An infiltration parameter determination method and system based on hierarchical measurement and numerical simulation

Abstract

The application relates to an infiltration parameter determination method and system based on layered actual measurement and numerical simulation. The technical problem of lacking efficiency, accuracy and flexibility in the existing infiltration parameter determination process is solved. The method comprises the following steps: detecting the physical property data of soil according to the layered soil sample of the in-situ soil layer structure of a to-be-measured area; constructing a transfer function between basic physical indexes and soil hydraulic parameters according to the main physical property data, forming a soil seepage model according to the basic physical indexes, the soil hydraulic parameters and the in-situ soil layer structure; simulating the infiltration according to the actual working condition of the double-ring infiltration, and calibrating according to the in-situ short-time measured data; and determining the distributed infiltration parameters of the to-be-measured area through the soil seepage model according to the soil layer structure of the to-be-measured area. The in-situ soil profile layered actual measurement, multi-dimensional parameter optimization calibration and modeling accurate copying of the double-ring test working condition replace the traditional field test mode, and the technical problem of conventional numerical simulation distortion and unreliability is solved.

Description

Technical Field

[0001] This invention relates to the field of soil hydrodynamics, specifically to a method and system for determining infiltration parameters based on stratified field measurements and numerical simulations. Background Technology

[0002] In existing technologies, soil infiltration parameter determination mainly employs the double-ring infiltration field test method and the indoor soil column infiltration test method. The double-ring infiltration field test method is the current national standard for soil infiltration testing. Its core principle involves pressing inner and outer circular steel rings into the surface soil. A constant water head is maintained by continuously supplying water to the inner rings. The water pressure in the outer ring blocks lateral seepage around the soil, creating an approximately vertical one-dimensional infiltration flow in the inner ring area. By recording the change in infiltration volume over time, core hydrological parameters such as instantaneous infiltration rate, steady-state infiltration rate, and cumulative infiltration volume are determined. The indoor soil column infiltration test method involves collecting undisturbed or reconstituted soil columns indoors and conducting infiltration tests under controlled laboratory conditions to determine saturated hydraulic conductivity and infiltration parameters.

[0003] However, in practical applications, the double-ring infiltration field test method suffers from technical problems such as cumbersome procedures, high manpower and material costs, long test cycles, and inability to be implemented in complex sites. For example, a single-point test typically takes 4-8 hours. In engineering projects requiring large-area surveys or multiple-point deployments, the long test cycle and high labor costs may prevent its implementation in water-scarce areas. It can only measure the overall infiltration rate of the soil below the surface. When there are multiple soil layers with significantly different properties in the soil profile, the test results cannot distinguish the hydraulic characteristics of each layer and cannot provide parameter support for stratified modeling. The test results are greatly affected by differences in human operation, environmental factors such as meteorological conditions during the test, and geological conditions such as gravel layers, karst development areas, groundwater level depth, and slopes, which can lead to technical obstacles or even complete impossibility. Field tests can only reflect the infiltration characteristics under the initial soil moisture content and meteorological conditions at the time of the test. They cannot freely adjust water head and groundwater level parameters, cannot achieve multivariate comparative simulation, and cannot predict the infiltration response under different antecedent rainfall conditions, different water head heights, or different rainfall intensities. While the indoor soil column infiltration test method offers good controllability, it suffers from problems such as sampling disturbance, sidewall effect, and inability to reflect the in-situ soil structure. Summary of the Invention

[0004] To address the aforementioned problems, embodiments of the present invention provide a method and system for determining infiltration parameters based on stratified field measurements and numerical simulations, thereby solving the technical problems of inefficiency, accuracy, and flexibility in existing infiltration parameter determination processes.

[0005] The method for determining infiltration parameters based on stratified field measurements and numerical simulations according to embodiments of the present invention includes: The physical properties of the soil were determined based on the layered soil samples from the in-situ soil structure of the area to be tested. Based on the main physical property data, a transfer function between basic physical indicators and soil hydraulic parameters is constructed, and a soil seepage model is formed based on the basic physical indicators, soil hydraulic parameters and in-situ soil structure. The soil seepage model simulates infiltration based on the actual working conditions of double-ring infiltration and is calibrated based on in-situ short-time measured data. The soil seepage model is used to quantify infiltration parameters. Based on the soil structure of the area to be tested, distributed infiltration parameters of the area to be tested are determined using a soil seepage model.

