-35% Q0, the variation of vegetation resistance coefficient n of seepage channel with x along the way roughly presented the variation of decreasing function "convex curve"; when the seepage intensity was 35%-70% Q0, the variation of vegetation resistance coefficient n of seepage channel with x along the way roughly presented the variation of "upward throwing curve"; when the seepage intensity was 70%-95% Q0, the variation of vegetation resistance coefficient n of seepage channel with x along the way roughly presented the variation of "concave curve" which first decreased and then increased to a certain value. The general change process is: at the initial position on the left side of the image, that is, the front end of the vegetation area, when the seepage intensity is 0-35% Q0, the vegetation resistance coefficient n of the seepage channel decreases continuously with the increase of x along the way; when the seepage intensity is 35%-70% Q0, the vegetation resistance coefficient n of the seepage channel increases first and then decreases with the increase of x along the way; when the seepage intensity is 70%-95% Q0, the vegetation resistance coefficient n of the seepage channel decreases first and then increases with the increase of x along the way. When reaching the end of the vegetation area, the vegetation resistance coefficient n of the seepage channel reaches 0.14-0.18.

[0103] like Fig. 9 As shown, when the water flow rate Q0 is 42.3m 3 / h, vegetation density is The variation of vegetation resistance coefficient n of seepage channel with x along the way under different seepage intensities. During the whole test process, the range of x was 0-0.7. When the seepage intensity was 0-10% Q0, the variation of vegetation resistance coefficient n of seepage channel with x along the way roughly presented the variation of decreasing function "convex curve"; when the seepage intensity was 10%-70% Q0, the variation of vegetation resistance coefficient n of seepage channel with x along the way roughly presented the variation of "upward throwing curve"; when the seepage intensity was 70%-95% Q0, the variation of vegetation resistance coefficient n of seepage channel with x along the way roughly presented the variation of "concave curve" which first decreased and then increased to a certain value. The general change process is: at the initial position on the left side of the image, that is, the front end of the vegetation area, when the seepage intensity is 0-70% Q0, n decreases continuously with the increase of x; when the seepage intensity is 10%-70% Q0, the vegetation resistance coefficient n of the seepage channel first increases and then decreases with the increase of x along the way; when the seepage intensity is 70%-95% Q0, the vegetation resistance coefficient n of the seepage channel first decreases and then increases with the increase of x along the way. When reaching the end of the vegetation area, the vegetation resistance coefficient n of the seepage channel reaches 0.1-0.16.

[0104] The variation of the vegetation resistance coefficient n of the seepage channel along the course is significantly affected by the vegetation density and the seepage intensity. There is an obvious transition interval in the variation of the vegetation resistance coefficient n of the seepage channel under different vegetation density and seepage intensity conditions. As shown in Table 3, under different vegetation density and seepage intensity conditions, the vegetation resistance coefficient n of the seepage channel has different variation rules in different transition intervals.

[0105] Table 3 Transitional variation range of vegetation resistance coefficient n along the seepage channel under different seepage intensities

[0106]

[0107] In high vegetation density Under the condition of Qs / Q0=0-60%, the vegetation resistance coefficient n of the seepage channel shows a significant nonlinear characteristic. Under the condition of Qs / Q0=0-60%, the vegetation resistance coefficient n of the seepage channel shows a monotonically decreasing convex curve change with the increase of x; while under the condition of Qs / Q0=70%-95%, the vegetation resistance coefficient n of the seepage channel shows a concave curve change with x that first decreases and then increases. Therefore, Qs / Q0=60%-70% is a high vegetation density. The transitional change interval of n along the course. The value range of the vegetation resistance coefficient n of the seepage channel is [0.1, 0.4].

[0108] In medium vegetation density Under the condition of Qs / Q0=0-35% (low seepage intensity), the seepage channel vegetation resistance coefficient n shows a monotonically decreasing convex curve change with the increase of x; under the condition of Qs / Q0=50-60%, the seepage channel vegetation resistance coefficient n shows a convex curve change with the increase of x, which first increases and then decreases; and under the condition of Qs / Q0=70%-95%, the seepage channel vegetation resistance coefficient n shows a concave curve change with x, which first decreases and then increases. Therefore, Qs / Q0=35%-50% and Qs / Q0=60%-70% are medium vegetation density, respectively. In the transitional change interval of n along the course, the value range of the seepage channel vegetation resistance coefficient n is [0.11, 0.21].

[0109] In low vegetation density Under the condition of Qs / Q0=0-12.5%, the seepage channel vegetation resistance coefficient n shows a monotonically decreasing convex curve change with the increase of x; under the condition of Qs / Q0=25-60%, the seepage channel vegetation resistance coefficient n shows a convex curve change with the increase of x, which first increases and then decreases; and under the condition of Qs / Q0=70%-95%, the seepage channel vegetation resistance coefficient n shows a concave curve change with x, which first decreases and then increases. Therefore, Qs / Q0=12.5%-25% and Qs / Q0=60%-70% are low vegetation density, respectively. The transitional change interval of n along the course. The value range of vegetation resistance coefficient n of seepage channel is [0.08, 0.22].

