Natural regulation type salinized soil desalination simulation and multi-target optimization configuration method

Abstract

The invention relates to the field of specific calculation models, and discloses a natural regulation type salinized soil desalination simulation and multi-objective optimization configuration method, which comprises the following steps of: 1, data acquisition and earlier stage processing; 2, constructing a water and salt migration model; step 3, simulation analysis and scheme optimization; 4, carrying out substitution model training and multi-objective optimization; the final scheme is directly used for guiding engineering implementation, and specifically comprises the steps of determining the terrain adjustment amplitude, the position and depth of a drainage ditch, the micro-topographic relief scale, the earth filling and digging volume and shallow guide and drainage path configuration. The method has the beneficial effects that the natural drainage capacity of regional underground water can be remarkably improved, the effect that evaporation drives salt to move upwards is weakened, the rainfall infiltration capacity is improved, and the natural leaching effect is enhanced. The method is suitable for areas such as mud flats, salt pans and natural reserves where artificial engineering measures are not suitable to be taken, and has the advantages of low cost, high stability, ecological friendliness and the like.

Description

Technical Field

[0001] This invention relates to a desalination simulation and multi-objective optimization configuration method based on a specific computational model, and particularly to a natural regulation type saline soil desalination simulation and multi-objective optimization configuration method. Background Technology

[0002] Currently, in flat areas such as coastal areas, lakeshores, or aeolian plains, groundwater evaporation is significant, while natural drainage channels are insufficient, leading to repeated salt accumulation in the shallow soil layers. Unlike areas requiring artificial regulation through engineering measures, these natural salt control scenarios typically lack the conditions for implementing underground drainage systems, large-scale earthwork construction, or continuous artificial leaching. Therefore, water-salt migration processes driven by natural potential energy play a dominant role in regional water-salt regulation.

[0003] Existing natural methods for salt control mostly rely on vegetation restoration, surface cover, and disturbance reduction. However, these methods have a weak impact on groundwater dynamics and salt migration pathways, and lack quantitative design tools. For example, slight changes in topographic slope have a significant impact on shallow groundwater level fields, surface runoff paths, infiltration rates, and evaporation center distribution, but current engineering practices have not yet established methods for predicting water and salt migration and optimizing schemes based on micro-topographic parameters.

[0004] While numerical models in recent years can simulate local water and salt transport, their computational demands are high, making them unsuitable for regional-scale topographical scheme experiments. Furthermore, since the natural salt drainage process is driven by multiple factors such as rainfall, infiltration, evaporation, wind speed, and permeability differences, there is currently no systematic natural salt drainage design framework based on topographic-flow field reshaping, and even less of a technical system for optimizing high-dimensional topographic parameter combinations.

[0005] Therefore, a simulation system is needed that can couple topography, groundwater flow field and water-salt migration process. By comparing multiple sets of micro-topography and flow field intervention schemes, the system can quantitatively predict salt discharge capacity, shallow water salt response and long-term desalination trend. Furthermore, it can utilize alternative models and multi-objective optimization techniques to achieve efficient design of regional natural salt control. Summary of the Invention

[0006] The main purpose of this invention is to address the current lack of a systematic natural desalination design framework based on topography-flow field reshaping, and the lack of a technical system for optimizing high-dimensional topographic parameter combinations. This invention provides a natural regulation-type saline soil desalination simulation and multi-objective optimization configuration method.

[0007] The natural regulation-type saline soil desalination simulation and multi-objective optimization configuration method provided by this invention includes the following steps:

[0008] Step 1: Data Acquisition and Pre-processing;

[0009] Step 2: Construction of a water-salt transport model;

[0010] Step 3: Simulation analysis and scheme optimization;

[0011] Step 4: Alternative model training and multi-objective optimization;

[0012] Step 5: Project Implementation Guidance: The final plan is directly used to guide the project implementation, specifically including determining the range of terrain adjustment, the location and depth of drainage ditches, the scale of micro-topographic undulations, the volume of earthwork for filling and excavation, and the configuration of shallow drainage paths.

[0013] The specific steps in the first step are as follows:

[0014] Step 1: Obtain a high-precision DEM of the study area and construct a regional micro-topography model by combining it with UAV lidar or high-resolution imagery;

[0015] Step 2: Extract the structural features of surface runoff paths, waterlogged depressions, and potential drainage channels through topographic and runoff analysis;

[0016] Step 3: Construct shallow groundwater level distribution using groundwater monitoring well data, and establish initial salinity field and hydraulic parameter library by combining soil salinity and moisture content monitoring data, so as to provide basic data support for subsequent modeling.

