Channel leakage calculation method and system suitable for stratified soil and lining conditions

Abstract

The invention discloses a channel leakage calculation method and system suitable for stratified soil and lining conditions. The channel leakage calculation method comprises the steps that basic channel section parameters, soil parameters and parameters of different lining schemes are collected; constructing a channel leakage loss numerical model of the channel under the non-lining condition; simulating a channel leakage process and a channel leakage amount by using the channel leakage loss numerical model, and generating a data set; a multivariate linear regression model of the channel leakage amount is constructed and checked, and the checked model serves as a channel leakage calculation model under the lining-free condition; constructing a water seepage reduction coefficient calculation model of different lining schemes according to the change of the leakage of the lining channel; and combining the channel leakage calculation model with each water seepage reduction coefficient calculation model to obtain a calculation model for calculating channel leakage of different lining schemes. According to the method, the channel leakage amount is calculated on the basis of the channel section parameters, the soil parameters and the lining parameters, and the accuracy of leakage loss calculation of the lining channel is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of agricultural irrigation water, and in particular relates to a channel leakage calculation method and system suitable for layered soil and lining conditions. Background Art

[0002] Channels are the main link in the water distribution process of irrigation areas. The vast majority (more than 90%) of the water loss in the path from the water source to the crops is channel leakage loss. Excessive leakage loss is also one of the main reasons for the low efficiency of agricultural water use. Lining the channel with low permeability materials can not only significantly reduce the channel leakage, but also prevent channel erosion and siltation to reduce channel management costs. It is a widely used anti-seepage method at home and abroad. Due to the simple construction of concrete and anti-seepage membranes and good anti-seepage effects, composite linings composed of concrete, anti-seepage membranes or both are the most widely used in actual use. As more and more channels use channel lining for anti-seepage, accurately calculating the leakage of lined channels is of great significance for evaluating the utilization efficiency of irrigation water, evaluating the benefits of lining projects, formulating accurate irrigation plans and managing irrigation areas, improving the utilization efficiency of water resources and promoting the sustainable use of water resources.

[0003] At present, there are analytical solutions, empirical formulas, and numerical calculation methods for calculating channel leakage. The actual channel bed soil permeability coefficient has large spatial variability. The boundary conditions and initial conditions assumed in the equation during the derivation of the analytical solution are difficult to meet, and the final parameter solution process is more complicated than the general empirical formula. Therefore, analytical solutions are not often used in practical applications, especially for solving the leakage of layered soil and lined channels. The empirical formula can calculate the leakage rate of lined channels simply and quickly. However, the lining parameters in the empirical formula are only a fixed value that changes with the lining material, or a relatively wide range is given. The calculation does not consider the weakening of the lining effect over time and the change in leakage after cracks and holes appear. Therefore, the empirical formula method will produce large errors in calculating the leakage rate of lined channels. When calculating earth channels, since the existing empirical formula does not take into account the influence of layered soil, it is difficult to apply it directly in practice. Numerical calculation methods can well adapt to various boundary conditions to solve channel leakage problems. Through simulation, the changes in channel leakage in time and space and the response of groundwater and soil moisture content to channel leakage can be obtained. However, this method requires a large number of iterative steps during calculation, has low calculation efficiency, and may not converge.

[0004] Accurate evaluation of channel leakage losses in applications such as irrigation area design, canal water utilization efficiency evaluation, and water rights conversion of channel linings requires a more precise assessment of channel leakage under the actual stratified soil and lining forms of the irrigation area and the presence of cracks and holes, a method for calculating earth channel leakage under stratified soil conditions, and a mathematical relationship between lining permeability parameters and the degree of channel damage, in order to develop a more efficient and accurate method for calculating channel leakage. Summary of the invention

[0005] One object of the present invention is to address the deficiencies of the prior art and provide a method for calculating channel leakage that is suitable for layered soil and lining conditions. The method calculates channel leakage based on channel cross-sectional parameters, channel bed layered soil parameters, and lining parameters, thereby effectively ensuring the accuracy of the calculation of lined channel leakage loss.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A method for calculating channel seepage applicable to layered soil and lining conditions comprises the following steps:

[0008] Step 1: Collect the basic channel section parameters, soil parameters and parameters of different lining schemes;

[0009] Step 2: Based on the channel section parameters and soil parameters collected in step 1, a numerical model of channel seepage loss without lining is constructed;

[0010] Step 3, using the channel seepage loss numerical model obtained in step 2, simulate the channel seepage process and channel seepage amount under different channel section parameters, soil parameters and boundary conditions, and generate a data set based on this;

[0011] Step 4: Taking channel section parameters and soil parameters as independent variables, a multivariate linear regression model of channel leakage is constructed based on a part of the data in the data set, and the remaining data is used to test the multivariate linear regression model, which is then used as a channel leakage calculation model under unlined conditions.

[0012] Step 5: According to the change of seepage volume of the channel with or without lining, a calculation model of seepage reduction coefficient for different lining schemes is constructed;

[0013] Step 6: Combine the channel leakage calculation model in step 4 with the calculation models of each seepage reduction coefficient in step 5 to obtain a calculation model for calculating channel leakage under different lining schemes.

[0014] Furthermore, the channel cross-section parameters include channel bottom width, channel water depth, and channel slope coefficient, and the soil parameters include saturated permeability coefficient and moisture characteristic curve data of each layer of soil.

[0015] Furthermore, the lining scheme includes concrete lining and geomembrane lining. The parameters of concrete lining include the permeability coefficient of concrete material, crack width, crack length and position, and the parameters of geomembrane lining include the permeability coefficient of geomembrane, position and area of ​​holes.

[0016] Furthermore, the numerical model of channel leakage loss constructed in step 2 is:

[0017]

[0018] Where θ is the volumetric moisture content of soil; t is time; z is the Z-axis coordinate of the soil in the vertical direction, with the ground as the 0 point and upward as the positive direction; x is the X-axis coordinate of the soil in the horizontal direction, that is, perpendicular to the direction of the channel, with the channel axis as the 0 point; K(h) is the unsaturated hydraulic conductivity of the soil, which is a function of the soil water potential h and is determined according to the soil moisture characteristic curve; h is the soil water potential.

[0019] Furthermore, the multivariate linear regression model of channel leakage constructed in step 4 is:

[0020]

[0021] Where: S s is the leakage rate of the earth channel; k and α are empirical parameters; i c is the stable leakage rate of the channel; f1, f2 and f3 represent three multivariate linear functions respectively; b is the channel bottom width; m is the channel slope coefficient; h is the channel water depth; Ks is the saturated permeability coefficient of each soil layer; the subscript n represents a total of n layers.

[0022] Furthermore, in step 5, the calculation model of the reduction factor of the concrete lining is:

[0023]

[0024] Where: β c is the reduction factor of concrete lining; K sl is the equivalent permeability coefficient of concrete lining; K soil is the permeability coefficient of the channel soil; B is the water surface width of the channel cross section; C is a dimensionless coefficient, interpolated from the values ​​of B / h and the slope coefficient m, h is the soil water potential; δ is the thickness of the lining; K sc is the permeability coefficient of the concrete lining material; l c is the length of the crack; subscript i represents the i-th crack; C k is the contribution rate of the crack permeability coefficient, representing the increase in the equivalent permeability coefficient caused by the crack per unit length; a is C in the double logarithmic curve k With crack width d f The slope of a straight line; df0 and d f are the actual width and equivalent width of the crack respectively; C kmax It follows d f Increase, C k The maximum value of d fs It is C k No longer follow f Increased critical crack width value; p f It is an equivalent multiple of the crack width area.

[0025] Furthermore, the reduction factor calculation model of geomembrane lining in step 5 is as follows:

[0026]

[0027] Where: β g is the reduction factor of geomembrane lining; D g is the damage degree of geomembrane lining, dimensionless; β g，min K is the reduction factor when the geomembrane lining has no holes; soil is the permeability coefficient of the channel soil, K sg is the leakage coefficient of the geomembrane, T is the thickness of the geomembrane, B is the water surface width of the channel cross section; C is a dimensionless coefficient, which is interpolated according to the value of B / h and the slope coefficient m, and h is the soil water potential; a d and a g are the area of ​​the holes in the underwater geomembrane lining and the area of ​​the geomembrane; a de is the equivalent area of ​​holes in the underwater geomembrane lining; p g It is an equivalent multiple of the hole area.

