Earth surface and underground water interactive simulation method and system based on aquifer analysis

Abstract

The invention discloses an earth surface and underground water interactive simulation method and system based on aquifer analysis, and relates to the technical field of earth surface and underground water interactive simulation. An earth surface and underground water interactive simulation system based on aquifer analysis comprises a data acquisition module, a data processing module, an aquifer analysis module, a model simplification module, an interactive simulation module and a resource management module. According to the method, data sampling is performed on high-resolution data in the preprocessed earth surface data and underground data, so that key information in the data can be reserved, and the data volume needing to be processed can be remarkably reduced under the condition that the precision of the model is not remarkably influenced; therefore, the calculation complexity and the calculation amount are reduced, the calculation efficiency and the operation efficiency of the model are improved, the model can be helped to better process noise and abnormal values, the over-fitting risk of the model is reduced, and the robustness and the generalization ability of the model and the performance and the reliability of the model in practical application are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of surface and groundwater interaction simulation, and particularly to a method and system for simulating surface and groundwater interaction based on aquifer analysis. Background Art

[0002] Surface water refers to the water bodies existing on the earth's surface, including rivers, lakes, reservoirs, wetlands, etc. Groundwater refers to the water stored in soil pores and rock fractures below the earth's surface. Surface water can recharge groundwater through seepage, especially during the low water level periods of water bodies such as rivers and lakes. At the same time, groundwater can also recharge surface water in the form of spring flows to maintain the base flow of water bodies such as rivers. Surface water and groundwater jointly participate in the earth's water cycle process, and the exchange and flow between them constitute a complete hydrological system. And the simulation of surface and groundwater interaction is a scientific method for studying and predicting the interaction between surface water bodies and groundwater. This kind of simulation is of great significance in the fields of water resource management, pollution control, and ecological restoration.

[0003] Existing methods and systems for simulating surface and groundwater interaction are usually implemented based on models such as the SWAT-MODFLOW coupling model, GSFLOW model, HydroGeoSphere (HGS) model, and CATHY. However, in order to accurately simulate the interaction process between surface water and groundwater, these models require a large amount of input data, including topography, soil properties, meteorological data, and hydrogeological parameters, etc. This leads to a high computational complexity and poor computational efficiency of the models. And existing interaction simulation methods usually only estimate the permeability coefficient based on the type and lithology of the aquifer when analyzing the aquifer, without considering the influence of soil depth and environmental factors on the permeability coefficient of the aquifer, resulting in poor simulation effects of these models on the interaction between surface water and groundwater.

[0004] Based on the above situation, the present invention proposes a method and system for simulating surface and groundwater interaction based on aquifer analysis with high computational efficiency and good simulation effects. Summary of the Invention

[0005] In order to overcome the shortcomings that existing methods and systems for simulating surface and groundwater interaction require a large amount of input data to ensure simulation effects, resulting in high computational complexity and poor computational efficiency of the models, and only estimate the permeability coefficient based on the type and lithology of the aquifer, without considering the influence of soil depth and environmental factors on the permeability coefficient of the aquifer, resulting in poor simulation effects of these models on the interaction between surface water and groundwater, the present invention proposes a method and system for simulating surface and groundwater interaction based on aquifer analysis with high computational efficiency and good simulation effects.

[0006] A method for simulating the interaction between surface water and groundwater based on aquifer analysis, comprising the following steps:

[0007] Obtain the surface data and underground data of the area to be simulated, where the surface data includes meteorological data, topographic data, and land use data, and the underground data includes groundwater hydrological data and geological structure data;

[0008] Preprocess the surface data and underground data to obtain the preprocessed surface data and underground data, and sample the high-resolution data in the preprocessed surface data and underground data to obtain the simplified surface data and underground data;

[0009] Based on the simplified geological structure data, divide the location and type of the aquifer, and calculate the permeability coefficient of the corresponding aquifer based on the location and type of the aquifer;

[0010] Construct a conceptual model and a numerical model for the interaction between surface water and groundwater based on the HGS model, simplify the parameters of the numerical model based on data characteristics or theoretical assumptions, input the permeability coefficient of the aquifer and the simplified surface data and underground data into the simplified numerical model, and simulate the interaction between surface water and groundwater by running the simplified numerical model to obtain the simulation results;

[0011] Evaluate the water resources status of the simulation area based on the simulation results, and set a reasonable development and management plan for the water resources in the simulation area according to the evaluation results.