[0006] In one embodiment of the present invention, the step of detecting the physical property data of the soil based on the layered soil samples of the in-situ soil structure of the area to be tested includes: In typical sections of the area to be tested, the in-situ soil geometry was obtained by vertically excavating complete vadose zone profiles, and the physical property data of soil layer stratification were quantified. Based on the soil layering, layered soil samples were collected and soil sample parameters were tested to quantify the measured physical property parameters of the soil samples.

[0007] In one embodiment of the present invention, the formation of the soil seepage model includes: By utilizing physical property data in the machine learning process, the nonlinear mapping relationship between basic physical indicators and soil hydraulic parameters is obtained, forming a transfer function that quantifies soil hydraulic parameters through basic physical indicators; Based on the constraints of basic physical indicators, soil hydraulic parameters obtained through transfer functions are used to form complete soil hydraulic parameter data for stratified soil samples. A soil seepage model was established based on the in-situ soil structure, soil hydraulic parameters and basic physical indicators of layered soil samples.

[0008] In one embodiment of the present invention, the soil seepage model simulates infiltration based on the actual working conditions of double-ring infiltration, and the calibration based on in-situ short-time measured data includes: A soil seepage model was set up to simulate the working conditions based on the standard double-ring infiltration process in the field. The water flow patterns in a standard double-ring infiltration process in the field were simulated based on Richard's equations and the VG model. Soil seepage model inversion calibration was performed based on in-situ short-time measured data.

[0009] In one embodiment of the present invention, the step of determining the distributed infiltration parameters of the test area based on the soil layer structure of the test area using a soil seepage model includes: Based on the distribution of soil layer structure in the geographic model of the area to be tested, soil seepage models are set up, and standard double-ring infiltration experiments are conducted in batches for numerical simulation. Based on the numerical simulation results, infiltration characteristic parameters and hydrological information are output.

[0010] The infiltration parameter determination based on stratified field measurements and numerical simulations in this invention includes: The measured data acquisition device is used to detect the physical properties of the soil based on the layered soil samples of the in-situ soil structure of the area to be tested; A soil model building device is used to construct a transfer function between basic physical indicators and soil hydraulic parameters based on the main physical property data, and to form a soil seepage model based on the basic physical indicators, soil hydraulic parameters and in-situ soil structure. The numerical simulation optimization device is used to simulate the infiltration of the soil seepage model based on the actual working conditions of double-ring infiltration, and to calibrate it based on in-situ short-time measured data. The infiltration parameters are quantified through the soil seepage model. The infiltration distribution simulation device is used to determine the distributed infiltration parameters of the test area based on the soil layer structure and a soil seepage model.

[0011] In one embodiment of the present invention, the measured data acquisition device includes: The structural data acquisition module is used to obtain the in-situ soil geometry by vertically excavating a complete vadose zone profile in a typical section of the area to be tested, and to quantify the physical property data of the soil layers. The feature data acquisition module is used to collect soil samples and test soil parameters according to soil layer stratification, and quantify the measured physical property parameters of the soil samples.

[0012] In one embodiment of the present invention, the soil model construction device includes: The transfer function construction module is used to obtain the nonlinear mapping relationship between basic physical indicators and soil hydraulic parameters in the machine learning process using physical property data, and to form a transfer function that quantifies soil hydraulic parameters through basic physical indicators. The function constraint construction module is used to constrain the soil hydraulic parameters obtained by the transfer function based on the basic physical index, and form complete soil hydraulic parameter data of the layered soil sample. The seepage model construction module is used to establish a soil seepage model based on the in-situ soil structure, soil hydraulic parameters and basic physical indicators of layered soil samples.

[0013] In one embodiment of the present invention, the numerical simulation optimization device includes: The simulation working condition definition module is used to set up a soil seepage model to simulate working conditions based on the standard double-ring infiltration process in the field. The simulated operating condition control module is used to simulate the water flow movement law of the standard double-ring infiltration process in the field according to Richard's equation and VG model. The simulated working condition calibration module is used to perform soil seepage model inversion calibration based on in-situ short-time measured data.

[0014] In one embodiment of the present invention, the infiltration distribution simulation device includes: The infiltration simulation planning module is used to distribute and deploy soil seepage models in the geographic model of the area to be tested according to the soil structure, and to perform numerical simulations of standard double-ring infiltration experiments in batches. The infiltration data application module is used to output infiltration characteristic parameters and hydrological information based on numerical simulation results.