[0017] The specific steps for the second step are as follows:

[0018] Step 1: Based on the data from Step 1 and Step 3, construct a water and salt transport model that considers topographic slope, groundwater dynamics and surface water cycle. The model is built using HYDRUS-2D software. The initial soil salinity is set to 2.1% and the slope is 10%. Simulate the salt discharge process at different drainage channel spacings of 8m, 10m, 12m, 15m and 20m.

[0019] Step 2: Soil media are generalized into two categories: native soil and rotary tillage soil; the bottom of the model is set to a given water head and concentration boundary, the water level is level with the bottom of the drainage ditch, and the solution concentration corresponds to the saturated extract concentration of 2.1% soil salt content.

[0020] Step 3: The top of the model is set as the atmospheric boundary, and the meteorological data are the monthly average values ​​of the study area over the years; the irrigation canal is set as the given head boundary, and the drainage canal is set as the seepage surface boundary;

[0021] Step 4: The simulation period is 2 years. The model parameters are calibrated using monitoring data over several years to ensure that the simulation results are consistent with the measured water salt distribution, water level changes, and evaporation salt accumulation patterns.

[0022] In the second step, step 1, the Hydrus-2D quantitatively simulates water migration in a variablely saturated porous medium by solving the Richards equation and calculates the relative permeability coefficient using the Van Genuchten-Mualem formula. The combined mathematical model for simulating groundwater flow is shown below:

[0023] ;

[0024] ;

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] Where: θ(h) is the moisture content, in m³. 3 ·m -3 h is the pressure head, in meters (m); x and z are the horizontal and vertical coordinates, in meters (m); θ r Residual moisture content, in meters (m). 3 ·m -3 ; α,n,m,l are empirical fitting coefficients; S e θ represents relative saturation; θ0 represents initial water content in cubic meters (m³). 3 ·m -3 ; Given the head boundary; t is time, in days; K(h) is the permeability coefficient, in m / d; S(h) is the source and sink terms; θ s This is the saturated water content, in meters (m). 3 ·m -3 ;K s h0 is the saturated permeability coefficient, in m / d; h0 is the initial head, in m; S is the simulation range; h1 is the given head boundary. The head of water is measured in meters (m).

[0030] Hydrus-2D quantitatively simulates salt migration by solving the advection–dispersion equation, as shown in the formula below. Since the main ion in the soil and groundwater of the study area is Cl... - and Na + Since it is chemically inert, interionic reactions are not considered.

[0031] ;

[0032] ;

[0033] ;

[0034] Where: c is the solute concentration in the soil solution, in mol / m³. 3 ; Let i be the spatial coordinates, i = 1, 2; Initial concentration, in mol / m³ 3 ; Given a concentration boundary; The dispersion coefficient is expressed in m. 2 / d; The water flow rate in the i-direction is expressed in m / d. For a given concentration boundary The concentration, in mol / m³ 3 .

[0035] The specific steps for the third step are as follows:

[0036] Step 1: Based on model calibration, generate different terrain reshaping schemes, including adjusting slope and re-laying shallow ditches, and evaluate the impact of each scheme on shallow water and salt dynamics, salt flux and natural salt discharge efficiency through multi-year scale simulation.

[0037] Step 2: Taking into account both economic efficiency and salt removal efficiency, the channel spacing should not exceed 12m.

[0038] The specific steps for the fourth step are as follows:

[0039] Step 1: Use the simulation results to train the alternative model, so that the alternative model can quickly predict the desalination effect and the risk of salt return with terrain parameters as input;

[0040] Step 2: Based on the alternative model, establish the following key objective functions:

[0041] ① Maximize the efficiency of natural salt removal;

[0042] ② Minimize the accumulation of shallow salt;

[0043] ③ Groundwater level regulation is the most reasonable approach, avoiding excessive drainage or water accumulation;

[0044] ④ Minimize terrain modification costs;

[0045] Step 3: Introduce actual engineering constraints, such as ensuring that the slope does not exceed the local stability threshold, the spacing between ditches meets the construction specifications, and the volume of cut and fill is controlled within a feasible range;

[0046] Step 4: Use multi-objective optimization algorithms, including NSGA-II and MOEA / D, to solve the model and perform Pareto front search in the objective space to obtain a set of non-dominated solutions, i.e., the set of optimization schemes;

[0047] Step 5: Combining on-site conditions and management requirements, select the optimal micro-topography-flow field co-reshaping scheme from the Pareto solution set to provide a quantitative and controllable design basis for subsequent engineering implementation.

