Channel leakage rate calculation method and system under groundwater jacking condition

Abstract

The invention provides a channel leakage rate calculation method and system under an underground water jacking condition. The method comprises the following steps: collecting parameters such as channel sections, soil properties, channel spacing and underground water burial depth; and establishing a leakage numerical model under the conditions of free infiltration and different underground water burial depths, simulating a leakage process under various parameter combinations, and generating a data set. A free leakage model is constructed based on a multi-output decision tree regression algorithm, a jacking coefficient calculation model is established in combination with different groundwater jacking conditions, and the free leakage model and the jacking coefficient calculation model are coupled to obtain a leakage rate calculation model suitable for groundwater jacking; and adjusting channel parameters or an underground water level control scheme by taking the condition that the channel leakage rate is smaller than a design value under the underground water jacking condition as a design target. According to the method, the channel leakage rate is calculated on the basis of channel water depth, section parameters, channel spacing, soil parameters and the like, and the accuracy of channel leakage loss calculation in the underground water shallow buried area is improved.

Description

Technical Field

[0001] This invention belongs to the technical field of agricultural irrigation water distribution and irrigation water efficiency simulation, and particularly relates to a system for calculating channel leakage rate under groundwater backwater conditions. Background Technology

[0002] Canal water conveyance is a crucial component of important water conservancy projects such as agricultural irrigation, urban and rural water supply, and ecological water replenishment. Canal leakage rate is a core parameter for assessing water conveyance efficiency, calculating water resource loss, and designing anti-seepage measures for engineering projects. Accurately calculating the canal leakage rate is of paramount importance for the efficient utilization of water resources, the prevention of secondary soil salinization, and the assessment of regional water-salt balance.

[0003] In existing technologies, the calculation methods for channel leakage rates are mainly based on classical groundwater dynamics theory, such as the Kosgakov formula and the wetted perimeter empirical method considering steady-state seepage conditions, as well as numerical simulation methods considering unsteady-state seepage (such as software based on finite element or finite difference methods like MODFLOW and FEFLOW). However, these traditional methods have obvious limitations and shortcomings when applied to working conditions where the "groundwater backing" effect exists.

[0004] Specifically, traditional analytical formulas are typically based on a series of idealized assumptions, such as the existence of an impermeable layer (waterproof base) beneath the channel, or the assumption that the groundwater level is much lower than the channel level and its influence is negligible. However, in actual engineering projects, especially in areas with high groundwater levels and close connections between the channel bed and shallow aquifers, groundwater exerts a significant "backing" effect on the infiltrative flow in the channel. This backing effect significantly alters the seepage field morphology around the channel, reducing the actual hydraulic gradient and thus drastically decreasing the leakage. In such cases, using traditional formulas that ignore the groundwater backing effect will severely overestimate the leakage, leading to a large discrepancy between the calculated results and the actual situation, failing to provide a reliable basis for precise water resource management and engineering decision-making. Existing groundwater backing coefficients for channel leakage use channel flow and groundwater depth as independent variables, neglecting the influence of other factors such as channel depth, cross-section, and soil parameters.

[0005] On the other hand, although numerical simulation can theoretically simulate complex boundary conditions (such as groundwater backing), its modeling process is cumbersome, it is highly dependent on the accuracy of hydrogeological parameters (such as permeability coefficient, specific yield, etc.), and it is costly to calculate and time-consuming. It requires professional personnel to operate, making it difficult to widely apply in engineering practices that require rapid evaluation and a large amount of calculation (such as regional water resources planning, rapid comparison and selection of channel seepage prevention schemes, etc.).

[0006] Therefore, there is an urgent need in this field for a method to calculate channel leakage rate that can accurately characterize the groundwater backwater effect, has high computational efficiency, and is easy to promote and apply, so as to overcome the inherent defects of existing analytical methods, empirical formula methods, and numerical simulation methods. Summary of the Invention