[0015] The infiltration parameter determination method and system based on stratified field measurement and numerical simulation of this invention accurately replicates the dual-loop test conditions through in-situ stratified soil profile measurement, multi-dimensional parameter optimization and calibration, and modeling. This replaces the traditional, relatively high-intensity, and highly discrete field test mode, solving the technical problems of distortion and unreliability in conventional numerical simulation. While reducing field operation costs and improving data stability and accuracy, it obtains stratified and refined infiltration data that is impossible with traditional techniques. Simultaneously, it supports multi-condition extended simulation, achieving efficient, accurate, batch-ready, and multi-scenario adaptable in-situ soil infiltration capacity evaluation. Attached Figure Description

[0016] Figure 1 The diagram shown is a flowchart of an embodiment of the present invention for determining infiltration parameters based on stratified field measurements and numerical simulations.

[0017] Figure 2 The diagram shown is a schematic representation of the architecture of an infiltration parameter measurement system based on stratified field measurements and numerical simulation, according to an embodiment of the present invention.

[0018] Figure 3 The diagram shown is a schematic diagram of the architecture of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0019] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0020] An embodiment of the present invention provides a method for determining infiltration parameters based on stratified field measurements and numerical simulations, as follows: Figure 1 As shown. In Figure 1 In this embodiment, the following are included: Step 100: Analyze the physical properties of the soil based on the layered soil samples from the in-situ soil structure of the area to be tested.

[0021] The in-situ soil layer structure is obtained from hydrogeologically representative points in the area to be measured. Layered soil samples with different physical properties are obtained from soil samples in the soil layer structure through natural interface stratification. The geometric structure of the in-situ soil layer structure is quantified based on the layered soil samples. Furthermore, basic measured data of physical parameters required for numerical simulation using the Richards equation and related models are obtained through laboratory testing of the layered soil samples. In the numerical simulation of soil water dynamics in this field, the Richards equation technique is a classic governing equation describing water migration in unsaturated soil in the vadose zone, and it can accurately characterize the whole process of soil water infiltration, wetting front advancement, and dynamic evolution of water content under the dual effects of gravity and matrix suction. Van Genuchten-Mualem (V-G) model is a soil constitutive model supporting the Richards equation. It can quantitatively describe the variation law of soil water characteristic curve and unsaturated hydraulic conductivity with water content through fitting parameters, and is a necessary supporting model for numerical solution of unsaturated seepage. The measured data of main physical parameters, both easily measurable and difficultly measurable, of the soil constitutive model can be obtained in laboratory environment through general detection methods.

[0022] Step 200: constructing a transfer function between basic physical indicators and soil hydraulic parameters according to the main physical property data, and forming a soil seepage model based on the basic physical indicators, soil hydraulic parameters and the in-situ soil layer structure.

[0023] Those skilled in the art can understand that the hydraulic characteristic parameters of soil samples can be obtained through laboratory testing. According to the non-linear implicit correlation between hydraulic characteristic parameters and physical characteristic parameters, a transfer function is constructed by using a numerical fitting process to form a mapping process between soil sample physical characteristic parameters and hydraulic characteristic parameters. The transfer function can be trained by using machine learning algorithms such as random forest with the physical characteristic parameters and hydraulic characteristic parameters obtained in the laboratory. The transfer function of soil is further formed from the transfer function of soil samples. Through refined grid division of the in-situ soil layer structure, the independent physical characteristic parameters and hydraulic characteristic parameters of each soil sample, combined with the geometric structure of the in-situ soil layer, form a numerical simulation model of the in-situ soil layer that fits the in-situ hydrogeological conditions. Different hydrogeologically representative points can form corresponding numerical simulation models.

[0024] Step 300: the soil seepage model performs infiltration simulation according to the actual working condition of double-ring infiltration, is calibrated according to in-situ short-term measured data, and realizes quantification of infiltration parameters through the soil seepage model.

[0025] Boundary conditions for infiltration simulation in the soil seepage model are defined based on actual working conditions to ensure equivalence between the simulated conditions and the actual test. The Richard unsaturated seepage equation is discretized using a numerical method, coupled with the VG model, and the parameters of each soil layer are substituted. The simulation duration and adaptive time step are set to be consistent with the actual test. The soil profile moisture content distribution, matrix suction distribution, and vertical seepage rate at different times are iteratively solved to simulate the entire process of initial infiltration decay and steady-state infiltration. To eliminate errors from laboratory tests, transfer function estimation biases, and systematic errors introduced by numerical modeling, in-situ short-time measured data are used for inversion calibration of the soil seepage model. The calibrated soil seepage model can quantify conventional indicators such as instantaneous infiltration rate, steady-state infiltration rate, cumulative infiltration volume, and time to stabilization. Simultaneously, it can obtain quantified fine indicators that are difficult to obtain in traditional double-ring infiltration tests, such as the stratified infiltration contribution rate, the wetting front advancement process, and the location of the limiting soil layer.