[0028] Another object of the present invention is to provide a method for determining a lining scheme, determine the design target of channel leakage, continuously adjust the parameters of the calculation model of the channel leakage of the above-mentioned different lining schemes and simulate the channel leakage. When the design target is reached, the lining scheme and its corresponding parameters are output at this time.

[0029] The present invention also provides a system for implementing the above-mentioned channel leakage calculation method applicable to layered soil and lining conditions, comprising:

[0030] Data collection module, used to collect basic channel section parameters, soil parameters and parameters of different lining schemes;

[0031] A numerical model building module is used to build a numerical model of channel seepage loss under unlined conditions based on the channel section parameters and soil parameters collected by the data collection module;

[0032] A data set generation module is used to simulate the channel seepage process and channel seepage amount under different channel section parameters, soil parameters and boundary conditions according to the channel seepage loss numerical model obtained by the numerical model construction module, and generate a data set based on this;

[0033] The model building module is used to construct a multivariate linear regression model of channel leakage based on a part of the data in the data set generated by the data set generation module, and to use the remaining data for testing, and to construct a corresponding seepage reduction coefficient calculation model based on the change in the seepage of the channel with or without lining;

[0034] The channel leakage calculation module is used to combine the channel leakage calculation model under unlined conditions obtained by the model building module with the seepage reduction coefficient calculation model of different lining schemes to obtain a calculation model for calculating the channel leakage of different lining schemes, and calculate the channel leakage of each lining scheme based on the obtained model.

[0035] Furthermore, it also includes a lining scheme determination module, which is used to continuously adjust the parameters of the channel leakage calculation model of different lining schemes according to the design target of the channel leakage, and input them into the channel leakage calculation module to simulate the channel leakage. When the design target is achieved, the lining scheme and its corresponding parameters at this time are output.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention calculates the seepage rate of the earth channel according to the channel cross-sectional parameters of the channel bed and the parameters of each layer of soil. The parameters have clear physical meanings and are used for various types of layered soil channels. The soil migration formula constructed through numerical simulation has a theoretical basis and is applicable to different conditions. The reduction coefficients of concrete and geomembrane linings no longer rely solely on empirical values, but have a clear quantitative relationship with the permeability coefficient of the lining material and the characteristics of the damage (cracks and holes) that appear. This method can be applied to various types of irrigation areas, various soils and lining conditions, and provides a more accurate and efficient way for calculating and evaluating channel leakage. In addition, the present invention can also generate channel parameters and lining schemes that meet the corresponding channel leakage loss targets, providing more intuitive technical support for actual channel design and channel anti-seepage. Construction according to channel parameters and management of lining schemes can effectively ensure the anti-seepage effect of the channel. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart of a method for calculating channel leakage applicable to layered soil and lining conditions provided by an embodiment of the present invention;

[0038] Figure 2 It is a diagram illustrating boundary conditions during numerical simulation of an embodiment of the present invention;

[0039] Figure 3A comparison diagram of the steady seepage rates predicted by the multivariate linear regression models for large water depth and small water depth according to an embodiment of the present invention;

[0040] Figure 4 This is a graph showing the variation of channel leakage with use time under the condition that the equivalent permeability coefficient of concrete lining increases year by year in an embodiment of the present invention;

[0041] Figure 5 This is a graph showing how channel leakage changes with use time under the condition that the hole density of the anti-seepage membrane lining increases year by year in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be described clearly and completely below in combination with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0044] The present invention will be further described below in conjunction with specific embodiments, but they are not intended to be limiting of the present invention.

