Method and device for determining unsaturated parameter numeric value, and electronic device

Abstract

To provide a method and device for determining an unsaturated parameter numeric value, and an electronic device.SOLUTION: The method of the present invention includes the steps of: determining unsaturated parameters of a first preset number of determination objects and a range of values of the unsaturated parameters in a second preset number of osmosis compartments in accordance with a preset model; generating a third preset number of unsaturated parameter combinations on the basis of the unsaturated parameters and the range of values; obtaining a finite element model and a simulation calculation condition on the basis of acquired observation data of hydroelectric power construction; performing simulation calculation on the basis of the unsaturated parameter combination, the finite element model, and the simulation calculation condition to obtain a simulation calculation result; and determining a target unsaturated parameter combination on the basis of the simulation calculation result and the observation data of the hydroelectric power construction to obtain numeric values of the unsaturated parameters.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the technical field of water conservancy and hydroelectric power generation engineering, and in particular to a method, device, and electronic device for determining the value of an unsaturated parameter. [Background technology]

[0002] In large-scale water conservancy and hydropower projects, seepage issues are key to dam safety, making seepage analysis a crucial factor in dam design. Seepage flow and seepage control are crucial issues in water conservancy and hydropower projects. Traditional seepage flow field analyses focus on saturated or stable seepage flow fields, while analysis of seepage flow under unsaturated conditions, such as rainfall infiltration and flood discharge, is rare. While such unsaturated conditions are common in actual construction, obtaining unsaturated parameters using existing field experiment methods is extremely difficult and often results in large errors. In recent years, there has been a gradual increase in seepage flow back-analysis research in the fields of water conservancy and hydropower projects, using specific back-analysis methods to obtain actual data, such as seepage pressure and hydraulic head, and rationally deriving unsaturated parameters for seepage flow fields.

[0003] The currently commonly used method of obtaining unsaturated parameters through indoor testing and back analysis has the following main drawbacks: During the actual construction and operation of water conservancy and hydropower projects, the seepage flow field in the rock mass often changes dynamically due to changes in the boundary head, the excavation and embankment of the dam foundation, rainfall, flood discharge, etc., making it difficult to accurately simulate this dynamic change process through indoor testing. Current back analysis methods mainly use the equalization method, which results in an extremely large number of parameter combinations and low inversion efficiency.

[0004] Therefore, the conventional technology is unable to simulate the dynamic change process of the bedrock seepage flow field, making it difficult to determine accurate unsaturated parameter values, resulting in low acquisition efficiency. Summary of the Invention [Problem to be solved by the invention]

[0005] The present application provides a method, device, and electronic device for determining unsaturated parameter values ​​to at least solve the problems existing in the related art, such as the inability to simulate the dynamic change process of the bedrock seepage flow field, the inability to determine accurate unsaturated parameter values, and low acquisition efficiency. [Means for solving the problem]

[0006] According to one aspect of the present embodiment, determining a first predetermined number of unsaturated parameters to be determined and a range of values ​​of said unsaturated parameters for a second predetermined number of permeation sections according to a predetermined model; generating a third preset number of unsaturated parameter combinations based on the unsaturated parameters and the ranges of values; A step of obtaining a finite element model and simulation calculation conditions based on the obtained observation data of the hydroelectric power generation construction; performing a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result; determining a target unsaturated parameter combination based on the simulation calculation results and the observation data of the hydroelectric power generation construction project, and obtaining the values ​​of the unsaturated parameters.

[0007] According to another aspect of the present embodiment, a determination module that determines a first predetermined number of unsaturated parameters to be determined and a range of values ​​of the unsaturated parameters for a second predetermined number of permeation sections according to a predetermined model; a generation module that generates a third preset number of unsaturated parameter combinations based on the unsaturated parameters and the value ranges; a first acquisition module for acquiring a finite element model and simulation calculation conditions based on the acquired observation data of the hydroelectric power generation construction; a calculation module that performs a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions, and obtains a simulation calculation result; The present invention further provides an apparatus for determining unsaturated parameter values, including a second acquisition module that determines a target unsaturated parameter combination based on the simulation calculation results and observation data of the hydroelectric power generation construction project, and obtains the values ​​of the unsaturated parameters.

[0008] Optionally, the generation module: a first determination unit for determining a first unsaturated parameter, a second unsaturated parameter, and remaining unsaturated parameters from the first predetermined number of unsaturated parameters to be determined; a first acquisition unit for acquiring a relationship equation between the first unsaturated parameter and a second unsaturated parameter, wherein the relationship equation and the first unsaturated parameter represent the second unsaturated parameter; and a generating unit for obtaining candidate values ​​for each of the unsaturated parameters in the permeation section according to the first unsaturated parameter, the relationship equation, the remaining unsaturated parameters, the value range, and a predetermined method, and generating a third predetermined number of combinations of the unsaturated parameters.

[0009] Optionally, the first acquisition module: a first acquisition unit for acquiring profile data points based on observation data of the hydroelectric power construction; a second acquisition unit for acquiring the finite element model based on the profile data points and a preset grid type; a division unit for generalizing the finite element model to divide the finite element model into a second predetermined number of the permeation compartments; a second acquisition unit for acquiring permeation compartment parameters of the permeation compartment; a third acquisition unit for acquiring boundary conditions and initial water level conditions of the finite element model based on observed data of the hydroelectric power generation construction; and a fourth obtaining unit for obtaining the simulation calculation conditions based on the permeation compartment parameters, the boundary conditions, and the initial water level conditions.

[0010] Optionally, the third acquisition unit: a first acquisition submodule for acquiring a water level line for a predetermined period based on observation data of the hydroelectric power generation construction; a first determination sub-module for determining a slope head boundary of the finite element model based on the water level line; a second determination sub-module that determines a water level value of the head boundary based on observation data of the hydroelectric power generation construction project, using a left boundary of the finite element model as a head boundary; a second acquisition sub-module for acquiring an actual observed head value based on the observation data of the hydroelectric power generation construction; and a third acquisition sub-module that inputs the measured observed head values ​​into a trained neural network to obtain the initial water level conditions.

[0011] Optionally, the third acquisition unit: a fourth acquisition sub-module for acquiring a predetermined number of watershed level values; a fourth acquisition sub-module for obtaining a head calculation value and a corresponding boundary head value at each borehole position according to a preset seepage analysis method and the watershed water level value; and a training sub-module for training an initial neural network using the calculated head value and the boundary head value to obtain the trained neural network.