[0007] The purpose of this invention is to address the shortcomings of existing technologies by providing a method for calculating channel leakage rate under groundwater backwater conditions. This method is based on channel water depth, channel cross-sectional parameters, channel bed stratified soil parameters, and groundwater burial depth parameters, thereby effectively ensuring the accurate calculation of channel leakage loss under groundwater backwater conditions.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: A method for calculating the seepage rate of a channel under groundwater backwater conditions includes the following steps: Collect basic channel cross-section and spacing parameters, soil parameters, and groundwater depth parameters; Based on the collected channel cross-sectional parameters and soil parameters, a numerical model of channel leakage loss under free infiltration conditions and different groundwater depths was constructed; and the channel leakage process and leakage rate under different parameter combinations were simulated to generate a dataset. Using channel cross-sectional parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables, a multi-output decision tree regression model for channel leakage rate applicable to different channel water depths was constructed based on partial data in the dataset. The remaining data in the dataset were used to test the multi-output decision tree regression model, and the test results were used as the channel free leakage calculation model under the condition of no top support. Based on the change in seepage rate of channels with and without backing, a calculation model for the groundwater backing coefficient under different backing conditions is constructed. The channel free seepage calculation model is coupled with the groundwater backwater coefficient calculation model to calculate the channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing and groundwater burial depth. With the goal of ensuring that the leakage rate of the channel is less than the design value under the condition of groundwater backing, adjust the channel parameters or the groundwater level control scheme.

[0009] Furthermore, the channel cross-sectional parameters, soil parameters, and groundwater parameters include, but are not limited to, channel longitudinal and transverse cross-sectional data, channel water depth data, channel soil stratification data, soil saturation permeability coefficient and moisture characteristic curve data for each soil layer, channel spacing data, and initial soil moisture content determined based on groundwater depth.

[0010] Furthermore, the groundwater backing conditions include the backing effect caused by mutual backing between channels or the initial groundwater depth being relatively high.

[0011] Furthermore, the numerical model for channel leakage loss is as follows: ; In the formula, θ Soil volumetric water content, dimensionless; t For time, h; z is the vertical Z-axis coordinate of the soil, with the ground as 0 and upward as the positive direction, in cm; x is the horizontal X-axis coordinate of the soil, with the channel axis as 0, in cm; K ( h ) represents the unsaturated hydraulic conductivity of the soil, which is a function of the soil water potential h; h Soil matrix potential or pressure potential.

[0012] Furthermore, in constructing the multi-output decision tree regression model, the independent variables are the channel bottom width, slope coefficient, channel water depth, saturated permeability coefficient of each soil layer, and initial groundwater depth; the regression output variable is the empirical parameter k. and the stable leakage rate of the channel i c .

[0013] Furthermore, the calculation model for free leakage in the channel under the condition of no support is as follows: ; In the formula: S s It is the seepage rate of the earthen canal, in meters. 3 / (h·m); k and These are empirical parameters; i c It is the stable leakage rate of the channel, m 3 / (h·m); t is time, h.

[0014] Furthermore, the calculation model for the groundwater backwater coefficient under different backwater conditions is as follows:

[0015] Wherein, γ is the groundwater backwater coefficient, which is dimensionless; H g is the groundwater depth of the channel, in meters; r1 and r2 are parameters characterizing the influence of groundwater depth on channel leakage, represented by a Logistic function; r max and g max It is the maximum value of r1 and r2; L It refers to the channel spacing, in meters (m). h It refers to the depth of the channel, in meters (m). Ks 1 is the saturated permeability coefficient of the canal bed soil, in m / s; , , It is an intermediate parameter, dimensionless.

[0016] Furthermore, the channel seepage rate was calculated under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing, and groundwater depths as follows:

[0017] In the formula: S ga It is the stable infiltration rate of the channel under the condition of groundwater backwater, m 3 / (h·m); S fa It is the free infiltration rate of the channel calculated by the free leakage calculation model, m 3 / (h·m).

[0018] Furthermore, the channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing, and groundwater depth can be calibrated based on data such as the measured groundwater depth and the corresponding channel infiltration rate; or the channel free infiltration rate can be calculated directly.

[0019] On the other hand, the present invention provides a system for calculating channel leakage rate under groundwater backwater conditions, comprising: Data collection module: It is used to collect basic channel cross-sectional parameters, soil parameters, and groundwater depth parameters; The channel seepage loss numerical model construction module is used to construct a channel seepage loss numerical model under free infiltration conditions and different groundwater depths based on collected channel cross-section parameters and soil parameters; and to simulate the channel seepage process and channel seepage rate under different parameter combinations to generate a dataset. The decision tree regression model construction module is used to construct a multi-output decision tree regression model of channel leakage rate applicable to different channel water depths based on partial data in the dataset, using channel cross-section parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables. The remaining data in the dataset is used to test the multi-output decision tree regression model, and the test results are used as the channel free leakage calculation model under the condition of no top support. Groundwater backwater coefficient calculation model construction module: It is used to construct groundwater backwater coefficient calculation models under different backwater conditions based on the change in the seepage rate of channels with and without backwater. Model Coupling Module: It is used to couple the channel free seepage calculation model with the groundwater backwater coefficient calculation model to calculate the channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing and groundwater depth. Parameter adjustment module: It is used to adjust channel parameters or groundwater level control scheme with the goal of ensuring that the channel leakage rate is less than the design value under groundwater backing conditions.