[0045] like Figure 1 As shown, the present invention discloses a channel leakage calculation method applicable to layered soil and lining conditions, comprising the following steps:

[0046] Step 1: Collect the basic channel section parameters, soil parameters and parameters of different lining schemes;

[0047] In this embodiment, the test area is in a certain irrigation area of ​​the Hetao Irrigation District in Inner Mongolia, and the channel section parameters include channel water depth, channel bottom width, and channel slope coefficient. The soil under the channel is divided into three layers, and examples of soil data for each layer are shown in Table 1.

[0048] Table 1 Main parameters of each layer of soil in a typical channel

[0049]

[0050] The lining scheme includes concrete lining and geomembrane lining. The parameters of concrete lining include the permeability coefficient of concrete material, crack width, crack length and position; the parameters of geomembrane lining include the permeability coefficient of geomembrane, position and area of ​​holes.

[0051] Step 2. Based on the channel section parameters and soil parameters collected in step 1, a numerical model of channel seepage loss without lining is constructed;

[0052] Under lining conditions, channel seepage loss depends on the movement of water in the soil. Therefore, the soil water movement model is constructed as a numerical model of channel seepage loss under unlined conditions. Specifically, the soil water movement model is as follows:

[0053]

[0054] Wherein, θ is the volumetric moisture content of soil, dimensionless; t is time, d; z is the vertical Z-axis coordinate of the soil, with the ground as the 0 point and upward as the positive direction, cm; x is the horizontal X-axis coordinate of the soil (perpendicular to the direction of the channel), with the channel axis as the 0 point, cm; K(h) is the unsaturated hydraulic conductivity of the soil, which is a function of the soil water potential h and is determined according to the soil moisture characteristic curve; h is the soil water potential.

[0055] Step 3. Use the channel seepage loss numerical model in step 2 to simulate the channel seepage process and channel seepage amount under different channel sections, channel water depths, soil parameters and boundary conditions, and generate a data set based on this;

[0056] Figure 2 This is a simplified diagram of the channel simulation boundary conditions. It is assumed that the channel section is an axisymmetric structure, where AI is the symmetry axis of the channel section, and the channel is symmetrically divided into two parts by the symmetry axis. Since the channel is a temporary test area, it is necessary to inject water into the test channel to a certain water level before conducting the hydrostatic test. The AB side and the BC side can be set as variable water depth boundaries; the CD side, the DE side, the EF side, and the FG side are connected to the atmosphere, and the boundary conditions are set as atmospheric boundaries; the AI ​​side is set as a zero flux boundary according to the symmetry of the seepage domain; the groundwater depth in the study area during the simulation is about 2.2 to 2.4 meters. Since there is little vertical exchange of the groundwater zone in the simulation domain, the vertical exchange of groundwater below 10 meters can be ignored. Therefore, the bottom boundary of the simulation domain is set to 10 meters below the surface as a zero flux boundary. When the lateral simulation domain width is 15 times the channel bottom width, the influence of the lateral boundary on channel leakage can be excluded, so GH is also set as a zero flux boundary. Under the above boundary conditions, this embodiment uses the channel leakage loss numerical model to simulate the channel leakage process and channel leakage amount of different channel sections, channel water depths, and soil parameters, and obtains a total of 787 sets of data, which are organized into a data set.

[0057] Step 4: Taking channel section parameters and soil parameters as independent variables, a multivariate linear regression model of channel leakage is constructed based on a part of the data in the data set, and the remaining data is used to test the multivariate linear regression model, which is then used as a channel leakage calculation model under unlined conditions.

[0058] Based on a part of the data set in step 3 (generally about 70%, which can also be determined according to specific needs), the channel section parameters (channel water depth, channel bottom width, channel slope coefficient) and soil parameters are used as independent variables to construct a multivariate linear regression model of water leakage in the earth channel:

[0059]

[0060] Where: S s is the leakage rate of the channel soil channel, m 3 / (s·m); k and α are empirical parameters; ic is the stable leakage rate of the channel, m 3 / (s·m); f1, f2 and f3 represent three multivariate linear functions respectively; b is the channel bottom width, m; m is the channel slope coefficient, m / m; h is the channel water depth, m; Ks is the saturated permeability coefficient of each soil layer, m / s; the subscript n represents a total of n layers.