[0012] Optionally, the calculation module: a selection unit for selecting one of the third preset number of unsaturated parameter combinations as an unsaturated parameter combination to be calculated; a first calculation unit that performs a simulation calculation based on the unsaturated parameter combination to be calculated, the finite element model, and the simulation calculation conditions, and obtains a single combination simulation calculation result corresponding to the unsaturated parameter combination to be calculated; a circulation unit that starts executing subsequent steps from the step of selecting one of the third predetermined number of unsaturated parameter combinations as an unsaturated parameter combination to be calculated, and executes the subsequent steps until a single combination single combination simulation calculation result corresponding to each of the unsaturated parameter combinations is obtained; and an integration unit for integrating all the single combination simulation calculation results to obtain the simulation calculation result.

[0013] Optionally, the second acquisition module: a second determining unit for determining a fifth predetermined number of detected data points; a fifth obtaining unit for obtaining a zero pressure surface position at a predetermined time corresponding to each of the unsaturated parameter combinations based on the simulation calculation result; a sixth acquisition unit for obtaining predicted data at each of the detected data points for each of the unsaturated parameter combinations based on the zero pressure surface position and the detected data points; a seventh acquisition unit for acquiring actual measurement data corresponding to the predicted data based on the observation data of the hydroelectric power generation construction; a second calculation unit that calculates an error at each of the detected data points for each of the non-saturated parameter combinations based on the predicted data and the actual measurement data; a third calculation unit for calculating a total error corresponding to each of the unsaturated parameter combinations based on the errors; and an identifying unit that identifies the unsaturated parameter combination corresponding to the smallest total error as the target unsaturated parameter combination that includes the numerical values ​​of the unsaturated parameters.

[0014] According to a further aspect of an embodiment of the present application, there is provided an electronic device including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus, the memory stores a computer program; The present invention further provides an electronic device, wherein the processor is adapted to perform the method steps according to any one of the above embodiments by operating the computer program stored in the memory.

[0015] According to a further aspect of an embodiment of the present application, there is further provided a computer-readable storage medium having a computer program stored thereon, the computer program being configured to perform the method steps according to any one of the above embodiments when executed by a processor.

[0016] In one embodiment of the present application, a first predetermined number of target unsaturated parameters and a second predetermined number of target unsaturated parameter value ranges are determined according to a preset model. A third predetermined number of unsaturated parameter combinations are generated based on the unsaturated parameters and their value ranges. A finite element model and simulation calculation conditions are derived based on the acquired observation data of the hydroelectric project. A simulation is performed based on the unsaturated parameter combinations, the finite element model, and the simulation calculation conditions to obtain the simulation results. Based on the simulation results and the observation data of the hydroelectric project, a target unsaturated parameter combination is determined and the values ​​of the unsaturated parameters are obtained. Using the above method, a finite element model is constructed, simulation calculation conditions are set, and a simulation is performed on the water level change process in the reservoir, thereby effectively considering the influence of various geological factors and improving the accuracy of parameter acquisition. The unsaturated parameters are combined to determine the target unsaturated parameter combinations to obtain the values ​​of each unsaturated parameter, effectively reducing the amount of calculation and improving the efficiency of obtaining the optimal unsaturated parameter combination. By analyzing the error of simulation calculation results based on observed data from hydroelectric power generation construction and selecting the target unsaturated parameter combination, it is possible to efficiently obtain a local optimal solution in a simple and convenient manner. This solves the problems present in related technologies, such as the inability to simulate the dynamic change process of the bedrock seepage flow field, the inability to determine accurate unsaturated parameter values, and low acquisition efficiency. [Brief explanation of the drawings]

[0017] The drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present invention and, together with the description, serve to explain the principles of the invention. In order to more clearly describe the embodiments of the present invention or the technical solutions in the prior art, the following will briefly describe the drawings that need to be used in the description of the embodiments or the prior art, and it is obvious to those skilled in the art that other drawings can be obtained based on these drawings without any creative efforts. [Figure 1] 1 is a flow diagram of a method for determining an optional desaturation parameter value according to an embodiment of the present application; [Figure 2] FIG. 1 is a schematic diagram of an optional finite element model and permeation zone according to an embodiment of the present application. [Figure 3] FIG. 10 illustrates the relationship between optional upstream water level and date change according to an embodiment of the present application. [Figure 4] FIG. 10 is a diagram showing the results of a seepage flow forward analysis of the parameters used in the optional unsaturated parameter combination according to an embodiment of the present application. [Figure 5] 1 is a flow diagram of another optional method for determining a numerical value of a desaturation parameter according to an embodiment of the present application; [Figure 6] FIG. 2 is a structural block diagram of an optional desaturation parameter value determination device according to an embodiment of the present application; [Figure 7] FIG. 2 is a structural block diagram of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE INVENTION

[0018] In order to enable those skilled in the art to better understand the aspects of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, but it is clear that the described embodiments are only some embodiments of the present application and do not represent all embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without any creative work shall fall within the protection scope of the present application.

[0019] It should be noted that terms such as "first," "second," and the like in the specification and claims of this application, as well as in the drawings, are used to distinguish between similar entities and are not used to describe a particular order or priority. It should be understood that data used in this manner are interchangeable where appropriate, and that the embodiments of this application described herein may be performed in orders other than those illustrated or described herein. Furthermore, the terms "comprise" and "have," and any variations thereof, are intended to cover exclusive inclusions; for example, a process, method, system, product, or apparatus comprising a series of steps or units need not be limited to the steps or units expressly listed, but may include other steps or units not expressly listed or inherent in the process, method, product, or apparatus.

[0020] According to one aspect of the embodiment of the present application, there is provided a method for determining a non-saturation parameter value, and as shown in FIG. 1, the flow of the method may include the following steps S101 to S105.

[0021] Step S101: Determine the value ranges of a first predetermined number of unsaturated parameters to be determined and a second predetermined number of unsaturated parameters in the infiltration compartments according to a predetermined model.

[0022] Optionally, in this embodiment, the preset model may be the van Genuchten (VG) model, which is a smooth and continuous water retention curve model based on Mualem theory. JPEG2025016354000002.jpg45145

[0023] s is a model variable, y and n are parameters related to the pore distribution, α is a parameter related to the intake value, θ is the moisture content, and θ s is the saturated volumetric water content, and θ r is the residual volumetric water content, and k r is the soil unsaturated infiltration coefficient, and s eis an intermediate variable, and k s is the saturated permeability coefficient.