[0026] Step 400: Based on the soil structure of the area to be tested, the distributed infiltration parameters of the area to be tested are determined using a soil seepage model.

[0027] Based on the typical soil structure characteristics of the test area, corresponding soil seepage models and GIS (Geographic Information System) resources are used in the computer to construct soil seepage models in batches within the test area according to soil structure and soil type. This achieves infiltration characteristic parameters equivalent to those of field tests, including instantaneous infiltration rate, steady-state infiltration rate, cumulative infiltration volume, and time to steady-state. At the same time, it obtains refined hydrological information that is difficult to characterize by traditional tests, such as the contribution rate of stratified infiltration, the process of wetting front movement, and the spatial distribution of confining soil layers, thus achieving an efficient replacement for field double-ring infiltration tests.

[0028] The infiltration parameter determination method based on stratified field measurement and numerical simulation in this invention replaces the traditional, relatively high-intensity, and highly discrete field test mode by accurately replicating the dual-loop test conditions through in-situ stratified soil profile measurement, multi-dimensional parameter optimization and calibration, and modeling. This solves the technical problems of distortion and unreliability in conventional numerical simulation. While reducing field operation costs and improving data stability and accuracy, it obtains stratified and refined infiltration data that is impossible with traditional techniques. At the same time, it supports multi-condition extended simulation, realizing efficient, accurate, batch-compatible, and multi-scenario adaptable in-situ soil infiltration capacity evaluation.

[0029] like Figure 1 As shown, in one embodiment of the present invention, step 100 includes: Step 110: Obtain the in-situ soil geometry by vertically excavating a complete vadose zone profile in a typical section of the area to be tested, and quantify the physical property data of the soil layers.

[0030] Typical locations were selected, avoiding atypical areas such as backfilled soil, depressions, and areas with disturbed vegetation, ensuring the sites were representative of the hydrogeological conditions of the area under test. For complete vadose zone profiles, soil layers were strictly divided according to natural interfaces such as soil lithology, density, pore structure, plow pan, and crust layer, ensuring no layer crossings or mixing. Layer-by-layer soil thickness, depth, groundwater level depth, topographic slope, and surface cover type were measured and recorded. Commonly used methods in the field included soil profile excavation tools, undisturbed soil samplers, disturbed soil samplers, short-term water replenishment monitoring equipment, and moisture content monitoring equipment to obtain information on the soil structure, layered soil samples, and in-situ initial moisture conditions.

[0031] Step 120: Collect soil samples and test soil parameters according to the soil layer stratification to quantify the measured physical property parameters of the soil samples.

[0032] For each soil layer, undisturbed and disturbed soil samples were collected separately, and parameters were classified and tested according to the basic parameter requirements of Richard's unsaturated seepage equation. Parameter testing for undisturbed soil samples included, but was not limited to, dry density, porosity, saturated water content, saturated hydraulic conductivity, and soil moisture characteristic curves. Parameter testing for disturbed soil samples included, but was not limited to, particle size distribution, organic matter content, and soil texture. Commonly used instruments in this field, such as particle size analyzers, density meters, pressure membrane meters, and saturated hydraulic conductivity meters, were employed to determine the physical and unsaturated hydraulic parameters of the soil samples. All the basic measured parameters required for solving Richard's equation were obtained, eliminating parameter distortion from single surface sampling.

[0033] The infiltration parameter determination method based on layered field measurement and numerical simulation in this invention obtains in-situ soil layer data through layered delineation and detection. This provides accurate geometric boundary physical property parameters and basic measured parameters for numerical modeling, ensuring the reliability and authenticity of the physical boundaries and model parameter initialization in subsequent numerical simulations.

[0034] like Figure 1 As shown, in one embodiment of the present invention, step 200 includes: Step 210: Utilize physical property data to obtain the nonlinear mapping relationship between basic physical indicators and soil hydraulic parameters during the machine learning process, and form a transfer function that quantifies soil hydraulic parameters through basic physical indicators.