[0012] As a preferred aspect of the invention, the meteorological data includes precipitation, temperature, and humidity, the topographic data includes elevation, slope, and the water level and evaporation of surface water bodies, the land use data includes land use types and vegetation coverage rates, the groundwater hydrological data includes groundwater levels, flow velocities, and water storage rates, and the geological structure data includes formation types, distributions, and lithologies.

[0013] As a preferred aspect of the invention, the specific steps for sampling the high-resolution data are as follows:

[0014] According to the characteristics of the high-resolution data, select the variables for stratification;

[0015] Divide the data into different layers according to the stratification variables;

[0016] Determine the number of samples to be extracted for each layer according to the proportion of each layer in the overall;

[0017] Extract samples by random sampling within each layer;

[0018] Merge the sample data extracted from each layer to obtain the simplified data set.

[0019] As a preferred aspect of the invention, the specific formula for calculating the permeability coefficient of the corresponding aquifer is as follows: ; where is the permeability coefficient, is the reference permeability coefficient, is the burial depth of the aquifer, is the flow velocity of groundwater, is the reference flow velocity, is the soil temperature, is the reference soil temperature, and , and are the influence coefficients of the burial depth of the aquifer, the flow velocity of groundwater, and the soil temperature on the permeability coefficient, respectively.

[0020] As a preferred aspect of the invention, the specific method for realizing the interaction simulation of surface water and groundwater through the numerical model of surface water-groundwater interaction is as follows:

[0021] The flow of surface water is simulated by the two-dimensional diffusion wave equation, and its mathematical expression is: ; where is the water depth, is the time, is the acceleration of gravity, and is the terrain slope;

[0022] The flow of groundwater is simulated by the three-dimensional Richards equation, and its mathematical expression is: ; where is the volumetric water content, is the time, is the hydraulic conductivity and is a function of the water content, and is the hydraulic head; The flow equations of surface water and groundwater are coupled to realize the interaction simulation of surface water and groundwater.

[0023] As a preferred aspect of the invention, the specific steps for parameterizing and simplifying the numerical model are as follows:

[0024] According to the data characteristics or theoretical assumptions, select a suitable functional form to express the relationship between the input variable or one of the output variables and another output variable;

[0025] Based on historical data, use the method of minimizing the mean square error or the least squares method to determine or estimate the parameters of the function;

[0026] Apply the constructed function model to the numerical model and conduct the interaction simulation of surface water and groundwater.

[0027] As a preferred aspect of the invention, the specific steps for verifying and optimizing the parameters of the simplified numerical model are as follows:

[0028] Obtain the historical surface data and historical underground data of the area to be simulated, preprocess and sample the obtained data, and input the simplified data and the permeability coefficient of the aquifer into the simplified numerical model to obtain the simulation results;

[0029] Compare the simulation results with the measured data, evaluate the performance of the simplified numerical model, and use the genetic algorithm to optimize the model parameters;

[0030] After parameter optimization, re-run the simplified numerical model and conduct comparative analysis until the coincidence degree between the model output and the measured data reaches the preset standard.

[0031] A surface and groundwater interaction simulation system based on aquifer analysis includes a data acquisition module, a data processing module, an aquifer analysis module, a model simplification module, an interaction simulation module, and a resource management module.