[0024] First, the unsaturated parameters to be determined in the van Genuchten (VG) model are determined. The unsaturated parameters are selected using α, y, n, and θ. r The analysis is generally performed using the following four parameters: saturated volumetric water content θ s and saturated permeability coefficient k s In general, data obtained from laboratory tests are used for the calculation of α, y, n, θ in a second predetermined number of infiltration sections according to previous laboratory tests and construction experience. r The range of the numerical values ​​is determined. Because the properties of the permeation flow are different for each permeation section, the first predetermined number and the second predetermined number are both plural, and the first predetermined number may be 4 or another numerical value.

[0025] Step S102: Generate a third preset number of unsaturated parameter combinations based on the unsaturated parameters and value ranges.

[0026] Optionally, the desaturation parameters (α, y, n, θ) determined in step S101 r Based on the range of values ​​of the second predetermined number of infiltration sections, the schemes for the unsaturated parameters are rationally combined by an orthogonal design method to generate a third predetermined number of unsaturated parameter combinations. For each unsaturated parameter combination, α, y, n, θ r There is a specific numerical value of the third preset number, and the third preset number is plural, but is not particularly limited.

[0027] Step S103: Based on the acquired observation data of the hydroelectric power generation construction, a finite element model and simulation calculation conditions are obtained.

[0028] Optionally, observation data from a hydropower project, such as observation data from an observation point with a long observation hole in a hydropower project in southwest China, is acquired, a riverbank profile is generated based on the observation data from the hydropower project, grid division is performed on the riverbank profile, and a two-dimensional or three-dimensional finite element model is created. The initial water level conditions of the riverbank are determined from the observation data from the hydropower project, and boundary conditions and infiltration compartment parameters for each infiltration compartment are set to obtain simulation calculation conditions.

[0029] Step S104: A simulation calculation is performed based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions, and a simulation calculation result is obtained.

[0030] Optionally, the SEEP / W module of the GEO-studio software is used to perform a simulation calculation, such as a seepage flow simulation analysis, for each unsaturated parameter combination based on the above-mentioned finite element model and simulation calculation conditions, and obtain simulation calculation results corresponding to each unsaturated parameter combination, where the simulation calculation results include the upstream water level based on the water level change in the reservoir and the distribution of hydraulic head (seepage pressure) at the measurement point position.

[0031] Step S105: Based on the simulation calculation results and the observation data of the hydroelectric power generation construction, a target unsaturated parameter combination is determined, and the numerical values ​​of the unsaturated parameters are obtained.

[0032] Optionally, actual measurement data is obtained based on observation data of hydroelectric power generation construction. Based on the simulation calculation results and actual measurement data obtained in step S104, the sum of squared errors between the actual measurement data and the simulation calculation results is calculated. After the calculation of the sum of squared errors for all unsaturated parameter combinations is completed, the unsaturated parameter combination with the smallest sum of squared errors is set as the target unsaturated parameter combination, and the numerical values ​​of the unsaturated parameters of the target unsaturated parameter combination are set as the optimal values ​​of the unsaturated parameters to be determined.

[0033] In one embodiment of the present invention, a first predetermined number of target unsaturated parameters and a second predetermined number of target unsaturated parameter value ranges are determined based on a preset model. A third predetermined number of unsaturated parameter combinations are generated based on the unsaturated parameters and their value ranges. A finite element model and simulation calculation conditions are derived based on the acquired observation data of the hydroelectric project. A simulation is performed based on the unsaturated parameter combinations, the finite element model, and the simulation calculation conditions to obtain the simulation results. Based on the simulation results and the observation data of the hydroelectric project, a target unsaturated parameter combination is determined and the values ​​of the unsaturated parameters are obtained. Using the above method, a finite element model is constructed, simulation calculation conditions are set, and a simulation is performed on the water level change process in the reservoir. This effectively takes into account the influence of various geological factors, thereby improving the accuracy of parameter acquisition. The unsaturated parameters are combined to determine the target unsaturated parameter combinations, thereby obtaining the values ​​of each unsaturated parameter, effectively reducing the amount of calculation and improving the efficiency of obtaining the optimal unsaturated parameter combination. By analyzing the error of simulation calculation results based on observed data from hydroelectric power generation construction and selecting the target unsaturated parameter combination, it is possible to efficiently obtain a local optimal solution in a simple and convenient manner. This solves the problems present in related technologies, such as the inability to simulate the dynamic change process of the bedrock seepage flow field, the inability to determine accurate unsaturated parameter values, and low acquisition efficiency.

[0034] As an optional example, generating the third preset number of unsaturated parameter combinations based on the unsaturated parameters and the value ranges may include: determining a first unsaturated parameter, a second unsaturated parameter, and remaining unsaturated parameters from a first preset number of unsaturated parameters to be determined; Obtaining a relationship equation between a first unsaturated parameter and a second unsaturated parameter, wherein the relationship equation and the first unsaturated parameter represent the second unsaturated parameter; and obtaining candidate values ​​for each unsaturated parameter in the infiltration section according to the first unsaturated parameter, the relationship equation, the remaining unsaturated parameters, the value range and the preset method, to generate a third preset number of unsaturated parameter combinations.

[0035] Optionally, in this embodiment, the desaturation parameters are α, y, n, θ r In this case, the first preset number is 4. r When a first unsaturation parameter, for example, n, and a second unsaturation parameter, for example, y, are selected from the above, the remaining unsaturation parameters are α, θ r Includes:

[0036] A relational equation between n and y, for example, y=1-1 / n, can be obtained, and y can be expressed as n by the relational equation. Therefore, once the value of n is determined, the value of y can be obtained by the value of n and the relational equation, and the value of y does not need to be taken into consideration when generating the unsaturated parameter combination, thereby reducing the amount of calculation. Next, the first unsaturated parameter n, the remaining unsaturated parameters α and θ are determined. r Based on the value ranges of the above unsaturated parameters in the second predetermined number of infiltration compartments, schemes for the unsaturated parameters are rationally combined using a predetermined method (e.g., orthogonal design method) to generate a third predetermined number of unsaturated parameter combinations. Taking the case where there are three types of infiltration compartments as an example, the value range of α in infiltration compartment 1 is, for example, 0.02 to 0.14, and the value range of n in infiltration compartment 2 is, for example, 0 to 4.00. The other value ranges are not described in detail, and the detailed value ranges are shown in the table below. The generated unsaturated parameter combinations are shown in the table below.

[0037] JPEG2025016354000003.jpg61170

[0038] In this case, the second preset number is three, the unsaturated parameter combinations include groups 1 to 7, and the third preset number is seven.

[0039] In the embodiment of the present application, the unsaturated parameters are combined by orthogonal design, which can effectively reduce the calculation of the combination and improve the efficiency of obtaining the optimal unsaturated parameter combination.