[0061] The remaining data (generally about 30%) in the data set are then used to test the constructed multiple linear regression model. Once the accuracy is achieved, it can be used as a channel leakage calculation method under unlined conditions.

[0062] In this embodiment, some scenario cases in the data set used to construct the multiple linear regression model are shown in Table 2, with a total of 625 groups; scenario cases used to verify the multiple linear regression model are shown in Table 3, with a total of 162 groups. Finally, the multiple linear regression model tested in this embodiment consists of two parts that are respectively applicable to large water depths (water depths above 1m) and small water depths (water depths below 1m);

[0063] The formula applicable to large water depths is as follows:

[0064]

[0065] Where: i is the channel leakage rate, cm3 / s; t is the infiltration time, s; i c is the steady permeability rate, cm 3 / s; l is the channel length, m; h is the water depth, m; b is the bottom width, m; m is the slope coefficient; ks1 is the saturated hydraulic conductivity of the soil layer from 0 to 60 cm, m / d; ks2 is the saturated hydraulic conductivity of the soil layer from 60 to 160 cm, m / d; ks3 is the saturated hydraulic conductivity of the soil layer from 160 to 300 cm, m / d; ks is the saturated hydraulic conductivity of the channel soil, m / d.

[0066] The formula applicable to small water depths is as follows:

[0067]

[0068] Where: i is the channel leakage rate, cm3 / s; t is the infiltration time, s; ic is the steady permeability rate, cm 3 / s; l is the channel length, m; h is the water depth, m; b is the bottom width, m; m is the slope coefficient; ks1 is the saturated hydraulic conductivity of the soil layer from 0 to 60 cm, m / d; ks2 is the saturated hydraulic conductivity of the soil layer from 60 to 160 cm, m / d; ks3 is the saturated hydraulic conductivity of the soil layer from 160 to 300 cm, m / d; ks is the saturated hydraulic conductivity of the channel soil, m / d.

[0069] The prediction results of the two formulas are shown in Figure 3 .

[0070] Table 2 Simulation scenarios when constructing multi-factor models

[0071]

[0072] Table 3 Simulation scenarios for validating the multi-factor model

[0073]

[0074] Note: Combinations B and C in the table are verification combinations under large water depth and small water depth conditions respectively.

[0075] Step 5: According to the change of seepage volume of the channel with or without lining, a calculation model of seepage reduction coefficient for different lining schemes is constructed;

[0076] The leakage of the lined channel is equal to the lining reduction coefficient multiplied by the leakage of the channel without lining. Under this premise, combined with the basic channel section parameters, soil parameters and lining parameters including the permeability coefficient, crack width, crack length and crack position of the concrete lining, the permeability coefficient, hole position and size of the geomembrane lining, the calculation model of the seepage reduction coefficient of the channel lining is constructed. Among them, the calculation model of the seepage reduction coefficient of the concrete lining is as follows:

[0077]

[0078] Where: β c is the reduction factor of concrete lining, dimensionless; K sl is the equivalent permeability coefficient of concrete lining, m / s; K soil is the permeability coefficient of the channel soil, m / s; B is the water surface width of the channel cross section, m; C is a dimensionless coefficient, which is interpolated according to the values ​​of B / h and the slope coefficient m; δ is the thickness of the lining, m; When calculating the leakage of small channels, it is also necessary to consider the effect of soil capillary action on leakage. In this case, parameter C is calculated according to B / h. v and slope coefficient m interpolation, h v Equal to the channel water depth plus half of the maximum capillary rise. K scis the permeability coefficient of concrete lining material, m / s; l c is the length of the crack, m; subscript i represents the i-th crack; C k is the contribution rate of the crack permeability coefficient, representing the increase in the equivalent permeability coefficient caused by the crack per unit length, 1 / s; a is C in the double logarithmic curve k With crack width d f The slope of a straight line, [-]; d f0 and d f are the actual width and equivalent width of the crack, mm; C kmax It follows d f Increase, C k Maximum value, 1 / s; d fs It is C k No longer follow f Increased critical crack width value, mm; p f It is an equivalent multiple of the crack width area;