[0032] Data acquisition module: used to acquire the surface data and underground data of the area to be simulated;

[0033] Data processing module: used to preprocess the surface data and underground data, and sample the high-resolution data in the preprocessed surface data and underground data;

[0034] Aquifer analysis module: used to divide the location and type of the aquifer according to the simplified geological structure data, and calculate the permeability coefficient of the corresponding aquifer based on the location and type of the aquifer;

[0035] Model simplification module: used to construct a conceptual model and a numerical model of surface water - groundwater interaction based on the HGS model, and parametrically simplify the numerical model based on data characteristics or theoretical assumptions;

[0036] Interaction simulation module: used to input the permeability coefficient of the aquifer and the simplified surface data and underground data into the simplified numerical model, and conduct surface water - groundwater interaction simulation by running the simplified numerical model to obtain the simulation results;

[0037] Resource management module: used to evaluate the water resource status of the simulation area based on the simulation results, and set reasonable development and management plans for the water resources in the simulation area according to the evaluation results.

[0038] The present invention has the following advantages:

[0039] 1. By performing data sampling on the high-resolution data in the preprocessed surface data and subsurface data, the present invention can not only significantly reduce the amount of data to be processed while retaining the key information in the data to ensure that the accuracy of the model is not significantly affected, thereby reducing the computational complexity and amount of calculation and improving the computational efficiency and running efficiency of the model, but also help the model better handle noise and outliers and reduce the risk of overfitting of the model, thereby improving the robustness and generalization ability of the model as well as the performance and reliability in practical applications, and enhancing the computational efficiency and simulation effect of this surface and groundwater interaction simulation method and system.

[0040] 2. By parameterizing and simplifying the numerical model according to data characteristics or theoretical assumptions, the present invention can not only effectively simplify the structure of the numerical model and the input data, thereby reducing the number of parameters to be input, reducing the computational complexity and cost, improving the running efficiency and interpretability of the model, and improving the performance and reliability of the model, but also quickly adjust the design of the model by simply changing the parameter values to adapt to new design requirements, so that there is no need to build the model from scratch, enabling the model to flexibly handle different simulation scenarios, and enhancing the computational efficiency and simulation effect of this surface and groundwater interaction simulation method and system.

[0041] 3. By calculating the permeability coefficient of the corresponding aquifer based on the simplified groundwater hydrological data and the location and type of the aquifer, the present invention can comprehensively consider the influence of the burial depth of the aquifer, the flow velocity of groundwater, and the soil temperature on the permeability coefficient and obtain an accurate permeability coefficient, thereby being able to more accurately simulate the flow path, velocity, and water volume of groundwater, improve the simulation effect and accuracy of the model for groundwater flow, and the accurate permeability coefficient can also reduce the error accumulation in model calculation, thereby effectively improving the overall simulation accuracy of the model, and enhancing the simulation effect of this surface and groundwater interaction simulation method and system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic structural diagram of a surface and groundwater interaction simulation system based on aquifer analysis adopted in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] In order to enable those skilled in the art of the present technology to better understand the technical solutions in the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention.

[0044] Embodiment 1, a surface and groundwater interaction simulation method based on aquifer analysis, includes the following steps:

[0045] Obtain the surface data and subsurface data of the area to be simulated, where the surface data includes meteorological data, topographic data, and land use data, and the subsurface data includes groundwater hydrological data and geological structure data;

[0046] Preprocess the surface data and subsurface data to obtain the preprocessed surface data and subsurface data. Sample the high-resolution data in the preprocessed surface data and subsurface data to obtain the simplified surface data and subsurface data;

[0047] Based on the simplified geological structure data, divide the location and type of the aquifer. Based on the simplified groundwater hydrological data, as well as the location and type of the aquifer, calculate the hydraulic conductivity of the corresponding aquifer;

[0048] Based on the HGS model, construct a conceptual model and a numerical model for surface water-groundwater interaction. Simplify the parameters of the numerical model based on data characteristics or theoretical assumptions. Input the hydraulic conductivity of the aquifer, as well as the simplified surface data and subsurface data, into the simplified numerical model. Based on the input data, determine the various parameters, boundary conditions, and initial conditions of the simplified numerical model. Perform surface water-groundwater interaction simulation by running the simplified numerical model and obtain the simulation results. The simulation results include the change in the groundwater level and the exchange flux between surface water and groundwater;

[0049] Evaluate the water resources status of the simulation area based on the simulation results, and set a reasonable development and management plan for the water resources in the simulation area according to the evaluation results.