[0040] As an optional example, the step of obtaining a finite element model and simulation calculation conditions based on the obtained observation data of the hydroelectric power generation construction includes: obtaining profile data points based on observed data of the hydroelectric construction; obtaining a finite element model based on the profile data points and a pre-set grid type; generalizing the finite element model to divide the finite element model into a second predetermined number of permeable compartments; obtaining permeation compartment parameters for the permeation compartment; obtaining boundary conditions and initial water level conditions for a finite element model based on observed data of the hydroelectric power generation project; and obtaining simulation calculation conditions based on the permeable compartment parameters, boundary conditions, and initial water level conditions.

[0041] Optionally, this embodiment takes as an example the construction of a two-dimensional finite element model using observation data from a long observation hole at a hydroelectric power plant in southwest China. Based on the observation data, profile data points are obtained and imported into the SEEP / W module of GEO-studio software to generate a riverbank profile with a left side elevation of 1010 meters (m), a right side elevation of 575 meters (m), and a bottom of 1100 meters. Next, a preset grid type is used to perform grid division on the riverbank profile graph to construct a two-dimensional finite element model. The preset grid type may be a 10-m square grid. After appropriate generalization of the model, the finite element model is divided into a second preset number of seepage compartments, for example, three. The generalization is a conventional method, i.e., ignoring some factors such as faults and structural planes that have little impact. In this case, the finite element model includes infiltration section 1, infiltration section 2, and infiltration section 3, as shown in Figure 2, and the upper right corner of Figure 2 is the river valley. The two-dimensional finite element model in Figure 2 has an initial groundwater level line, and also has monitoring point 1 and monitoring point 2. The two monitoring points are for selecting and comparing data from the observation data of hydroelectric power generation construction and the simulation calculation results. For details, please refer to Figure 2.

[0042] In addition, setting the boundary conditions, initial water level conditions and infiltration compartment parameters in the SEEP / W module of the GEO-studio software is specifically as follows: The method includes obtaining the infiltration compartment parameters of the infiltration compartment, wherein the present application includes adjusting the model according to the infiltration capacity of each zone, and calculating the saturated infiltration coefficient of 1.00×10 -5 m / s, 3.00 x 10 -6 m / s, 9.00 x 10 -7 The saturated volumetric water content of permeation compartment 1 is determined as 0.30, and the saturated volumetric water content of permeation compartments 2 and 3 is determined as 0.40. The specific permeation compartment parameters are shown in the table below.

[0043] JPEG2025016354000004.jpg27170

[0044] The initial water level conditions of the riverbank may be determined from the observation data of the hydroelectric power generation construction project, boundary conditions may be set, the above-mentioned infiltration compartment parameters, boundary conditions and initial water level conditions may be integrated to obtain simulation calculation conditions, and simulation calculations may be performed based on the simulation calculation conditions and the above-mentioned finite element model.

[0045] In the embodiment of the present application, a finite element model is created based on the observation data of the hydroelectric power plant project, and together with the simulation calculation conditions, it provides a basis for subsequent simulation calculation. Based on the above finite element model and simulation calculation conditions, an inverse analysis is carried out according to the relationship between the water level and the seepage pressure and head at the measurement point during the water level change process in the reservoir, so as to effectively consider the influence of each geological factor, thereby improving the accuracy of parameter acquisition.

[0046] As an optional example, the step of obtaining boundary conditions and initial water level conditions for the finite element model based on observed data of the hydroelectric power generation construction includes: obtaining a water level line for a predetermined period based on observation data of the hydroelectric power generation construction; determining a slope head boundary of the finite element model based on the waterline; a step of determining a water level value of the head boundary based on observation data of the hydroelectric power generation construction, with the left boundary of the finite element model as the head boundary; obtaining an actual observed head value based on observation data of the hydroelectric power generation construction; and inputting the measured observed head values ​​into the trained neural network to obtain initial water level conditions.

[0047] Optionally, in this embodiment, observation data from an observation point with a long observation hole in a hydroelectric power plant in southwest China is used as the observation data for the hydroelectric power plant. Based on this observation data from the hydroelectric power plant, the change in upstream water level over time (i.e., the water level line) for the hydroelectric power plant in southwest China is obtained. This water level line is shown in Figure 3, which includes the change in upstream water level (m) from April 3, 2021 to October 3, 2021. From Figure 3, the water level line for a preset period is obtained. The preset period may be from April 23, 2021 to May 7, 2021, a total of 15 days.

[0048] Based on this water level line, the valley side of the river in the finite element model is set as the slope head boundary (i.e., the upper right corner in Figure 2), and the water level value of the slope head boundary is determined based on this water level line.

[0049] The boundary water level on the left side of the finite element model (the boundary on the mountain side of the right bank, i.e., the side away from the river valley) is determined as the head boundary, and the water level value of the head boundary is determined based on observation data from hydroelectric power generation construction work.For example, the water level value of the head boundary is determined by inverting it using borehole water level observation data in the observation data from hydroelectric power generation construction work.

[0050] Based on the observation data of the hydroelectric power generation project, the actual observation head value is obtained, and the actual observation head value is input into the trained neural network to obtain the optimal watershed boundary water level condition, i.e., the initial water level condition.

[0051] In an embodiment of the present application, the boundary conditions of a finite element model are determined based on observed data from hydroelectric power generation construction, and the initial water level conditions are obtained using a trained neural network, thereby reducing the time required to determine the initial water level conditions.

[0052] As an optional example, prior to inputting the measured observed head values ​​into the trained neural network, the method comprises: obtaining a fourth preset number of watershed level values; obtaining a head calculation value and a corresponding boundary head value for each borehole location based on a preset seepage analysis method and a watershed water level value; and training an initial neural network using the head calculation values ​​and the boundary head values ​​to obtain a trained neural network.

[0053] Optionally, a plurality of proposed watershed water level values ​​are obtained, and the fourth preset number is a plurality of values. A stable seepage analysis method (i.e., a preset seepage analysis method) is used to calculate the seepage flow field of the left bank mountain body and the calculated head values ​​at each drilling position from the above watershed water level values, and corresponding boundary head values ​​are obtained. An initial neural network is trained using the calculated head values ​​as input samples and the boundary head values ​​as output samples, thereby obtaining a trained neural network. The initial neural network may be a genetic neural network.

[0054] In the embodiment of the present application, the head calculation value and the boundary head value are used to train an initial neural network and obtain a trained neural network, thereby reducing the time required to determine the initial water level condition and improving the efficiency of determining the desaturation parameter value.