[0020] Compared with the prior art, the present invention has the following beneficial effects: This invention calculates the groundwater backwater coefficient and seepage rate of a canal based on the canal bed's water depth, cross-sectional parameters, soil parameters at each layer, canal spacing, and groundwater depth. The parameters have clear physical meanings and are applicable to various levels and types of canals, avoiding the inconsistent results obtained by using only flow rate as the unit. The calculation formula under groundwater backwater conditions, constructed through numerical simulation and a multi-output decision tree regression model algorithm, has a theoretical basis, is applicable to different conditions, and has higher computational efficiency. This method is applicable to various irrigation areas and various soil and groundwater depth conditions, providing a more accurate and efficient way to assess canal seepage rates. Furthermore, this invention can generate canal parameters and groundwater level control schemes that meet corresponding canal seepage loss targets, providing more intuitive technical support for actual canal design and management. Construction and management based on canal parameters can effectively ensure the canal's water conveyance effect. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 is a flowchart of the method for calculating channel leakage rate under groundwater backing conditions provided by the present invention; Figure 2 illustrates the boundary conditions during the numerical simulation. Figure 3 shows the training effect of the multi-output regression model for channel free infiltration rate; Figure 4 shows the effect of the multi-output regression model for channel free infiltration rate during testing; Figure 5 shows the leakage rate of a channel under different groundwater burial depths. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] In specific implementation, the method proposed in the technical solution of this invention can be automatically executed by those skilled in the art using computer software technology. System devices for implementing the method, such as computer-readable storage media storing the corresponding computer program of the technical solution of this invention and computer equipment including the computer program running the corresponding computer program, should also be within the protection scope of this invention.

[0025] Example 1 like Figure 1 As shown in the figure, this embodiment provides a method for calculating the seepage rate of a channel under groundwater backwater conditions, including the following steps: Step 1: Collect basic channel cross-sectional parameters, soil parameters, and groundwater depth parameters; Step 2: Based on the collected channel cross-sectional parameters and soil parameters, construct a numerical model of channel leakage loss under free infiltration conditions and different groundwater depths; and simulate the channel leakage process and leakage rate under different parameter combinations to generate a dataset. Step 3: Using channel cross-section parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables, construct a multi-output decision tree regression model for channel leakage rate applicable to different channel water depths based on partial data in the dataset. Then, use the remaining data in the dataset to test the multi-output decision tree regression model. After testing, it is used as the channel free leakage calculation model under the condition of no top support. Step 4: Construct a calculation model for the groundwater backwater coefficient under different backwater conditions based on the change in the seepage rate of the channel with and without backwater. Step 5: Couple the channel free leakage calculation model with the groundwater backwater coefficient calculation model to calculate the channel leakage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing and groundwater depth. Step 6: Adjust the channel parameters or groundwater level control scheme with the goal of achieving a channel leakage rate that is less than the design value under groundwater backing conditions.

[0026] The channel cross-sectional parameters, soil parameters, and groundwater parameters in step 1 include, but are not limited to, channel longitudinal and transverse cross-sectional data, channel water depth data, channel soil stratification data, soil saturation permeability coefficient and moisture characteristic curve data for each layer, channel spacing data, and initial soil moisture content determined based on groundwater depth. In this embodiment, the test area is located within a specific irrigation district. According to the data, the soil beneath the channel is divided into three layers, and examples of soil data for each layer are shown in Table 1.