[0050] The meteorological data includes precipitation, temperature, humidity, and wind speed, which are used to simulate hydrological processes such as evaporation and runoff. The topographic data includes elevation, slope, and the water level, flow rate, and evaporation of surface water bodies, which are used to determine the surface water flow direction and confluence path. The land use data includes land use type and vegetation coverage rate. The groundwater hydrological data includes groundwater level, flow velocity, water storage rate, and specific yield, which are used to determine the initial groundwater level and boundary conditions and construct a groundwater model. The geological structure data includes formation type, porosity, distribution, thickness, and lithology.

[0051] The specific steps for preprocessing the surface data and subsurface data are as follows:

[0052] Missing value processing: Process the null values or missing values in the dataset. Use interpolation methods such as linear interpolation or polynomial interpolation to fill the missing values, or directly use the mean or median of the dataset to fill the missing values to ensure the integrity of the data and the stability of the model;

[0053] Outlier handling, identifying outliers in the dataset that do not conform to the expected pattern through the Z-Score method or the IQR method, and avoiding the negative impact of these outliers on the model simulation by deleting the outliers and replacing them with the mean or median of the dataset or using interpolation methods to repair the outliers;

[0054] Data standardization, standardizing data with different dimensions through min-max standardization. The calculation formula for min-max standardization is:

[0055] ; where represents the original data value, represents the minimum value in the dataset, represents the maximum value in the dataset, represents the standardized data value.

[0056] The specific steps for data sampling of the high-resolution data in the preprocessed surface data and subsurface data are as follows:

[0057] Determine the stratification variable. According to the characteristics of the high-resolution data, select the variable for stratification. For example, the data can be stratified according to geological structure, hydrogeological characteristics, and pollutant concentration, etc.;

[0058] Divide the layers. Divide the data into different layers according to the stratification variable. For example, divide the areas with different permeability coefficients into different layers, or divide the data into different layers according to soil types;

[0059] Determine the sample size for each layer. Determine the number of samples to be drawn for each layer according to the proportion of each layer in the overall population;

[0060] Select samples. Use uniform sampling, random sampling, or importance-based sampling methods to draw samples within each layer;

[0061] Merge samples. Merge the sample data drawn from each layer to obtain the final sample dataset, that is, the simplified dataset.

[0062] By performing data sampling on the high-resolution data in the preprocessed surface data and subsurface data, the above steps can not only retain the key information in the data, significantly reduce the amount of data to be processed while ensuring that the accuracy of the model is not significantly affected, thereby reducing the computational complexity and amount of calculation and improving the computational efficiency and running efficiency of the model, but also help the model better handle noise and outliers and reduce the risk of overfitting of the model, thus improving the robustness and generalization ability of the model as well as the performance and reliability in practical applications, and enhancing the computational efficiency and simulation effect of this surface and groundwater interaction simulation method and system.

[0063] For example, assume we have a set of high-resolution soil permeability data that covers a large watershed with a very high spatial resolution. To simplify the data and improve the model running efficiency, the following steps can be taken for stratified sampling:

[0064] Determine the stratification basis. According to the distribution of soil permeability, divide it into three levels: high permeability, medium permeability, and low permeability;

[0065] Divide the levels. Divide the soil permeability data into three levels, with each level corresponding to a different permeability range;

[0066] Sampling strategy. In each level, adopt a uniform sampling strategy and extract a sample point every certain distance (such as 100 meters);

[0067] Data simplification. Use an interpolation method (such as bilinear interpolation) to process the sampled data and generate simplified soil permeability data;

[0068] Verification and adjustment. Compare the simplified data with the original data to ensure that the simplified data can accurately reflect the characteristics of the original data. If it is found that the simplified data in some areas has a large difference from the original data, the sampling density can be appropriately increased or the stratification strategy can be adjusted.