[0055] As an optional example, the step of performing a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result includes: selecting one unsaturated parameter combination from a third preset number of unsaturated parameter combinations as an unsaturated parameter combination to be calculated; A step of performing a simulation calculation based on the unsaturated parameter combination to be calculated, the finite element model, and the simulation calculation conditions, and obtaining a single combination simulation calculation result corresponding to the unsaturated parameter combination to be calculated; Selecting one unsaturated parameter combination from the third preset number of unsaturated parameter combinations as the unsaturated parameter combination to be calculated, and then starting to execute subsequent steps to obtain single combination simulation calculation results corresponding to each unsaturated parameter combination; and combining all the single combination simulation calculation results to obtain a simulation calculation result.

[0056] Optionally, in this embodiment, it is necessary to carry out simulation calculation for each unsaturated parameter combination, and obtain a single combination simulation calculation result corresponding to this unsaturated group. This process is repeated until the simulation calculation for all unsaturated parameter combinations is completed, and specifically includes:

[0057] One unsaturated parameter combination is selected from the third preset number of unsaturated parameter combinations as the unsaturated parameter combination to be calculated, and a combination simulation calculation is performed on the unsaturated parameters to be calculated based on the above-mentioned finite element model and simulation calculation conditions, to obtain a single combination simulation calculation result corresponding to the unsaturated parameter combination to be calculated.An unsaturated parameter combination that has not been subjected to simulation calculation is selected from the third preset number of unsaturated parameter combinations as the unsaturated parameter combination to be calculated, and the above process is repeated to obtain a single combination simulation calculation result for the unsaturated parameter combination to be calculated.The process ends when a single combination simulation calculation result corresponding to each unsaturated parameter combination is obtained.

[0058] All the single combination simulation calculation results may be integrated to obtain a simulation calculation result, and a target unsaturated parameter combination may be determined based on the simulation calculation result and observation data of the hydroelectric power generation construction.

[0059] In the embodiment of the present application, a simulation calculation is performed for each unsaturated parameter combination, and a simulation calculation result corresponding to each unsaturated parameter combination is obtained, which provides a basis for later selecting a target unsaturated parameter combination from the unsaturated parameter combinations based on the simulation calculation result and observation data of the hydroelectric power generation project.

[0060] As an optional embodiment, the step of determining a target unsaturated parameter combination and obtaining a value of the unsaturated parameter based on the simulation calculation result and the observation data of the hydroelectric power generation construction includes: determining a fifth preset number of detected data points; obtaining a zero pressure surface position at a predetermined time corresponding to each unsaturated parameter combination based on the simulation calculation result; obtaining predicted data at each sensed data point for each unsaturated parameter combination based on the zero pressure surface location and the sensed data points; A step of obtaining actual measurement data corresponding to the prediction data based on observation data of the hydroelectric power generation construction work; calculating an error at each detected data point for each desaturation parameter combination based on the predicted data and the actual measured data; calculating a total error corresponding to each unsaturated parameter combination based on the errors; Identifying the unsaturated parameter combination that corresponds to the smallest total error as the target unsaturated parameter combination that includes the numerical values ​​of the unsaturated parameters.

[0061] Optionally, a fifth preset number of detection data points is determined, and the fifth preset number is plural. In this embodiment, two detection data points, i.e., monitoring point 1 and monitoring point 2 in FIG. 2, are used to illustrate a total of seven non-saturation parameter combinations, group 1 to group 7.

[0062] Based on the simulation results, the seepage flow forward analysis results shown in Figure 4 were obtained for the parameters used for each unsaturated parameter combination. Figure 4 shows the distribution of hydraulic heads at different pressures in a finite element model. From this seepage flow forward analysis result, the zero pressure surface position at a preset time corresponding to each unsaturated parameter combination can be obtained. The zero pressure surface position is the position where the pressure head is 0 m, and the preset times are 1, 5, 7, 11, and 15 days. Based on the zero pressure surface position, monitoring points 1 and 2, predicted data was obtained at each detection data point for each unsaturated parameter combination. The predicted data is the height (m) above sea level at the two detection data points of the zero pressure surface position. Based on observation data from the hydroelectric power generation construction project, the actual measured data (m) corresponding to the predicted data was obtained. The predicted and actual measured data are shown in the table below.

[0063] JPEG2025016354000005.jpg80170

[0064] Based on the above predicted data and actual measured data, the standard deviation (i.e., error) at each detected data point for each desaturation parameter combination was calculated, and based on this error, the population standard deviation sum (i.e., total error) corresponding to each desaturation parameter combination was calculated. The errors and population standard deviation sum (i.e., total error) at monitoring point 1 and monitoring point 2 for each desaturation parameter combination are shown in the table below. JPEG2025016354000006.jpg53170

[0065] As a result of the comparison, the data calculated for group 5 had a population standard deviation of 0.04166 when compared with the data at monitoring point 1, and a population standard deviation of 0.04470 when compared with the data at monitoring point 2. The sum of the population standard deviations (i.e., the sum of the errors at monitoring point 1 and monitoring point 2) was the desaturation parameter combination with the smallest population standard deviation sum among all groups, and therefore group 5 was determined to be the target desaturation parameter combination. rThe specific value of y in each infiltration section is obtained, and the specific value of n is used to calculate the specific value of y in each infiltration section according to the relationship equation between n and y: y=1-1 / n.

[0066] In the embodiment of the present application, error analysis is performed using the sum of squares of the error between the calculated measured data and the numerical simulation calculation results, thereby making it possible to efficiently obtain a local optimum solution in a simple and easy manner.

[0067] According to one aspect of the embodiment of the present application, there is provided another method for determining a value of an unsaturation parameter, and as shown in FIG. 5, the flow of the method includes the following steps:

[0068] The method includes the steps of determining the number and approximate range of VG model inversion analysis parameters, rationally combining schemes for unsaturated parameters using the orthogonal design method, creating a three-dimensional finite element model and performing unsaturated seepage flow forward analysis, calculating the sum of squares of the error between the actual measurement data and the numerical simulation calculation results to find the optimal combination, and inverting the results.

[0069] In the present embodiment, an inversion analysis is performed according to the relationship between the water level and the osmotic pressure and hydraulic head at the measurement point during the water level change process in the reservoir, effectively considering the influence of various geological factors, thereby improving the accuracy of parameter acquisition. By combining unsaturated parameters using orthogonal design, the number of combination calculations can be effectively reduced, improving the efficiency of obtaining the optimal unsaturated parameter combination. Error analysis is performed using the sum of squares of the error between the calculated measured data and the numerical simulation results, making it possible to efficiently obtain a local optimal solution in a simple and convenient manner.