[0027] Table 1. Main parameters of soil layers in typical canals

[0028] In step 2, based on the channel cross-sectional parameters and soil parameters collected in step 1, a numerical model of channel seepage loss under the condition of no jacking is constructed as follows: ; In the formula, θ Soil volumetric water content, dimensionless; t For time, d; z is the vertical Z-axis coordinate of the soil, with the ground as 0 and upward as the positive direction, in cm; x is the horizontal X-axis coordinate of the soil (perpendicular to the channel direction), with the channel axis as 0, in cm; K ( h ) represents the unsaturated hydraulic conductivity of the soil, which is a function of the soil water potential h and is determined based on the soil moisture characteristic curve; h Soil water potential; A numerical model of channel seepage loss under unsupported conditions was used to simulate the channel seepage process and seepage rate under different channel cross-sections, water depths, soil parameters, and initial groundwater depths. A dataset was generated based on this simulation. The various parameters are shown in Table 2. There are 11 combinations of channel water depth and cross-section parameters, 7 groups of soil parameters, and 8 groups of groundwater depths. When setting the groundwater depth, the smaller the depth, the smaller the interpolation between adjacent scenarios. A total of 616 cases were used to construct the dataset after all three categories were combined. Table 2. Simulation Scenario Parameters for Training and Testing Machine Learning Algorithm Models

[0029] Figure 2 The simplified boundary condition diagram for the channel simulation is shown below. Assuming the channel cross-section is axisymmetric, AI is the axis of symmetry, dividing the channel symmetrically into two parts. Since the channel is a temporary test area, water needs to be injected to a certain level before the hydrostatic test. Therefore, sides AB and BC can be set as variable depth (head) boundaries; sides CD, DE, EF, and FG are connected to the atmosphere, and their boundary conditions are set as atmospheric boundaries; based on the symmetry of the seepage domain, side AI is set as a zero-flux boundary. Under free drainage conditions without channel backwater, the bottom IH of the simulation domain is set as the free drainage boundary. In this case, due to the limited area affected by seepage, the right boundary GH is set as a zero-flux boundary. Under conditions of shallow groundwater depth and backwater, since vertical exchange of groundwater within the simulation domain is minimal, vertical exchange of groundwater below the groundwater level can be ignored, and the bottom boundary IH of the simulation domain is used as the zero-flux boundary.

[0030] Step 3. Based on a portion (70%) of the dataset from Step 2, using channel cross-sectional parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables; and initial infiltration rate, steady-state infiltration rate, and gradual parameter as objective variables, construct a multi-output decision tree regression model suitable for the above complex parameter combinations. Use the remaining portion of the dataset from Step 3 to validate the model constructed in Step 4. The validated model can then be used as a calculation method for free seepage in channels under conditions without top support. In this example, the results of model construction and validation are shown in the following figures. Figure 3 and Figure 4 . Step 4. Construct a calculation model for the groundwater backwater coefficient under different backwater conditions based on the change in the seepage rate of the channel with and without backwater. The calculation formula of the model is as follows; ; Wherein, γ is the groundwater backwater coefficient, which is dimensionless; H g is the groundwater depth of the channel, in meters; r1 and r2 are parameters characterizing the influence of groundwater depth on channel leakage, represented by a Logistic function; r max and g max It is the maximum value of r1 and r2; L It refers to the channel spacing, in meters (m). h It refers to the depth of the channel, in meters (m). Ks 1 is the saturated permeability coefficient of the canal bed soil, in m / s; , , It is an intermediate parameter, dimensionless.

[0031] Step 5. Calculate the channel leakage rate under groundwater backwater conditions.