[0048] The beneficial effects of this invention are:

[0049] The natural-controlled saline soil desalination simulation and multi-objective optimization configuration method provided by this invention achieves integrated design of topographic control and groundwater dynamic control in natural salt control scenarios, forming a natural-driven desalination scheme that can be systematically extrapolated, quantitatively compared, and applied in engineering. By reconstructing the topographically driven shallow flow field, this invention can significantly improve the natural drainage capacity of regional groundwater, weaken the evaporation-driven salt uplift effect, and enhance rainfall infiltration capacity, thereby strengthening the natural leaching effect. Compared with the traditional long-term process relying on natural succession, this invention can shorten the desalination cycle and improve the treatment effect through technical design.

[0050] By employing an alternative model, this invention avoids extensive repetitive simulations, significantly improving optimization efficiency and enabling the evaluation of large-scale micro-topographical combination schemes. It provides a quantitative optimization scheme balancing natural salt drainage efficiency, shallow salinity stability, and remediation costs, allowing natural salt control methods to achieve an engineering-ready, implementable, and maintainable expression. This method is particularly suitable for areas unsuitable for artificial engineering measures, such as tidal flats, salt fields, and nature reserves, offering advantages such as low cost, high stability, and eco-friendliness. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of parameter simulation for the unused salt field scheme described in this invention.

[0052] Figure 2 This is a schematic diagram of the model simulation described in this invention. Detailed Implementation

[0053] Please see Figure 1 and Figure 2 As shown:

[0054] The natural regulation-type saline soil desalination simulation and multi-objective optimization configuration method provided by this invention includes the following steps:

[0055] The first step, data acquisition and preprocessing, is as follows:

[0056] First, a high-precision DEM of the study area was acquired, and a regional micro-topographic model was constructed by combining UAV lidar or high-resolution imagery. Structural features such as surface runoff paths, waterlogged depressions, and potential drainage channels were extracted through topographic and runoff analysis. Simultaneously, shallow groundwater level distribution was constructed using groundwater monitoring well data, and an initial salinity field and hydraulic parameter database were established by combining soil salinity and moisture content monitoring data, providing fundamental data support for subsequent modeling.

[0057] The second step, constructing a water-salt transport model, is as follows:

[0058] Based on the aforementioned data, a water-salt transport model was constructed considering topographic slope, groundwater dynamics, and surface water cycle. The model was built using HYDRUS-2D software, with an initial soil salinity of 2.1% and a slope of 10%, simulating the salt drainage process at different drainage channel spacings (8m, 10m, 12m, 15m, and 20m). The soil medium was generalized into two types: native soil and rotary tillage soil. The bottom of the model was set as a given water head and concentration boundary, with the water level flush with the bottom of the drainage channel, and the solution concentration corresponding to the saturated extract concentration of 2.1% soil salinity. The top of the model was set as the atmospheric boundary, with meteorological data using the monthly average values ​​of the study area over the years. Irrigation channels were set as a given water head boundary, and drainage channels as permeability surface boundaries. The simulation period was two years, and the model parameters were calibrated using years of monitoring data to ensure that the simulation results were consistent with measured water-salt distribution, water level changes, and evaporative salt accumulation patterns.

[0059] The aforementioned Hydrus-2D quantitatively simulates water migration in a variablely saturated porous medium by solving the Richards equation and calculates the relative permeability coefficient using the Van Genuchten-Mualem formula. The combined formula for the groundwater flow simulation mathematical model is shown below:

[0060] ;

[0061] ;

[0062] ;

[0063] ;

[0064] ;

[0065] ;

[0066] Where: θ(h) is the moisture content, in m³. 3 ·m -3 h is the pressure head, in meters (m); x and z are the horizontal and vertical coordinates, in meters (m); θ r Residual moisture content, in meters (m).3 ·m -3 ; α,n,m,l are empirical fitting coefficients; S e θ represents relative saturation; θ0 represents initial water content in cubic meters (m³). 3 ·m -3 ; Given the head boundary; t is time, in days; K(h) is the permeability coefficient, in m / d; S(h) is the source and sink terms; θ s This is the saturated water content, in meters (m). 3 ·m -3 ;K s h0 is the saturated permeability coefficient, in m / d; h0 is the initial head, in m; S is the simulation range; h1 is the given head boundary. The head of water is measured in meters (m).