[0035] The transfer function is used to achieve accurate conversion from easily measurable physical parameters to difficult-to-measurable hydraulic parameters. In one embodiment of the present invention, a dataset containing characteristic curves of clay content, silt content, dry density, organic matter, and moisture content, as well as VG model parameters, is constructed. Machine learning algorithms such as random forest are used for training to establish a transfer function suitable for the soil hydraulic parameters of the region. Specifically, the inputs (features) include clay content, silt content, dry density, and organic matter content, while the outputs (targets) include VG model parameters (residual water content θr, scale parameter α, shape parameter n), saturated hydraulic conductivity, etc. Utilizing the regression method based on ensemble learning using random forest, by averaging and integrating the prediction results of multiple decision trees, the nonlinear relationship between soil physical indicators and hydraulic parameters can be effectively captured. This method has advantages such as strong anti-interference ability, good generalization performance, and low overfitting rate.

[0036] Step 220: Based on the constraints of the basic physical indicators, the soil hydraulic parameters obtained through the transfer function are used to form complete soil hydraulic parameter data for the stratified soil samples.

[0037] Soil hydraulic parameters obtained from the transfer function need to be calibrated using physical constraints such as measured total porosity and saturated water content in basic physical indices to ensure that empirical parameters conform to the true physical laws of the soil and significantly reduce parameter estimation errors.

[0038] Step 230: Establish a soil seepage model based on the in-situ soil structure, soil hydraulic parameters and basic physical indicators of the layered soil samples.

[0039] Soil seepage models are used to recreate the real layered heterogeneous seepage structure of soil. A two-dimensional axisymmetric numerical model is constructed based on the measured structure of in-situ soil layers, while also adapting to the radially symmetrical seepage characteristics of double-ring infiltration. In one embodiment of the invention, the in-situ soil layers are finely meshed, and the measured and optimized hydraulic parameters are independently assigned to each soil layer. Boundary conditions are uniformly set: the central axis is the symmetrical boundary, the lateral boundary is the no-flow boundary, and the bottom is set with free drainage or constant head boundary according to the groundwater level, which conforms to the in-situ hydrogeological conditions.

[0040] The infiltration parameter determination method based on stratified field measurements and numerical simulations in this invention reduces the quantification cost of soil hydraulic parameters (equipment, cycle time, soil sample disturbance, and measured density) by constructing transfer functions. This makes it easier to convert and complete saturated hydraulic conductivity Ks, residual water content θr, field capacity, VG model parameters, and soil moisture characteristic curves, significantly reducing the workload of field and laboratory experiments. The parameter accuracy is more closely aligned with the soil properties of the test area than general empirical formulas, making the soil seepage model more locally specific.

[0041] like Figure 1 As shown, in one embodiment of the present invention, step 300 includes: Step 310: Set up a soil seepage model to simulate the working conditions based on the standard double-ring infiltration process in the field.

[0042] The simulated working conditions, based on the boundary conditions of the standard double-ring infiltration test in the field, include: According to the standard double-ring infiltration meter dimensions, the model surface was divided into inner ring, outer ring, and outer ring areas; The experimental principle is to apply the same constant water head to both the inner and outer rings, restore the pressure stability of the outer ring, block lateral seepage, and allow vertical seepage to be the main feature of the inner ring. An atmospheric flow-free boundary is set for the outer area to achieve boundary constraints consistent with national standard tests.

[0043] Ensure that subsequent numerical simulation results can directly and equivalently replace field measurement results.

[0044] Step 320: Simulate the water flow patterns of a standard double-ring infiltration process in the field based on Richard's equations and the VG model.

[0045] Using Richard's unsaturated seepage equation as the governing equation and combining it with the VG soil hydraulic property model to form a closed equation system, a numerical method was employed to spatially discretize and iteratively solve the soil seepage model over time. Hydraulic parameters of each soil layer, obtained through measured measurements, transfer function derivation, and physical constraint calibration, were layered and assigned to the soil seepage model. A simulation duration and adaptive time step consistent with field experiments were set, and the soil profile moisture content field, matrix suction field, and vertical seepage velocity field were iteratively calculated at each time step, fully reproducing the entire process of water flow from initial infiltration, attenuation transition to stable infiltration. The resulting basic calculations are then presented.

[0046] Step 330: Perform soil seepage model inversion calibration based on in-situ short-time measured data.

[0047] One to three typical locations within the test area were selected, and a small amount of in-situ short-term measured data was obtained through short-term water replenishment observation and surface moisture content monitoring. Using the in-situ measured data as constraints, and aiming to minimize the error between simulated and measured values, a general optimization algorithm was used to invert and adjust the sensitive hydraulic parameters of the soil seepage model, correcting systematic errors caused by modeling and parameter estimation, and ensuring that the simulated infiltration process and results highly match the actual infiltration patterns on site.