[0069] Experiment 1:

[0070] Among them, the measured groundwater level is the water level data of the groundwater for seven days obtained through actual measurement; the simulated groundwater level data of experimental group 1 is obtained through simulation based on the input data with a resolution of 30 meters; the simulated groundwater level data of experimental group 2 is obtained through simulation based on the input data with a resolution of 100 meters. It should be noted that the input data with a resolution of 100 meters is obtained by sampling the input data with a resolution of 30 meters; RMSE and R² are the evaluation indexes for the fitting degree of the simulated groundwater level data of experimental group 1 and experimental group 2 with the measured groundwater level data.

[0071] Result analysis: In experimental group 1 (30-meter resolution), due to more noise and errors in the data, although the resolution is high, the fitting degree between the simulation result and the measured data has decreased, that is, the RMSE is high and the R² is low; in experimental group 2 (100-meter resolution), although the data resolution is low, the data quality is good, and the fitting degree between the simulation result and the measured data is high, that is, the RMSE is low and the R² is high.

[0072] Conclusion: The impact of data quality on simulation results is significant. Even with a high resolution, if there is a lot of noise and error in the data, it may lead to a decrease in the fitting degree of the simulation results. In practical applications, it is necessary to balance the data resolution and data quality to obtain the best simulation effect.

[0073] The specific formula for calculating the permeability coefficient of the corresponding aquifer based on the simplified groundwater hydrological data, the location and type of the aquifer is as follows: ; where is the permeability coefficient, is the reference permeability coefficient, is the buried depth of the aquifer, is the flow velocity of groundwater, is the reference flow velocity, is the soil temperature, is the reference soil temperature, and 、 and are the influence coefficients of the buried depth of the aquifer, the flow velocity of groundwater, and the soil temperature on the permeability coefficient respectively, and the values of each influence coefficient can be obtained by laboratory measurement method or empirical formula method.

[0074] It should be noted that the reference flow velocity and the reference soil temperature are obtained based on the normal data of the aquifer, while the reference permeability coefficient is obtained by estimation based on the type and lithology of the aquifer. The types of the aquifer include unconsolidated rock pore aquifer, general clastic rock fissure pore aquifer, pervious (water-free) layer or water area, carbonate rock karst aquifer, red bed fissure pore aquifer, and bedrock fissure aquifer. Among them, the bedrock fissure aquifer can be further divided into flexible rock fissure aquifer, mudstone fissure aquifer, shale fissure aquifer, granite fissure aquifer, and siliceous rock fissure aquifer according to lithology.

[0075] The above steps can calculate the permeability coefficient of the corresponding aquifer according to the simplified groundwater hydrological data, the location and type of the aquifer, comprehensively consider the influence of the buried depth of the aquifer, the flow velocity of groundwater, and the soil temperature on the permeability coefficient, and obtain an accurate permeability coefficient, so as to more accurately simulate the flow path, velocity and water volume of groundwater, improve the simulation effect and accuracy of the model for groundwater flow, and the accurate permeability coefficient can also reduce the error accumulation in the model calculation, thus effectively improving the overall simulation accuracy of the model and enhancing the simulation effect of this surface-groundwater interaction simulation method and system.

[0076] The specific way to realize the interaction simulation of surface water and groundwater through the numerical model of surface water-groundwater interaction is as follows:

[0077] The flow of surface water is simulated by the two-dimensional diffusion wave equation, which is the diffusion wave approximation of the shallow water equation and is applicable to simulating processes such as surface runoff. Its mathematical expression is: ; where is the water depth, is the time, is the acceleration due to gravity, and is the topographic slope;

[0078] The flow of groundwater is simulated by the three-dimensional Richards equation, which describes the water flow movement in saturated-unsaturated porous media. Its mathematical expression is: ; where is the volumetric water content, is the time, is the hydraulic conductivity and is a function of the water content, and is the hydraulic head;

[0079] The flow equations of surface water and groundwater are coupled to achieve the interactive simulation of surface and groundwater.