[0070] According to another aspect of the present invention, there is also provided an apparatus for determining unsaturated parameter values, which is used to implement the above-mentioned method for determining unsaturated parameter values. Figure 6 is a structural block diagram of an optional apparatus for determining unsaturated parameter values ​​according to the present invention. As shown in Figure 6, the apparatus includes: a determining module 601 for determining a first predetermined number of unsaturated parameters to be determined and a second predetermined number of permeation compartment value ranges according to a predetermined model; a generation module 602 that generates a third preset number of unsaturated parameter combinations based on the unsaturated parameters and value ranges; a first acquisition module 603 for acquiring a finite element model and simulation calculation conditions based on the acquired observation data of the hydroelectric power generation construction; a calculation module 604 that performs a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result; The method may further include a second acquisition module 605 that determines a target unsaturated parameter combination based on the simulation calculation results and observation data of the hydroelectric power generation construction work, and obtains the numerical values ​​of the unsaturated parameters.

[0071] It should be noted that the determination module 601 in this embodiment may perform the above step S101, the generation module 602 in this embodiment may perform the above step S102, the first acquisition module 603 in this embodiment may perform the above step S103, the calculation module 604 in this embodiment may perform the above step S104, and the second acquisition module 605 in this embodiment may perform the above step S105.

[0072] Using the above modules, a finite element model is constructed, simulation calculation conditions are set, and simulation calculations are performed on the water level change process in the reservoir. The effects of various geological factors are effectively taken into account, improving the accuracy of parameter acquisition. By combining unsaturated parameters and determining the target unsaturated parameter combination to obtain the values ​​of each unsaturated parameter, the amount of calculation is effectively reduced and the efficiency of obtaining the optimal unsaturated parameter combination is improved. By analyzing the error of the simulation calculation results based on observed data from hydropower construction projects and selecting the target unsaturated parameter combination, it is possible to efficiently obtain a local optimal solution in a simple and convenient manner. This solves the problems present in related technologies, such as the inability to simulate the dynamic change process of the bedrock seepage flow field, the inability to accurately determine unsaturated parameter values, and low acquisition efficiency.

[0073] As an optional example, the generation module: a first determination unit for determining a first unsaturated parameter, a second unsaturated parameter, and remaining unsaturated parameters from a first preset number of unsaturated parameters to be determined; a first acquisition unit for acquiring a relationship equation between a first unsaturated parameter and a second unsaturated parameter, wherein the relationship equation and the first unsaturated parameter represent the second unsaturated parameter; and a generating unit for obtaining candidate values ​​for each unsaturated parameter in the infiltration section according to the first unsaturated parameter, the relationship equation, the remaining unsaturated parameters, the value range and a preset method, and generating a third preset number of unsaturated parameter combinations.

[0074] As an optional example, the first acquisition module: a first acquisition unit for acquiring profile data points based on observation data of the hydroelectric power generation construction; a second acquisition unit for acquiring a finite element model based on the profile data points and a preset grid type; a division unit for generalizing the finite element model to divide the finite element model into a second predetermined number of permeable compartments; a second acquisition unit for acquiring permeation compartment parameters of the permeation compartment; a third acquisition unit for acquiring boundary conditions and initial water level conditions of the finite element model based on observed data of the hydroelectric power generation construction; and a fourth obtaining unit for obtaining simulation calculation conditions based on the permeation compartment parameters, the boundary conditions and the initial water level conditions.

[0075] As an optional example, the third acquisition unit: a first acquisition submodule for acquiring a water level line for a predetermined period based on observation data of the hydroelectric power generation construction; a first determination sub-module for determining a slope head boundary of the finite element model based on the water level line; a second determination submodule for determining a water level value of the head boundary based on observation data of the hydroelectric power generation construction project, with the left boundary of the finite element model as the head boundary; a second acquisition sub-module for obtaining a measured observed head value based on the observation data of the hydroelectric power generation construction; and a third acquisition sub-module that inputs the measured observed head values ​​into the trained neural network to obtain initial water level conditions.

[0076] As an optional example, the third acquisition unit: a fourth acquisition sub-module for acquiring a predetermined number of watershed level values; a fourth obtaining sub-module for obtaining a head calculation value and a corresponding boundary head value for each borehole location according to a preset seepage analysis method and a watershed water level value; and a training sub-module for training an initial neural network using the head calculation values ​​and the boundary head values ​​to obtain a trained neural network.

[0077] As an optional example, the calculation module: a selection unit for selecting one unsaturated parameter combination from a third preset number of unsaturated parameter combinations as an unsaturated parameter combination to be calculated; a first calculation unit that performs a simulation calculation based on the unsaturated parameter combination to be calculated, the finite element model, and the simulation calculation conditions, and obtains a single combination simulation calculation result corresponding to the unsaturated parameter combination to be calculated; a circulation unit for selecting one unsaturated parameter combination from the third preset number of unsaturated parameter combinations as the unsaturated parameter combination to be calculated, and then starting to execute subsequent steps to obtain a single combination simulation calculation result corresponding to each unsaturated parameter combination; and an integration unit for integrating all the single combination simulation calculation results to obtain a simulation calculation result.

[0078] As an optional example, the second acquisition module may include: a second determining unit for determining a fifth predetermined number of detected data points; a fifth obtaining unit for obtaining a zero pressure surface position at a predetermined time corresponding to each unsaturated parameter combination based on the simulation calculation result; a sixth acquisition unit for obtaining predicted data at each detected data point for each unsaturated parameter combination based on the zero pressure surface position and the detected data point; a seventh acquisition unit for acquiring actual measurement data corresponding to the predicted data based on the observation data of the hydroelectric power generation construction; a second calculation unit for calculating an error at each detected data point for each unsaturated parameter combination based on the predicted data and the actual measured data; a third calculation unit for calculating a total error corresponding to each unsaturated parameter combination based on the error; and an identifying unit that identifies the unsaturated parameter combination corresponding to the minimum total error as a target unsaturated parameter combination including the numerical values ​​of the unsaturated parameters.

[0079] Here, the above modules are the same as the examples and application scenarios realized by the corresponding steps, but are not limited to the contents disclosed in the above embodiments.

[0080] According to a further aspect of the embodiment of the present application, there is also provided an electronic device that implements the above-described method for determining a desaturation parameter value, and the electronic device may be a server, a terminal, or a combination thereof.