[0048] The infiltration parameter determination method based on stratified field measurements and numerical simulation in this invention improves the overall simulation accuracy and parameter reliability by replicating operating conditions, performing spatiotemporal iterative solutions, and using measured data for inversion calibration. This makes the soil seepage model more closely match actual soil conditions. Simultaneously, it quantifies conventional indicators and obtains detailed indicators that are difficult to obtain in traditional double-ring infiltration tests, such as stratified infiltration contribution rate, wetting front propagation process, and location of confining soil layers.

[0049] like Figure 1As shown, in one embodiment of the present invention, step 400 includes: Step 410: Based on the soil structure, deploy soil seepage models in the geographic model of the area to be tested, and conduct numerical simulations of standard double-ring infiltration experiments in batches.

[0050] A geographic model of the area to be tested is created using computer technology and GIS resources. Based on the geographic model, a soil seepage model is adapted according to the soil structure and soil type. The distributed soil seepage models form a full-process simulation, data calculation, and parameter acquisition for a standard double-ring infiltration experiment.

[0051] Step 420: Output infiltration characteristic parameters and hydrological information based on the numerical simulation results.

[0052] Infiltration characteristic parameters include, but are not limited to, instantaneous infiltration rate, steady-state infiltration rate, cumulative infiltration volume, and time to stabilization. Hydrological information includes, but is not limited to, refined hydrological information such as the contribution rate of stratified infiltration, the migration process of wetting fronts, and the spatial distribution of confining soil layers, which are difficult to characterize by traditional tests, thus achieving an efficient and equivalent replacement for field double-ring infiltration tests.

[0053] The infiltration parameter determination method based on stratified field measurement and numerical simulation in this invention significantly reduces field workload, shortens the test cycle, and lowers costs, while achieving equivalent substitution and information expansion for the results of field physical double-ring infiltration tests. It provides high-precision and high-resolution data support for regional soil infiltration capacity evaluation, hydrological process simulation, and related engineering calculations.

[0054] In one embodiment of the present invention, the finite difference method is preferred for solving the Richard equation, but it can also be equivalently replaced by the finite element method or the finite volume method for discrete iterative solution of the equation.

[0055] In one embodiment of the present invention, a two-dimensional axisymmetric numerical model constructed based on the measured structure of in-situ soil layers can be directly replaced by a three-dimensional layered heterogeneous model. This is suitable for refined infiltration simulation of large-scale, complex terrain sites.

[0056] In one embodiment of the present invention, the parameter acquisition method of actual measurement + soil transfer function conversion can be completely replaced by the mode of actual measurement of parameters in full indoor test (all hydraulic parameters are completely measured by pressure membrane instrument and permeameter).

[0057] In one embodiment of the present invention, the double-ring test condition in which the same constant water head is applied to the inner and outer rings can be effectively replaced by the double-ring test condition with variable water head, the double-ring test condition with dynamic water head due to natural rainfall, or the double-ring test condition with dynamic changes in groundwater depth, in order to adapt to specific hydrological scenarios.

[0058] In one embodiment of the present invention, for complex soils, structural correction factors and dual-porosity models can be used, and the VG model can be equivalently replaced by a large-pore permeability correction model and a temperature coupling correction model to adapt to special sites such as frozen soil and cracked soil.

[0059] In one embodiment of the present invention, in-situ short-time measured data can be replaced with profile moisture content monitoring data, wetting front burial depth observation data, and in-situ matrix potential data to complete model inversion calibration.

[0060] An embodiment of the present invention provides a system for measuring infiltration parameters based on stratified field measurements and numerical simulations, as follows: Figure 2 As shown. In Figure 2 In this embodiment, the following are included: The measured data acquisition device 10 is used to detect the physical properties of the soil based on the layered soil samples of the in-situ soil structure of the area to be tested. Soil model building device 20 is used to build a transfer function between basic physical indicators and soil hydraulic parameters based on the main physical property data, and to form a soil seepage model based on the basic physical indicators, soil hydraulic parameters and in-situ soil structure. The numerical simulation optimization device 30 is used to simulate the infiltration of the soil seepage model based on the actual working conditions of double-ring infiltration, and to calibrate it based on in-situ short-time measured data. The soil seepage model is used to quantify the infiltration parameters. The infiltration distribution simulation device 40 is used to determine the distributed infiltration parameters of the area under test based on the soil structure of the area under test and through a soil seepage model.

[0061] like Figure 2 As shown, in one embodiment of the present invention, the measured data acquisition device 10 includes: The structural data acquisition module 11 is used to obtain the in-situ soil geometry by vertically excavating a complete vadose zone profile in a typical section of the area to be tested, and to quantify the physical property data of the soil layers. The feature data acquisition module 12 is used to collect layered soil samples and detect soil parameters according to soil layering, and quantify the measured physical property parameters of the soil samples.