[0032] Example 1: Based on the free infiltration rate and groundwater backwater coefficient calculation method proposed in this invention, the channel seepage rate under groundwater backwater conditions is calculated. The calculation object is a 1m long section of a farm canal in the Hetao Irrigation District of Inner Mongolia. The measured bottom width is 0.58m, the slope coefficient is 1.6, the water depth is 0.3m, and the soil permeability coefficients of the three layers of the canal are 0.157, 0.211, and 0.367 m / d, respectively. The initial groundwater depth is 2.5m. The free infiltration rate of the canal calculated by the multi-output decision tree regression model is 1.253 × 10⁻⁶ m / d. -5 m 3 / (m·s), that is, 0.0451 m 3 / (m·h). The spacing between channels of the same level in the irrigation area is 100 m. Based on the groundwater backwater coefficient calculated using this method, which is 0.741, the final calculated channel seepage rate under groundwater backwater conditions is 0.0334 m³ / h. 3 / (m·h) Example 2 extrapolates leakage results for other groundwater depths based on test data from a specific groundwater depth condition. The channel parameters are consistent with those in Example 1. Based on the static water leakage test, the measured leakage rate of the channel is 0.03 m³ / s at a water depth of 0.32 m and a groundwater depth of 2.5 m. 3 The permeability coefficient (m·h) was used to calculate the channel seepage rate under the backing condition when the groundwater depth varied from 0.5 to 4.5 m. First, based on the backing coefficient of 0.741 at a depth of 2.5 m, the seepage rate under the free seepage condition was calculated to be 0.0405 m³ / h. 3 / (m·h), and then, based on the backwater coefficient corresponding to the same groundwater depth, the leakage rate under the channel backwater condition was calculated. The results are shown in the figure. Figure 5 . Step 6. With the goal of reducing the channel seepage rate to less than the design value, adjust different channel cross-sectional parameters, groundwater depth, and design water depth to simulate the channel seepage rate after each adjustment. Determine suitable channel parameters or groundwater level control schemes based on whether the output variables meet the design target. Otherwise, modify and adjust the input parameters and simulate again until the output variables meet the design target. In this example, the current groundwater depth in the area is 2.5m, corresponding to a backwater coefficient of 0.741. With the design target of reducing the increase in channel seepage rate by less than 20% after implementing field water-saving measures, determine the maximum suitable groundwater depth in the area. Based on the backwater coefficient variation curve of the channel seepage rate, this depth is determined to be 3.2m.

[0033] Example 2 This embodiment provides a system for calculating the seepage rate of a channel under groundwater backwater conditions, including: Data collection module: It is used to collect basic channel cross-sectional parameters, soil parameters, and groundwater depth parameters; The channel seepage loss numerical model construction module is used to construct a channel seepage loss numerical model under free infiltration conditions and different groundwater depths based on collected channel cross-section parameters and soil parameters; and to simulate the channel seepage process and channel seepage rate under different parameter combinations to generate a dataset. The decision tree regression model construction module is used to construct a multi-output decision tree regression model of channel leakage rate applicable to different channel water depths based on partial data in the dataset, using channel cross-section parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables. The remaining data in the dataset is used to test the multi-output decision tree regression model, and the test results are used as the channel free leakage calculation model under the condition of no top support. Groundwater backwater coefficient calculation model construction module: It is used to construct groundwater backwater coefficient calculation models under different backwater conditions based on the change in the seepage rate of channels with and without backwater. Model Coupling Module: It is used to couple the channel free seepage calculation model with the groundwater backwater coefficient calculation model to calculate the channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing and groundwater depth. Parameter adjustment module: It is used to adjust channel parameters or groundwater level control scheme with the goal of ensuring that the channel leakage rate is less than the design value under groundwater backing conditions.

[0034] It should be understood that any parts not described in detail in this specification belong to the prior art.

[0035] It should be understood that the above description of the preferred embodiments is quite detailed, but this should not be construed as limiting the scope of protection of this invention. It is neither necessary nor possible to exhaustively describe all possible implementations. Those skilled in the art, guided by this invention, can make substitutions or modifications without departing from the scope of the claims, all of which fall within the scope of protection of this invention. The scope of protection of this invention should be determined by the appended claims.

Claims

1. A method for calculating the seepage rate of a channel under groundwater backwater conditions, characterized in that, Includes the following steps: Collect basic channel cross-section and spacing parameters, soil parameters, and groundwater depth parameters; Based on the collected channel cross-sectional parameters and soil parameters, a numerical model of channel leakage loss under free infiltration conditions and different groundwater depths was constructed; and the channel leakage process and leakage rate under different parameter combinations were simulated to generate a dataset. Using channel cross-sectional parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables, a multi-output decision tree regression model for channel leakage rate applicable to different channel water depths was constructed based on partial data in the dataset. The remaining data in the dataset were used to test the multi-output decision tree regression model, and the test results were used as the channel free leakage calculation model under the condition of no top support. Based on the change in seepage rate of channels with and without backing, a calculation model for the groundwater backing coefficient under different backing conditions is constructed. The channel free seepage calculation model is coupled with the groundwater backwater coefficient calculation model to calculate the channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing and groundwater burial depth. With the goal of ensuring that the leakage rate of the channel is less than the design value under the condition of groundwater backing, adjust the channel parameters or the groundwater level control scheme.

2. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 1, characterized in that, The channel cross-sectional parameters, soil parameters, and groundwater parameters include, but are not limited to, channel longitudinal and transverse cross-sectional data, channel water depth data, channel soil stratification data, soil saturation permeability coefficient and moisture characteristic curve data for each layer, channel spacing data, and initial soil moisture content determined based on groundwater depth.

3. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 1, characterized in that, The groundwater backing conditions include the backing effect caused by mutual backing between channels or the initial groundwater depth being relatively high.

4. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 2, characterized in that, The numerical model for channel leakage loss is as follows: ； In the formula, θ Soil volumetric water content, dimensionless; t For time, h; z is the vertical Z-axis coordinate of the soil, with the ground as 0 and upward as the positive direction, in cm; x is the horizontal X-axis coordinate of the soil, with the channel axis as 0, in cm; K ( h ) represents the unsaturated hydraulic conductivity of the soil, which is a function of the soil water potential h; h Soil matrix potential or pressure potential.

5. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 1, characterized in that, When constructing the multi-output decision tree regression model, the independent variables are the channel bottom width, slope coefficient, channel water depth, saturated permeability coefficient of each soil layer, and initial groundwater depth. Its regression output variable is the empirical parameter k. and the stable leakage rate of the channel i c .

6. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 5, characterized in that, The calculation model for free leakage in channels under the condition of no support is as follows: In the formula: S s It is the seepage rate of the earthen canal, in meters. 3 / (h·m); k and These are empirical parameters; i c It is the stable leakage rate of the channel, m 3 / (h·m); t is time, h.

7. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 6, characterized in that, The calculation model for the groundwater backwater coefficient under different backwater conditions is as follows: Wherein, γ is the groundwater backwater coefficient, which is dimensionless; H g is the groundwater depth of the channel, in meters; r1 and r2 are parameters characterizing the influence of groundwater depth on channel leakage, represented by a Logistic function; r max and g max It is the maximum value of r1 and r2; L It refers to the channel spacing, in meters (m). h It refers to the depth of the channel, in meters (m). Ks 1 is the saturated permeability coefficient of the canal bed soil, in m / s; , , It is an intermediate parameter, dimensionless.

8. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 7, characterized in that, The channel seepage rate was calculated under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing, and groundwater depths as follows: In the formula: S ga It is the stable infiltration rate of the channel under the condition of groundwater backwater, m 3 / (h·m); S fa It is the free infiltration rate of the channel calculated by the free leakage calculation model, m 3 / (h·m).

9. The method for calculating channel seepage rate under groundwater backwater conditions according to claim 1, characterized in that, The channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing, and groundwater depth can be calculated by calibrating the channel free infiltration rate based on on-site measured groundwater depth and the corresponding channel infiltration rate; or by directly calculating the channel free infiltration rate.

10. A system for calculating the seepage rate of a channel under groundwater backwater conditions, characterized in that, include: Data collection module: It is used to collect basic channel cross-sectional parameters, soil parameters, and groundwater depth parameters; The channel seepage loss numerical model construction module is used to construct a channel seepage loss numerical model under free infiltration conditions and different groundwater depths based on collected channel cross-section parameters and soil parameters; and to simulate the channel seepage process and channel seepage rate under different parameter combinations to generate a dataset. The decision tree regression model construction module is used to construct a multi-output decision tree regression model of channel leakage rate applicable to different channel water depths based on partial data in the dataset, using channel cross-section parameters, channel water depth, soil parameters, and initial groundwater depth as independent variables. The remaining data in the dataset is used to test the multi-output decision tree regression model, and the test results are used as the channel free leakage calculation model under the condition of no top support. Groundwater backwater coefficient calculation model construction module: It is used to construct groundwater backwater coefficient calculation models under different backwater conditions based on the change in the seepage rate of channels with and without backwater. Model Coupling Module: It is used to couple the channel free seepage calculation model with the groundwater backwater coefficient calculation model to calculate the channel seepage rate under groundwater backwater conditions with different channel water depths, soil parameters, cross-sectional parameters, channel spacing and groundwater depth. Parameter adjustment module: It is used to adjust channel parameters or groundwater level control scheme with the design objective of the channel seepage rate being less than the design value under groundwater backwater conditions. The system for calculating channel leakage rate under groundwater backing conditions is used to perform the steps in the method for calculating channel leakage rate under groundwater backing conditions as described in any one of claims 1-9.

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