[0079] The reduction factor calculation model for geomembrane lining is as follows:

[0080]

[0081] Where: β g is the reduction factor of geomembrane lining, dimensionless; D g is the damage degree of geomembrane lining, dimensionless; β g，min K is the reduction factor when the geomembrane lining has no holes, dimensionless; sg is the leakage coefficient of geomembrane, T is the thickness of geomembrane, and the meanings of other symbols are the same as those in the calculation formula of reduction coefficient of concrete lining; a d and a g are the area of ​​the holes in the underwater geomembrane lining and the area of ​​the geomembrane, m 2 ; a de is the equivalent area of ​​the holes in the underwater geomembrane lining m 2 ;p g It is an equivalent multiple of the hole area.

[0082] Combined with the measured data, the equivalent multiples of the crack width area in the reduction factor of the concrete lining and the equivalent multiples of the hole density in the reduction factor of the geomembrane lining are calibrated. When the experimental measured data is insufficient, the equivalent multiples of the crack width area are difficult to calibrate, and the equivalent permeability coefficient of the concrete lining can be directly calibrated according to the measured leakage data. In this embodiment, the measured test data of a concrete lined channel is used to calibrate the equivalent permeability coefficient of the concrete lining. The channel is concrete lined with a thickness of 0.1m, a channel cross-section bottom width of 1.2m, a slope coefficient of 1.5, and the permeability coefficients of the three layers of soil are 0.31, 0.31 and 0.66m / d respectively. Before and after the lining, when the water depth is 0.82m, the leakage rate of the channel is 0.196cm 2 / s and 0.096cm 2 / s, the corresponding lining reduction factor is 0.49. In the formula of step 6, the water surface width B is 3.66m, and the channel bed soil permeability coefficient K soil is 0.31m / d, coefficient C is 2.35, so the Ks is determined l 2.05×10 -7 m / s.

[0083] In this embodiment, the hole density equivalent times is determined by using the measured test data of a geomembrane lined channel. In this channel, the specific parameter values ​​are as follows: the measured reduction coefficient of the anti-seepage membrane lining is 0.89; β g，min is the reduction factor when the geomembrane lining has no holes. Since the permeability coefficient is less than 1.0×10 -10 m / s, the value is 0.001; the measured a d and a g 48mm respectively 2 and 1.91×10 6 mm, so the p g It is 100.

[0084] Step 6: Combining the channel leakage calculation model in step 4 with the calculation models of each seepage reduction coefficient in step 5 to obtain a calculation model for calculating channel leakage in different lining schemes;

[0085] The channel leakage calculation model in step 4 is multiplied by the calculation model of each seepage reduction coefficient in step 5 to obtain the calculation model for calculating the channel leakage of different lining schemes. For an unlined channel with a channel cross-section bottom width of 1.2m, a slope coefficient of 1.5, and three layers of soil with permeability coefficients of 0.31, 0.31 and 0.66m / d respectively, the soil channel leakage rate is 0.196cm when the channel water depth is 1m. 2 / s. According to the results of step 5, the equivalent permeability coefficient of concrete lining can be calculated separately at 1.0×10 -10 ~1.0×10-6 The leakage rate under the condition of m / s change and increase by one order of magnitude every 2.5 years (see the results in Figure 4 ), and the use of geomembrane lining, the actual density of holes increases by 3.713×10 -7 Channel leakage rate under the conditions (see Figure 5 ).

[0086] This embodiment also provides a method for determining a lining scheme. First, the design target of channel leakage is determined, the parameters of the calculation model of channel leakage of different lining schemes are continuously adjusted, and the channel leakage is simulated. When the design target is reached, the lining scheme and its corresponding parameters are output. In this example, the design target is to ensure that the leakage rate of the lining channel in the first 10 years is less than 50% of the earthen channel. Among the two lining schemes, since the leakage rates of concrete and geomembrane linings are 66% and 28% of the earthen channel leakage rate in the 10th year, respectively, the geomembrane lining scheme is selected.