[0062] like Figure 2 As shown, in one embodiment of the present invention, the soil model construction device 20 includes: The transfer function construction module 21 is used to obtain the nonlinear mapping relationship between basic physical indicators and soil hydraulic parameters in the machine learning process using physical property data, and to form a transfer function that quantifies soil hydraulic parameters through basic physical indicators. Function constraint construction module 22 is used to constrain the soil hydraulic parameters obtained by the transfer function according to the basic physical index to form complete soil hydraulic parameter data of the layered soil sample; The seepage model construction module 23 is used to establish a soil seepage model based on the in-situ soil structure, soil hydraulic parameters and basic physical indicators of layered soil samples.

[0063] like Figure 2 As shown, in one embodiment of the present invention, the numerical simulation optimization device 30 includes: The simulation working condition definition module 31 is used to set up the soil seepage model to simulate working conditions based on the standard double-ring infiltration process in the field. The simulation operating condition control module 32 is used to simulate the water flow movement law of the standard double-ring infiltration process in the field according to Richard's equation and VG model. The simulated working condition calibration module 33 is used to perform soil seepage model inversion calibration based on in-situ short-time measured data.

[0064] like Figure 2 As shown, in one embodiment of the present invention, the infiltration distribution simulation device 40 includes: The infiltration simulation planning module 41 is used to distribute and deploy soil seepage models in the geographic model of the area to be tested according to the soil structure, and to perform numerical simulation of standard double-ring infiltration experiments in batches. The infiltration data application module 42 is used to output infiltration characteristic parameters and hydrological information based on the numerical simulation results.

[0065] This application also provides an electronic device, the structure of which is as follows: Figure 3 As shown, the electronic device 4000 includes at least one processor 4001, a memory 4002, and a bus 4003. At least one processor 4001 is electrically connected to the memory 4002. The memory 4002 is configured to store at least one computer-executable instruction, and the processor 4001 is configured to execute the at least one computer-executable instruction to perform the steps of the infiltration parameter determination method based on stratified field measurement and numerical simulation provided in any embodiment or optional implementation of this application.

[0066] Furthermore, the processor 4001 can use a general-purpose processor (CPU) to run software programs to implement all module functions, which is the most flexible implementation method; it can also use a graphics processing unit (GPU) to accelerate the three-dimensional coordinate mapping and rendering process, utilizing the massive parallel computing capabilities of the GPU to improve performance; or it can use an application-specific integrated circuit (ASIC) or a field-programmable gate array (FPGA) to embed some or all modules in hardware, suitable for embedded scenarios with extremely high real-time requirements (such as submarine sonar display and control consoles). In addition, a distributed processing architecture can be adopted, deploying different modules on different processors to work collaboratively. Regardless of the processing unit or hardware architecture used, as long as the algorithm executed and the functions implemented meet the technical requirements of the present invention, they should be considered equivalent embodiments of the present invention.

[0067] This application also provides another computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for determining infiltration parameters based on stratified field measurements and numerical simulations provided in any embodiment or optional implementation of this application.

[0068] The computer-readable storage media provided in this application include, but are not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic cards, or optical cards. In other words, readable storage media include any medium by which a device (e.g., a computer) stores or transmits information in a readable form.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for determining infiltration parameters based on stratified field measurements and numerical simulation, characterized in that, include: The physical properties of the soil were determined based on the layered soil samples from the in-situ soil structure of the area to be tested. Based on the main physical property data, a transfer function between basic physical indicators and soil hydraulic parameters is constructed, and a soil seepage model is formed based on the basic physical indicators, soil hydraulic parameters and in-situ soil structure. The soil seepage model simulates infiltration based on the actual working conditions of double-ring infiltration and is calibrated based on in-situ short-time measured data. The soil seepage model is used to quantify infiltration parameters. Based on the soil structure of the area to be tested, distributed infiltration parameters of the area to be tested are determined using a soil seepage model.

2. The method for determining infiltration parameters based on stratified field measurements and numerical simulation according to claim 1, characterized in that, The physical property data of the soil obtained from the analysis of layered soil samples based on the in-situ soil structure of the area to be tested include: In typical sections of the area to be tested, the in-situ soil geometry was obtained by vertically excavating complete vadose zone profiles, and the physical property data of soil layer stratification were quantified. Based on the soil layering, layered soil samples were collected and soil sample parameters were tested to quantify the measured physical property parameters of the soil samples.