[0081] FIG. 7 is a structural block diagram of an optional electronic device according to an embodiment of the present application. As shown in FIG. 7, the electronic device includes: a processor 701, a communication interface 702, a memory 703, and a communication bus 704, and the processor 701, the communication interface 702, and the memory 703 communicate with each other via the communication bus 704; The memory 703 stores computer programs. When the processor 701 executes a computer program stored in the memory 703, determining a range of values ​​of the unsaturated parameter for a first predetermined number of determined unsaturated parameters and a second predetermined number of infiltration sections according to a predetermined model; generating a third preset number of unsaturated parameter combinations based on the unsaturated parameters and value ranges; A step of obtaining a finite element model and simulation calculation conditions based on the obtained observation data of the hydroelectric power generation construction; performing a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result; and determining a target unsaturated parameter combination based on the simulation calculation results and observation data of the hydroelectric power generation construction work, and obtaining the numerical values ​​of the unsaturated parameters.

[0082] Optionally, in this embodiment, the communication bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus may be classified into an address bus, a data bus, a control bus, etc. In Fig. 7, only one thick line is shown for ease of illustration, but this does not indicate that there is only one bus or only one type of bus.

[0083] The communication interface is used for communication between the electronic device and other devices.

[0084] The memory may include RAM or non-volatile memory, such as at least one magnetic disk memory. Optionally, the memory may be at least one storage device remote from the processor.

[0085] 7, the memory 703 may include, but is not limited to, the determining module 601, the generating module 602, the first obtaining module 603, the calculating module 604, and the second obtaining module 605 of the device for determining the desaturation parameter value. In addition, the memory 703 may include, but is not limited to, other module units of the device for determining the desaturation parameter value, which are not described in detail in this example.

[0086] The processor may be a general-purpose processor, including but not limited to a central processing unit (CPU), network processor (NP), digital signal processing (DSP), application specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component.

[0087] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and therefore will not be described in detail in this embodiment.

[0088] As will be understood by those skilled in the art, the structure shown in FIG. 7 is a schematic diagram, and the device implementing the above-described method for determining a desaturation parameter value may be a terminal device, such as a smartphone (e.g., an Android mobile phone, an iOS mobile phone, etc.), a tablet terminal, a handheld computer, a mobile internet device (MID), a PAD, etc. FIG. 7 does not limit the structure of the above-described electronic device. For example, the terminal device may include more or fewer components (e.g., a network interface, a display device, etc.) than those shown in FIG. 7, or may have a different configuration from that shown in FIG. 7.

[0089] As can be understood by those skilled in the art, all or part of the steps in the various methods of the above embodiments may be performed by instructing a program in hardware associated with the terminal device, and the program may be stored in a computer-readable storage medium including a flash memory, a ROM, a RAM, a magnetic disk, an optical disk, or the like.

[0090] According to a further aspect of an embodiment of the present application, there is also provided a storage medium, which may optionally store a program code for executing the method for determining a desaturation parameter value.

[0091] Optionally, in this embodiment, the storage medium may be located on at least one network device among a plurality of network devices in the network shown in the above embodiment.

[0092] Optionally, in this embodiment, the storage medium comprises: determining a range of values ​​of the unsaturated parameter for a first predetermined number of determined unsaturated parameters and a second predetermined number of infiltration sections according to a predetermined model; generating a third preset number of unsaturated parameter combinations based on the unsaturated parameters and value ranges; A step of obtaining a finite element model and simulation calculation conditions based on the obtained observation data of the hydroelectric power generation construction; performing a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result; The storage device is configured to store a program code for executing a step of determining a target unsaturated parameter combination and obtaining the numerical value of the unsaturated parameter based on the simulation calculation result and observation data of the hydroelectric power generation construction work.

[0093] Optionally, the specific examples in this embodiment can refer to the examples described in the above embodiments, but will not be described in detail in this embodiment.

[0094] Optionally, in this embodiment, the storage medium may include various media capable of storing program code, such as a USB memory, a ROM, a RAM, a removable hard disk, a magnetic disk, an optical disk, etc., but is not limited thereto.

[0095] In the description of this specification, a statement referring to "this embodiment," "one embodiment," "some embodiments," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in connection with that embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, general expressions using the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, a person skilled in the art may combine different embodiments or examples described herein, as well as features of different embodiments or examples, without mutual contradiction. In the description of this disclosure, "plurality" means at least two, e.g., two, three, etc., unless otherwise explicitly specified.

[0096] It is clear that the above embodiments are merely examples for the purpose of clarity and are not intended to limit the scope of the present invention. Those skilled in the art may make various modifications or changes based on the above description. A complete list of all implementations is not necessary or possible here. Any obvious modifications or changes derived therefrom fall within the scope of protection of the present invention.

Claims

1. 1. A method for determining an unsaturation parameter value, comprising the steps of: Determining a first predetermined number of unsaturated parameters to be determined and a range of values ​​of the unsaturated parameters in a second predetermined number of permeation compartments according to a predetermined model, the predetermined model being a VG model, the predetermined model being represented by the following formula: s is a model variable, y and n are parameters related to the pore distribution, α is a parameter related to the intake value, θ is the water content, and θ ｓ is the saturated volumetric water content, and θ ｒ is the remaining volumetric water content, k ｒ is the soil unsaturated permeability coefficient, s ｅ is an intermediate variable, and generating a third preset number of unsaturated parameter combinations based on the unsaturated parameters and the value ranges; Obtaining a finite element model and simulation calculation conditions based on the obtained observation data of the hydroelectric power generation construction; performing a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result; determining a target unsaturated parameter combination based on the simulation calculation result and the observation data of the hydroelectric power generation construction, and obtaining a value of the unsaturated parameter; generating a third preset number of unsaturated parameter combinations based on the unsaturated parameters and the ranges of values; determining a first unsaturated parameter, a second unsaturated parameter, and a remaining unsaturated parameter from the first preset number of unsaturated parameters to be determined; obtaining a relationship equation between the first unsaturation parameter and a second unsaturation parameter, the relationship equation and the first unsaturation parameter being representative of the second unsaturation parameter; and obtaining candidate values ​​of each of the unsaturated parameters in the permeable section by a preset method, which is an orthogonal design method, using the first unsaturated parameter, the relationship equation, the remaining unsaturated parameters, and the range of values, to generate a third preset number of combinations of the unsaturated parameters; The step of obtaining a finite element model and simulation calculation conditions based on the obtained observation data of the hydroelectric power generation construction, obtaining profile data points based on observed data of the hydroelectric construction; obtaining the finite element model based on the profile data points and a pre-defined grid type; generalizing the finite element model to divide the finite element model into a second predetermined number of the permeable compartments; obtaining permeation compartment parameters for the permeation compartment; obtaining boundary conditions and initial water level conditions for the finite element model based on observed data of the hydroelectric power generation construction; obtaining the simulation calculation conditions based on the permeation compartment parameters, the boundary conditions, and the initial water level conditions; The step of obtaining boundary conditions and initial water level conditions of the finite element model based on observation data of the hydroelectric power generation construction includes: A step of obtaining a water level line for a preset period based on observation data of a hydroelectric power generation construction project; determining a slope head boundary of the finite element model based on the waterline; A step of determining a water level value of the head boundary based on observation data of the hydroelectric power generation construction project, with the left boundary of the finite element model being a water head boundary, the step of determining the water level value of the head boundary based on the observation data of the hydroelectric power generation construction project includes: A step including a step of determining the water level value of the head boundary by inversion based on borehole water level observation data in the observation data of the hydroelectric power generation construction; Obtaining an actual observed head value based on observation data of the hydroelectric power generation construction work; obtaining a fourth preset number of watershed level values; Obtaining head calculation values ​​and corresponding boundary head values ​​for each borehole position according to a preset seepage analysis method and the watershed water level value; training an initial neural network using the head calculation values ​​and the boundary head values ​​to obtain a trained neural network; and inputting the measured observed head values ​​into the trained neural network to obtain the initial water level conditions.