[0110] It can be seen from Table 3 that the higher the vegetation density, the larger the variation range of the vegetation resistance coefficient n of the seepage channel, and the more significant the resistance effect on the water flow, especially under high seepage intensity conditions.

[0111] As shown in formula (15)-formula (18), all the main terms in the Saint-Venant equation are d The normalized expression of is:

[0112]

[0113] Vegetation resistance coefficient of seepage channel:

[0114]

[0115] Among them: Bed slope effect term: S0 * =0; Flow pressure item: Convection term: Seepage term: The change of n is given by (P * -A * +S * )Decide.

[0116] like Fig.10 , Fig.11 , Fig.12 As shown, the interaction between the pressure term P*, the convection term A* and the seepage term S* along the stream direction in the operating conditions A0-A8, B0-B8, and C0-C8 is shown.

[0117] like Figure 13-Figure 18 As shown, (P * -A * +S * ) is almost the same shape as (P * -A * ) is the same shape. The shape of the vegetation resistance coefficient n of the seepage channel is mainly determined by P*. When the water flow rate Q0 is 42.3m 3 / h, vegetation density is The trend of the various factors affecting the vegetation resistance coefficient n of the seepage channel along the x path under different seepage intensities is roughly the same as the trend of the curve of n along the x path. When the seepage intensity is 0-70% Q0, the change of the vegetation resistance coefficient n of the seepage channel along the x path roughly shows a "convex curve" change that first increases and then decreases; when the seepage intensity is 70%-95% Q0, the change of the vegetation resistance coefficient n of the seepage channel along the x path roughly shows a "concave curve" change that first decreases and then increases. For working conditions A0-A8, when the seepage intensity is 0-70% Q0, P* initially increases, but not significantly, and then decreases along x; when the seepage intensity is 70%-95% Q0, P* decreases and then increases along x. And the value of A* increases along x. When the seepage intensity is 0-70% Q0, the seepage term S* increases along x; when the seepage intensity is 70%-95% Q0, the seepage term S* decreases along x. P* dominates the change of the driving term (P*-A*), and the seepage term S* is smaller than the advection term A* and the pressure term P*, so the effect of S* on the water drive term (P*-A*) is small.

[0118] Therefore, for the non-uniform flow through vegetation under the seepage channel, the pressure term P*, the convection term A* and the seepage term S* lead to the change of the vegetation resistance coefficient. With the change of vegetation density and seepage intensity, the vegetation resistance coefficient n of the seepage channel eventually changes from decreasing along the way to first decreasing and then increasing.

[0119] The system and method for simulating the structure of vegetation water flow in a seepage channel of the present invention establish a vegetation resistance coefficient equation and a water depth model under seepage conditions through the Saint-Venant equation, use cylindrical aluminum rods to simulate rigid vegetation, and conduct seepage experiments to simulate and verify the distribution of water depth along the vegetation water flow under seepage conditions, thereby analyzing and obtaining the structural characteristics and resistance characteristics of the emergent vegetation water flow under different vegetation densities and different seepage intensities, obtaining the vegetation water flow resistance coefficient under seepage conditions under different vegetation densities and different seepage intensities, and studying the variation law of the vegetation water flow resistance coefficient under seepage conditions, which is helpful to understand the structural characteristics of vegetation water flow in seepage channels and provide a certain reference for the practice of riverbed or riverbank ecological restoration.

[0120] The above content is an explanation of the preferred embodiments of the present invention, which can help those skilled in the art to more fully understand the technical solution of the present invention. However, these embodiments are merely illustrative, and it cannot be determined that the specific implementation methods of the present invention are limited to the description of these embodiments. For ordinary technicians in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions and transformations can be made, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. The water flow structure simulation system of the vegetation in the seepage river channel is characterized by: It includes a model prediction unit, an experimental measurement unit, a result comparison unit and a result analysis unit; the model prediction unit establishes a seepage channel vegetation resistance coefficient equation and a water depth model based on the Saint-Venant equation, and predicts the predicted water depth values ​​under different vegetation densities and different seepage intensities; The experimental measurement unit includes a seepage experiment module, and the seepage experiment module is used to set a seepage flume experiment to obtain measured water depth values ​​under different vegetation densities and different seepage intensities; The result comparison unit compares the predicted water depth value with the measured water depth value to obtain a prediction accuracy conclusion of the water depth model; The result analysis unit obtains the seepage channel vegetation resistance coefficient according to the prediction accuracy conclusion of the water depth model, and analyzes the factors affecting the seepage channel vegetation resistance coefficient.