3. The method for determining infiltration parameters based on stratified field measurements and numerical simulation according to claim 1, characterized in that, The formation of the soil seepage model includes: By utilizing physical property data in the machine learning process, the nonlinear mapping relationship between basic physical indicators and soil hydraulic parameters is obtained, forming a transfer function that quantifies soil hydraulic parameters through basic physical indicators; Based on the constraints of basic physical indicators, soil hydraulic parameters obtained through transfer functions are used to form complete soil hydraulic parameter data for stratified soil samples. A soil seepage model was established based on the in-situ soil structure, soil hydraulic parameters and basic physical indicators of layered soil samples.

4. The method for determining infiltration parameters based on stratified field measurements and numerical simulation according to claim 1, characterized in that, The soil seepage model is simulated based on the actual double-ring infiltration condition, and calibrated based on in-situ short-time measured data, including: A soil seepage model was set up to simulate the working conditions based on the standard double-ring infiltration process in the field. The water flow patterns in a standard double-ring infiltration process in the field were simulated based on Richard's equations and the VG model. Soil seepage model inversion calibration was performed based on in-situ short-time measured data.

5. The method for determining infiltration parameters based on stratified field measurements and numerical simulation according to claim 1, characterized in that, The determination of distributed infiltration parameters in the test area based on the soil layer structure and using a soil seepage model includes: Based on the distribution of soil layer structure in the geographic model of the area to be tested, soil seepage models are set up, and standard double-ring infiltration experiments are conducted in batches for numerical simulation. Based on the numerical simulation results, infiltration characteristic parameters and hydrological information are output.

6. A method for determining infiltration parameters based on stratified field measurements and numerical simulation, characterized in that, include: The measured data acquisition device is used to detect the physical properties of the soil based on the layered soil samples of the in-situ soil structure of the area to be tested; A soil model building device is used to construct a transfer function between basic physical indicators and soil hydraulic parameters based on the main physical property data, and to form a soil seepage model based on the basic physical indicators, soil hydraulic parameters and in-situ soil structure. The numerical simulation optimization device is used to simulate the infiltration of the soil seepage model based on the actual working conditions of double-ring infiltration, and to calibrate it based on in-situ short-time measured data. The infiltration parameters are quantified through the soil seepage model. The infiltration distribution simulation device is used to determine the distributed infiltration parameters of the test area based on the soil layer structure and a soil seepage model.

7. The infiltration parameter determination based on stratified field measurements and numerical simulation as described in claim 6, characterized in that, The measured data acquisition device includes: The structural data acquisition module is used to obtain the in-situ soil geometry by vertically excavating a complete vadose zone profile in a typical section of the area to be tested, and to quantify the physical property data of the soil layers. The feature data acquisition module is used to collect soil samples and test soil parameters according to soil layer stratification, and quantify the measured physical property parameters of the soil samples.

8. The infiltration parameter determination based on stratified field measurements and numerical simulation as described in claim 6, characterized in that, The soil model construction device includes: The transfer function construction module is used to obtain the nonlinear mapping relationship between basic physical indicators and soil hydraulic parameters in the machine learning process using physical property data, and to form a transfer function that quantifies soil hydraulic parameters through basic physical indicators. The function constraint construction module is used to constrain the soil hydraulic parameters obtained by the transfer function based on the basic physical index, and form complete soil hydraulic parameter data of the layered soil sample. The seepage model construction module is used to establish a soil seepage model based on the in-situ soil structure, soil hydraulic parameters and basic physical indicators of layered soil samples.

9. The infiltration parameter determination based on stratified field measurements and numerical simulation as described in claim 6, characterized in that, The numerical simulation optimization device includes: The simulation working condition definition module is used to set up a soil seepage model to simulate working conditions based on the standard double-ring infiltration process in the field. The simulated operating condition control module is used to simulate the water flow movement law of the standard double-ring infiltration process in the field according to Richard's equation and VG model. The simulated working condition calibration module is used to perform soil seepage model inversion calibration based on in-situ short-time measured data.

10. The infiltration parameter determination based on stratified field measurements and numerical simulation as described in claim 6, characterized in that, The infiltration distribution simulation device includes: The infiltration simulation planning module is used to distribute and deploy soil seepage models in the geographic model of the area to be tested according to the soil structure, and to perform numerical simulations of standard double-ring infiltration experiments in batches. The infiltration data application module is used to output infiltration characteristic parameters and hydrological information based on numerical simulation results.

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