[0087] The present invention also provides a system for implementing the above-mentioned channel leakage calculation method applicable to layered soil and lining conditions, comprising:

[0088] Data collection module, used to collect basic channel section parameters, soil parameters and parameters of different lining schemes;

[0089] A numerical model building module is used to build a numerical model of channel seepage loss under unlined conditions based on the channel section parameters and soil parameters collected by the data collection module;

[0090] A data set generation module is used to simulate the channel seepage process and channel seepage amount under different channel section parameters, soil parameters and boundary conditions according to the channel seepage loss numerical model obtained by the numerical model construction module, and generate a data set based on this;

[0091] The model building module is used to construct a multivariate linear regression model of channel leakage based on a part of the data in the data set generated by the data set generation module, and to use the remaining data for testing, and to construct a corresponding seepage reduction coefficient calculation model based on the change in the seepage of the channel with or without lining;

[0092] The channel leakage calculation module is used to combine the channel leakage calculation model under unlined conditions obtained by the model building module with the seepage reduction coefficient calculation model of different lining schemes to obtain a calculation model for calculating the channel leakage of different lining schemes, and calculate the channel leakage of each lining scheme based on the obtained model.

[0093] In another embodiment, the system of the method for calculating the leakage of a lined channel also includes a lining scheme determination module, which is used to continuously adjust the parameters of the calculation model of the channel leakage of different lining schemes according to the design target of the channel leakage, and input them into the channel leakage calculation module to simulate the channel leakage. When the design target is reached, the lining scheme and its corresponding parameters at this time are output.

[0094] The above are only preferred embodiments of the present invention, and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the contents of the specification of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calculating channel leakage suitable for layered soil and lining conditions, characterized in that: The following steps are involved: Step 1: Collect the basic channel section parameters, soil parameters and parameters of different lining schemes; Step 2: Based on the channel section parameters and soil parameters collected in step 1, a numerical model of channel seepage loss without lining is constructed; Step 3, using the channel seepage loss numerical model obtained in step 2, simulate the channel seepage process and channel seepage amount under different channel section parameters, soil parameters and boundary conditions, and generate a data set based on this; Step 4: Taking channel section parameters and soil parameters as independent variables, a multivariate linear regression model of channel leakage is constructed based on a part of the data in the data set, and the remaining data is used to test the multivariate linear regression model, which is then used as a channel leakage calculation model under unlined conditions. Step 5: According to the change of seepage volume of the channel with or without lining, a calculation model of seepage reduction coefficient for different lining schemes is constructed; Step 6: Combine the channel leakage calculation model in step 4 with the calculation models of each seepage reduction coefficient in step 5 to obtain a calculation model for calculating channel leakage under different lining schemes.

2. The channel leakage calculation method applicable to layered soil and lining conditions according to claim 1 is characterized in that: In step 1, the channel cross-section parameters include channel bottom width, channel water depth, and channel slope coefficient, and the soil parameters include the saturated permeability coefficient and moisture characteristic curve of each layer of soil.

3. The channel leakage calculation method applicable to layered soil and lining conditions according to claim 1 is characterized in that: The lining scheme includes concrete lining and geomembrane lining. The parameters of concrete lining include the permeability coefficient of concrete material, crack width, crack length and position; the parameters of geomembrane lining include the permeability coefficient of geomembrane, position and area of ​​holes.

4. The channel leakage calculation method applicable to layered soil and lining conditions according to claim 2 is characterized in that: The numerical model of channel leakage loss constructed in step 2 is: In the formula, θ is the soil volume moisture content; t is the time; z is the Z-axis coordinate of the soil in the vertical direction, with the ground as the 0 point and upward as the positive direction; x is the X-axis coordinate of the soil in the horizontal direction, that is, perpendicular to the direction of the channel, with the channel axis as the 0 point; K(h) is the unsaturated hydraulic conductivity of the soil, which is a function of the soil water potential h and is determined according to the soil moisture characteristic curve; h is the soil water potential.