2. The seepage river vegetation water flow structure simulation system according to claim 1 is characterized in that: For a constant non-uniform gradient flow, when the vegetation is not submerged, the assumption of local uniform flow is used to analyze the force of the water flow. The resistance coefficient of the vegetation in the seepage channel is The water depth prediction value h under any vegetation density is predicted by water depth H = c1ln|x+c2|+c3 Predicted ; Among them, C d is the drag coefficient of vegetation; m is the density of vegetation distribution; D is the width of vegetation; g is the acceleration of gravity, φ veg is the density of vegetation, H is the water depth, x is the direction of water flow; c1, c2, c3 are parameters, which are determined by robust regression analysis using MATLAB software.

3. The seepage river vegetation water flow structure simulation system according to claim 1 is characterized in that: The seepage experiment module includes a seepage trough, a water pump is provided upstream of the seepage trough, water is supplied from the water reservoir to the seepage trough by the water pump, a honeycomb energy dissipation pipe is provided at the upstream water inlet to smooth the water flow, an adjustable tail gate is provided at the end of the seepage trough to ensure that the water flows evenly into the water reservoir, different vegetation densities are provided in the seepage trough, so as to measure the water depth under different vegetation densities; a seepage trough groove is provided at the lower part of the seepage trough, and holes are evenly drilled at the bottom of the seepage trough groove to simulate a uniform seepage process.

4. The seepage river vegetation water flow structure simulation system according to claim 3 is characterized in that: Aluminum cylindrical rods with a height of 0.4 m and a diameter of d = 0.007 m were used to simulate rigid water-emergent vegetation. The distance between the aluminum cylindrical rods was adjusted to simulate the spacing between vegetation. The different vegetation densities were 0.267, 0.150, and 0.096, respectively. The measured water depth values ​​h of 27 working conditions with different vegetation densities were obtained. Measured .

5. The seepage river vegetation water flow structure simulation system according to claim 1 is characterized in that: The measured values ​​of vegetation water depth under different seepage intensities were compared with the predicted values, and the fitting degree between the measured values ​​and the predicted values ​​was analyzed by the root mean square error: Where: h Predicted is the predicted water depth; j Measured is the measured value of water depth; N is the number of measuring points under each working condition.

6. The seepage river vegetation water flow structure simulation system according to claim 5 is characterized in that: The overall RMSE of the 9 groups of measured water depth values ​​is 0.00042; The overall RMSE of the 9 groups of measured water depth values ​​is 0.00023; The overall RMSE of the 9 groups of measured water depth values ​​is 0.00026.

7. The seepage river vegetation water flow structure simulation system according to claim 1 is characterized in that: The water depth prediction value of the water depth model is analyzed to obtain the vegetation resistance coefficient of the seepage channel; and the variation law of the vegetation resistance coefficient under different seepage intensities is obtained according to the vegetation resistance coefficient equation of the seepage channel, and the vegetation resistance coefficient under different seepage intensities is analyzed to obtain the influencing factors affecting the vegetation resistance coefficient of the seepage channel.

8. The seepage river vegetation water flow structure simulation system according to claim 7 is characterized in that: Under different seepage intensities, the vegetation resistance coefficient of the seepage channel presents three changing trends along the way, and the vegetation resistance coefficient of the seepage channel at the end of the vegetation zone of these three changing curves will be concentrated in a certain value range; When , the value range of vegetation resistance coefficient along the seepage channel is [0.1, 0.4]; when When , the value range of vegetation resistance coefficient along the seepage channel is [0.11, 0.21]; when When the vegetation resistance coefficient along the seepage channel is in the range of [0.08, 0.22]; the value of the vegetation resistance coefficient of the seepage channel changes with the vegetation density. decreases with the decrease of; The vegetation resistance coefficient of the seepage channel shows three changing trends along the way: under low seepage intensity: the vegetation resistance coefficient of the seepage channel decreases monotonically along the way; under medium seepage intensity: the vegetation resistance coefficient of the seepage channel increases first and then decreases; under high seepage intensity: the vegetation resistance coefficient of the seepage channel decreases first and then increases.

9. The seepage river vegetation water flow structure simulation system according to claim 8, characterized in that: The larger the variation range of the vegetation resistance coefficient n of the seepage channel, the more significant the resistance effect on the water flow, especially under the condition of high seepage intensity. Among them: Bed slope effect term: S0 * =0; Flow pressure item: Convection term: Seepage term: The change of n is given by (P * -A * +S * )Decide.

10. A method for simulating water flow structure in a seepage channel with vegetation, applicable to the water flow structure simulation system in a seepage channel with vegetation, characterized in that: The specific steps include: Step 1: Based on the Saint-Venant equation, the vegetation resistance coefficient equation and water depth model of the seepage channel are established, and the predicted water depth values ​​under different vegetation densities and different seepage intensities are predicted; Step 2: Set up a seepage flume experiment to obtain measured water depth values ​​under different vegetation densities and different seepage intensities; Step 3: Compare the predicted water depth value with the measured water depth value to obtain the prediction accuracy conclusion of the water depth model; Step 4: Analyze and obtain the vegetation resistance coefficient of the seepage channel according to the prediction accuracy conclusion of the water depth model, and analyze the factors affecting the vegetation resistance coefficient of the seepage channel.

Images