[0080] It should be noted that the above-mentioned tight coupling of surface and groundwater is achieved by the numerical model of surface water-groundwater interaction simultaneously solving the two-dimensional diffusion wave equation of surface water and the three-dimensional Richards equation of groundwater through a global implicit method. And the numerical model of surface water-groundwater interaction is not just a simple coupling of the flow equations of surface water and groundwater, but a complex system that comprehensively considers various hydrological processes and physical mechanisms. The integration of other hydrological processes includes solute transport. The numerical model can simulate the transport process of solutes in surface water and groundwater, including diffusion, convection, and molecular diffusion, etc.; heat transfer. The numerical model can also simulate the heat transfer process on the surface and underground, which is crucial for understanding the heat exchange and temperature change in the hydrological system; ecological processes. The numerical model can simulate the flow process of matter and energy in the ecosystem, including soil moisture and plant growth, etc.; geochemical processes. The numerical model can simulate the chemical reaction and matter transport process in groundwater and soil, including the migration and transformation of inorganic substances.

[0081] The specific steps for parameterizing and simplifying the numerical model based on data characteristics or theoretical assumptions are as follows:

[0082] Assume the function form: According to data characteristics or theoretical assumptions, select a suitable function form to express the relationship between input variables and output variables or the relationship between one output variable and another output variable;

[0083] Estimation parameters: Determine or estimate the parameters of a function through historical data or experimental data using statistical methods or optimization algorithms to make it fit the data as closely as possible. For statistical methods, the least mean square error method is used to determine the parameters of the function, while for optimization algorithms, the least squares method is used to estimate the parameters of the function;

[0084] Apply the model: Apply the constructed function model to the numerical model and conduct simulations of the interaction between surface water and groundwater.

[0085] The above steps can effectively simplify the structure and input data of the numerical model by parameterizing and simplifying the numerical model according to data characteristics or theoretical assumptions, thereby reducing the number of parameters to be input, lowering the computational complexity and cost, improving the running efficiency and interpretability of the model, and enhancing the performance and reliability of the model. It can also quickly adjust the design of the model to adapt to new design requirements by simply changing the parameter values, eliminating the need to build the model from scratch, enabling the model to flexibly handle different simulation scenarios, and improving the computational efficiency and simulation effect of this surface and groundwater interaction simulation method and system.

[0086] For example, suppose we want to simulate the exchange flux between surface water and groundwater. Usually, complex hydrogeological data and boundary conditions need to be input. To simplify this process, a parameterized modeling method can be used, which specifically includes the following steps:

[0087] Assume the function form, select a linear function based on the water level difference to describe the exchange flux between surface water and groundwater, and its function form is as follows: ; where represents the exchange flux, represents the exchange coefficient, and and represent the water levels of surface water and groundwater respectively;

[0088] Estimate the parameters, estimate the exchange coefficient through historical data or experimental data using an optimization algorithm (such as the least squares method), or determine the exchange coefficient using the least mean square error method

[0089] to make it fit the exchange flux data between surface water and groundwater;

[0090] Verify the model, evaluate the goodness of fit of the model through statistical tests and compare it with the measured data to ensure the predictive ability of the model;

[0091] Experiment 2:

[0092] Among them, the measured exchange flux is the data of the seven-day groundwater and surface water exchange flux obtained through actual measurement; the exchange flux of experimental group 1 (model) is the data of the seven-day exchange flux obtained through model simulation; the exchange flux of experimental group 2 (function) is the seven-day exchange flux data calculated through the formula where is the exchange coefficient determined based on historical data and using the method of minimizing the mean square error; RMSE and R² are the evaluation indexes of the fitting degree between the exchange fluxes of experimental group 1 and experimental group 2 and the measured data.

[0093] Conclusion: The fitting degree of experimental group 2 (function) (RMSE = 0.08 m³ / s, R² = 0.97) is better than that of experimental group 1 (model) (RMSE = 0.12 m³ / s, R² = 0.95), indicating that calculating the exchange flux by combining the formula can improve the fitting degree and calculation efficiency of the model.