5. The channel leakage calculation method applicable to layered soil and lining conditions according to claim 2 is characterized in that: The multivariate linear regression model of channel leakage constructed in step 4 is: Where: S s is the leakage rate of the earth channel; k and α are empirical parameters; i c is the stable leakage rate of the channel; f1, f2 and f3 represent three multivariate linear functions respectively; b is the channel bottom width; m is the channel slope coefficient; h is the channel water depth; Ks is the saturated permeability coefficient of each soil layer; the subscript n represents a total of n layers.

6. The channel leakage calculation method applicable to layered soil and lining conditions according to claim 3 is characterized in that: In step 5, the calculation model of the reduction factor of concrete lining is: Where: β c is the reduction factor of concrete lining; K sl is the equivalent permeability coefficient of concrete lining; K soil is the permeability coefficient of the channel soil; B is the water surface width of the channel cross section; C is a dimensionless coefficient, interpolated from the values ​​of B / h and the slope coefficient m, where h is the soil water potential; δ is the thickness of the lining; K sc is the permeability coefficient of the concrete lining material; l c is the length of the crack; subscript i represents the i-th crack; C k is the contribution rate of the crack permeability coefficient, representing the increase in the equivalent permeability coefficient caused by the crack per unit length; a is C in the double logarithmic curve k With crack width d f The slope of a straight line; d f0 and d f are the actual width and equivalent width of the crack respectively; C kmax It follows d f Increase, C k The maximum value of d fs It is C k No longer follow f Increased critical crack width value; p f It is an equivalent multiple of the crack width area.

7. The channel leakage calculation method applicable to layered soil and lining conditions according to claim 3 is characterized in that: The reduction factor calculation model for geomembrane lining in step 5 is as follows: Where: β g is the reduction factor of geomembrane lining; D g is the damage degree of geomembrane lining, dimensionless; β g，min K is the reduction factor when the geomembrane lining has no holes; soil is the permeability coefficient of the channel soil, K sg is the leakage coefficient of the geomembrane, T is the thickness of the geomembrane, B is the water surface width of the channel cross section; C is a dimensionless coefficient, which is interpolated according to the value of B / h and the slope coefficient m, and h is the soil water potential; a d and a g are the area of ​​the holes in the underwater geomembrane lining and the area of ​​the geomembrane; a de is the equivalent area of ​​holes in the underwater geomembrane lining; p g It is an equivalent multiple of the hole area.

8. A method for determining a lining scheme, characterized in that: Determine the design target of channel leakage, continuously adjust the parameters of the calculation model of channel leakage of different lining schemes described in any one of claims 1-7 and simulate the channel leakage. When the design target is reached, output the lining scheme and its corresponding parameters at this time.

9. A system for implementing the channel leakage calculation method applicable to layered soil and lining conditions as described in claims 1-7, characterized in that: include: Data collection module, used to collect basic channel section parameters, soil parameters and parameters of different lining schemes; A numerical model building module is used to build a numerical model of channel seepage loss under unlined conditions based on the channel section parameters and soil parameters collected by the data collection module; A data set generation module is used to simulate the channel seepage process and channel seepage amount under different channel section parameters, soil parameters and boundary conditions according to the channel seepage loss numerical model obtained by the numerical model construction module, and generate a data set based on this; The model building module is used to construct a multivariate linear regression model of channel leakage based on a part of the data in the data set generated by the data set generation module, and to use the remaining data for testing, and to construct a corresponding seepage reduction coefficient calculation model based on the change in the seepage of the channel with or without lining; The channel leakage calculation module is used to combine the channel leakage calculation model under unlined conditions obtained by the model building module with the seepage reduction coefficient calculation model of different lining schemes to obtain a calculation model for calculating the channel leakage of different lining schemes, and calculate the channel leakage of each lining scheme based on the obtained model.

10. The system for calculating channel leakage suitable for layered soil and lining conditions according to claim 9, characterized in that: It also includes a lining scheme determination module, which is used to continuously adjust the parameters of the channel leakage calculation model of different lining schemes according to the design target of channel leakage, and input them into the channel leakage calculation module to simulate the channel leakage. When the design target is achieved, the lining scheme and its corresponding parameters at this time are output.

Images