2. The step of performing a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result includes: selecting one of the third preset number of unsaturated parameter combinations as an unsaturated parameter combination to be calculated; A step of performing a simulation calculation based on the unsaturated parameter combination of the calculation target, the finite element model, and the simulation calculation conditions, and obtaining a single combination simulation calculation result corresponding to the unsaturated parameter combination of the calculation target; A step of selecting one of the unsaturated parameter combinations from the third preset number of unsaturated parameter combinations as an unsaturated parameter combination to be calculated, and performing subsequent steps until a single combination simulation calculation result corresponding to each of the unsaturated parameter combinations is obtained; and a step of combining all the single combination simulation calculation results to obtain the simulation calculation result.

3. The step of determining a target unsaturated parameter combination and obtaining a value of the unsaturated parameter based on the simulation calculation result and the observation data of the hydroelectric power generation construction, determining a fifth preset number of detected data points; obtaining a zero pressure surface position at a preset time corresponding to each of the unsaturated parameter combinations based on the simulation calculation results; obtaining predicted data at each of the sensed data points for each of the unsaturated parameter combinations based on the zero pressure surface location and the sensed data points; obtaining actual measurement data corresponding to the prediction data based on observation data of the hydroelectric power generation construction work; calculating an error at each of the detected data points for each of the non-saturated parameter combinations based on the predicted data and the measured data; calculating a total error corresponding to each of the unsaturated parameter combinations based on the errors; and identifying the unsaturated parameter combination that corresponds to a minimum total error as the target unsaturated parameter combination that includes the numerical values ​​of the unsaturated parameters.

4. 1. An apparatus for determining an unsaturation parameter value, comprising: a determination module for determining a first predetermined number of unsaturated parameters to be determined and a range of values ​​of said unsaturated parameters at a second predetermined number of permeation compartments according to a predetermined model, The preset model is a VG model, and the preset model is expressed by the following formula: s is a model variable, y and n are parameters related to the pore distribution, α is a parameter related to the intake value, θ is the water content, and θ ｓ is the saturated volumetric water content, and θ ｒ is the remaining volumetric water content, k ｒ is the soil unsaturated permeability coefficient, s ｅ is an intermediate variable, the decision module, a generation module that generates a third preset number of unsaturated parameter combinations based on the unsaturated parameters and the value ranges; A first acquisition module for acquiring a finite element model and a simulation calculation condition based on the acquired observation data of the hydroelectric power generation construction; a calculation module that performs a simulation calculation based on the unsaturated parameter combination, the finite element model, and the simulation calculation conditions to obtain a simulation calculation result; A second acquisition module is configured to determine a target unsaturated parameter combination based on the simulation calculation result and the observation data of the hydroelectric power generation construction, and obtain a value of the unsaturated parameter; The generating module includes: a first determination unit for determining a first unsaturated parameter, a second unsaturated parameter, and a remaining unsaturated parameter from the first preset number of unsaturated parameters to be determined; a first acquisition unit for acquiring a relationship equation between the first unsaturation parameter and a second unsaturation parameter, the relationship equation and the first unsaturation parameter representing the second unsaturation parameter; a generating unit for obtaining candidate values ​​of each of the unsaturated parameters in the permeation section according to the first unsaturated parameter, the relationship equation, the remaining unsaturated parameters, the value range, and a preset method, to generate a third preset number of combinations of the unsaturated parameters; The first acquisition module includes: A first acquisition unit for acquiring profile data points based on observation data of the hydroelectric power construction; a second acquisition unit for acquiring the finite element model based on the profile data points and a pre-defined grid type; a division unit for generalizing the finite element model to divide the finite element model into a second preset number of the permeation compartments; a second acquisition unit for acquiring a permeation compartment parameter of the permeation compartment; a third acquisition unit for acquiring boundary conditions and initial water level conditions of the finite element model based on observed data of the hydroelectric power generation project; a fourth acquisition unit for obtaining the simulation calculation conditions according to the permeation compartment parameters, the boundary conditions and the initial water level conditions; The third acquisition unit includes: A first acquisition submodule for acquiring a water level line for a preset period based on observation data of a hydroelectric power generation construction project; a first determination sub-module for determining a slope head boundary of the finite element model based on the waterline; A second determination submodule for determining a water level value of the head boundary based on observation data of a hydroelectric power generation project, with the left boundary of the finite element model as the head boundary, and determining the water level value of the head boundary based on the observation data of the hydroelectric power generation project includes a step of determining the water level value of the head boundary by inversion based on borehole water level observation data in the observation data of the hydroelectric power generation project; A second acquisition submodule for acquiring an actual observed head value based on the observation data of the hydroelectric power generation construction; a fourth pre-defined number of watershed level values; and a fourth acquisition sub-module for obtaining a head calculation value and a corresponding boundary head value of each borehole position according to a preset seepage analysis method and a watershed water level value; a training submodule for training an initial neural network using the head calculation value and the boundary head value to obtain a trained neural network; and a third acquisition sub-module that inputs the measured observed head values ​​into the trained neural network to obtain initial water level conditions.

5. A processor, a communication interface, a memory, and a communication bus; The processor, the communication interface, and the memory are in communication with each other via the communication bus; The memory stores a computer program; The electronic device, wherein the processor executes the method steps according to any one of claims 1 to 3 by operating the computer program stored in the memory.

6. A computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method steps according to any one of claims 1 to 3.

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