[0094] The specific steps for verifying and optimizing the parameters of the simplified numerical model are as follows:

[0095] Obtain the historical surface data and historical underground data of the area to be simulated, preprocess and sample the obtained data, and input the simplified data and the permeability coefficient of the aquifer into the simplified numerical model to obtain the simulation results;

[0096] Compare the simulation results with the measured data, evaluate the accuracy and reliability of the simplified numerical model, and optimize the model parameters by using genetic algorithm, dynamic dimension search or particle swarm optimization algorithm;

[0097] After parameter optimization, re-run the simplified numerical model and conduct comparative analysis until the degree of coincidence between the model output and the measured data reaches the preset standard.

[0098] Example 2, a surface and groundwater interaction simulation system based on aquifer analysis, as Figure 1 shown, includes a data acquisition module, a data processing module, an aquifer analysis module, a model simplification module, an interaction simulation module and a resource management module,

[0099] Data acquisition module: used to acquire the surface data and underground data of the area to be simulated;

[0100] Data processing module: used to preprocess the surface data and underground data to obtain the preprocessed surface data and underground data, and sample the high-resolution data in the preprocessed surface data and underground data to obtain the simplified surface data and underground data;

[0101] Aquifer analysis module: used to divide the location and type of aquifers according to the simplified geological structure data, and calculate the permeability coefficient of the corresponding aquifers based on the groundwater hydrological data, as well as the location and type of the aquifers;

[0102] Model simplification module: used to construct a conceptual model and a numerical model of surface water-groundwater interaction based on the HGS model, and perform parametric simplification on the numerical model based on data characteristics or theoretical assumptions;

[0103] Interaction simulation module: used to input the permeability coefficient of the aquifer, as well as the simplified surface data and underground data, into the simplified numerical model, establish the various parameters, boundary conditions and initial conditions of the simplified numerical model based on the input data, and perform surface water-groundwater interaction simulation through running the simplified numerical model to obtain the simulation results;

[0104] Resource management module: used to evaluate the water resource status of the simulation area based on the simulation results, and set reasonable development and management plans for the water resources in the simulation area according to the evaluation results.

[0105] It should be understood that those of ordinary skill in the art can make improvements or transformations according to the above description, and all such improvements and transformations shall fall within the protection scope of the appended claims of the present invention. The parts not described in detail in this specification belong to the prior art well-known to those of ordinary skill in the art.

Claims

1. A method for simulating the interaction between surface water and groundwater based on aquifer analysis, characterized in that, It includes the following steps: Obtain the surface data and subsurface data of the area to be simulated, where the surface data includes meteorological data, terrain data, and land use data, and the subsurface data includes groundwater hydrological data and geological structure data; Preprocess the surface data and subsurface data to obtain the preprocessed surface data and subsurface data, and sample the high-resolution data in the preprocessed surface data and subsurface data to obtain the simplified surface data and subsurface data; Based on the simplified geological structure data, divide the location and type of the aquifer, and calculate the hydraulic conductivity of the corresponding aquifer based on the location and type of the aquifer; Construct a conceptual model and a numerical model for surface water-groundwater interaction based on the HGS model, simplify the parameters of the numerical model based on data characteristics or theoretical assumptions, input the hydraulic conductivity of the aquifer and the simplified surface data and subsurface data into the simplified numerical model, and perform surface water-groundwater interaction simulation through running the simplified numerical model to obtain the simulation results; Evaluate the water resources status of the simulated area based on the simulation results, and set a reasonable development and management plan for the water resources of the simulated area according to the evaluation results.

2. The surface and groundwater interaction simulation method based on aquifer analysis according to claim 1, wherein The meteorological data includes precipitation, temperature, and humidity, the terrain data includes elevation, slope, and the water level and evaporation of surface water bodies, the land use data includes land use types and vegetation coverage rates, the groundwater hydrological data includes groundwater level, flow velocity, and water storage rate, and the geological structure data includes formation types, distributions, and lithologies.

3. A method for simulating the interaction between surface water and groundwater based on aquifer analysis according to claim 1, characterized in that, The specific steps for sampling the high-resolution data are as follows: According to the characteristics of the high-resolution data, select the variables for stratification; Divide the data into different layers according to the stratification variables; Determine the number of samples to be extracted for each layer according to the proportion of each layer in the overall; Extract samples through random sampling within each layer; Combine the sample data extracted from each layer to obtain the simplified data set.

4. A method for simulating the interaction between surface water and groundwater based on aquifer analysis according to claim 3, characterized in that, The specific formula for calculating the hydraulic conductivity of the corresponding aquifer is: ; where is the permeability coefficient, is the reference permeability coefficient, is the buried depth of the aquifer, is the flow velocity of groundwater, is the reference flow velocity, is the soil temperature, is the reference soil temperature, while , and are the influence coefficients of the buried depth of the aquifer, the flow velocity of groundwater, and the soil temperature on the permeability coefficient, respectively.

5. A method for simulating the interaction between surface water and groundwater based on aquifer analysis according to claim 1, characterized in that, The specific method for realizing surface and groundwater interaction simulation through the numerical model of surface water-groundwater interaction is: Simulate the flow of surface water through the two-dimensional diffusion wave equation, and its mathematical expression is: ; wherein is the water depth, is the time, is the acceleration due to gravity, and is the terrain slope; Simulate the flow of groundwater through the three-dimensional Richards equation, and its mathematical expression is: ; where is the volumetric water content, is the time, is the hydraulic conductivity and is a function of the water content, and is the hydraulic head; the flow equations of surface water and groundwater are coupled to achieve the interactive simulation of surface and groundwater.

6. A method for simulating the interaction between surface water and groundwater based on aquifer analysis according to claim 5, characterized in that, The specific steps for parameterizing and simplifying the numerical model are: According to data characteristics or theoretical assumptions, select a suitable functional form to express the relationship between the input variable or one of the output variables and another output variable; Based on historical data, use the method of minimizing the mean square error or the least squares method to determine or estimate the parameters of the function; Apply the constructed function model to the numerical model and perform surface water and groundwater interaction simulation.

7. A method for simulating the interaction between surface water and groundwater based on aquifer analysis according to claim 6, characterized in that, The specific steps for verifying and optimizing the parameters of the simplified numerical model are: Obtain the historical surface data and historical subsurface data of the area to be simulated, preprocess and sample the obtained data, and input the simplified data and the hydraulic conductivity of the aquifer into the simplified numerical model to obtain the simulation results; Compare the simulation results with the measured data, evaluate the performance of the simplified numerical model, and optimize the model parameters using the genetic algorithm; After parameter optimization, re-run the simplified numerical model and conduct a comparative analysis until the degree of agreement between the model output and the measured data reaches the preset standard.

8. A surface and groundwater interaction simulation system based on aquifer analysis, which is applied to a surface and groundwater interaction simulation method according to any one of claims 1-7, characterized in that, It includes a data acquisition module, a data processing module, an aquifer analysis module, a model simplification module, an interactive simulation module, and a resource management module. Data acquisition module: used to acquire surface data and underground data of the area to be simulated; Data processing module: used to preprocess the surface data and underground data, and sample the high-resolution data in the preprocessed surface data and underground data; Aquifer analysis module: used to divide the location and type of the aquifer according to the simplified geological structure data, and calculate the permeability coefficient of the corresponding aquifer based on the location and type of the aquifer; Model simplification module: used to construct a conceptual model and a numerical model of surface water-groundwater interaction based on the HGS model, and parametrically simplify the numerical model based on data characteristics or theoretical assumptions; Interactive simulation module: used to input the permeability coefficient of the aquifer and the simplified surface data and underground data into the simplified numerical model, and conduct surface water-groundwater interaction simulation through running the simplified numerical model to obtain the simulation results; Resource management module: used to evaluate the water resource status of the simulation area based on the simulation results, and set reasonable development and management plans for the water resources in the simulation area according to the evaluation results.

Images