[0067] Hydrus-2D quantitatively simulates salt migration by solving the advection–dispersion equation, as shown in the formula below. Since the main ion in the soil and groundwater of the study area is Cl... - and Na + Since it is chemically inert, interionic reactions are not considered.

[0068] ;

[0069] ;

[0070] ;

[0071] Where: c is the solute concentration in the soil solution, in mol / m³. 3 ; Let i be the spatial coordinates, i = 1, 2; Initial concentration, in mol / m³ 3 ; Given a concentration boundary; The dispersion coefficient is expressed in m. 2 / d; The water flow rate in the i-direction is expressed in m / d. For a given concentration boundary The concentration, in mol / m³ 3 .

[0072] The simulation parameters were initially given with reference to the empirical values ​​of the region (the permeability coefficients of the original soil and the improved soil were based on the measured values ​​in the research and development experiment of the high-salt soil nutrient substrate cultivation technology to enhance seepage), as shown in Tables 1 and 2.

[0073] Table 1 Soil Hydraulic Characteristic Parameters

[0074] Soil type Residual moisture content θ (%) Saturated water content θ (%) Empirical coefficient α Empirical coefficient n Hydraulic conductivity coefficient K (cm / d) Empirical coefficient I original soil 0.0078 0.6 0.021 1.45 1.17 0.5 Improved soil 0.045 0.5 0.124 2.28 250 0.5

[0075] Table 2 Solute transport parameters

[0076] Soil type <![CDATA[Bulk density (g / cm 3 ).]]> Longitudinal dispersion coefficient (cm) Lateral dispersion coefficient (cm) Fract. Balance coefficient Thromb. Immovable water coefficient original soil 1.52 6 0.6 1 0 Improved soil 1.24 15 1.5 1 0

[0077] The third step, simulation analysis and scheme optimization, is as follows:

[0078] Based on model calibration, different terrain reshaping schemes were generated, including slope adjustment and re-layout of shallow ditches. Multi-year simulations were used to evaluate the impact of each scheme on shallow water salinity dynamics, salt flux, and natural desalination efficiency. Simulation results show that as channel spacing increases, the improvement cost gradually decreases, but the desalination time increases non-linearly. For example, with a channel spacing of 8m, the desalination time is approximately 115 days and the cost is 27.75 yuan / m²; with a spacing of 12m, the desalination time is approximately 516 days and the cost is 24.83 yuan / m²; while with a spacing ≥15m, desalination could not be completed within two years. Considering both economic efficiency and desalination efficiency, it is recommended that the channel spacing not exceed 12m.

[0079] Step 4, Alternative Model Training and Multi-Objective Optimization, is as follows:

[0080] The simulation results were used to train an alternative model, enabling it to quickly predict desalination effectiveness and salt return risk using terrain parameters as input. Based on the alternative model, the following key objective functions were established: ① maximizing natural salt drainage efficiency; ② minimizing shallow salt accumulation; ③ maximizing the rationality of groundwater level control (e.g., avoiding excessive drainage or water accumulation); ④ minimizing terrain modification costs. Simultaneously, practical engineering constraints were introduced, such as slope not exceeding the local stability threshold, ditch spacing conforming to construction specifications, and cut / fill volume controlled within feasible limits. Multi-objective optimization algorithms (e.g., NSGA-II, MOEA / D, etc.) were used to solve the above model, performing a Pareto front search in the objective space to obtain a set of non-dominated solutions (i.e., an optimal solution set). Finally, considering field conditions and management requirements, the optimal micro-topography-flow field co-reshaping scheme was selected from the Pareto solution set, providing a quantitative and controllable design basis for subsequent engineering implementation.

[0081] Step 5: Engineering Implementation Guidance: The final plan can be directly used to guide the engineering implementation, specifically including determining the extent of terrain adjustment, the location and depth of drainage ditches, the scale of micro-topographic undulations, the volume of earthwork for filling and excavation, and the configuration of shallow drainage paths. This method relies on natural potential energy and terrain structure to achieve desalination, and has the characteristics of low energy consumption, simple maintenance, and strong adaptability.

Claims

1. A method for simulating and optimizing the desalination of saline soil using a natural regulation mechanism, characterized in that: The method includes the following steps: Step 1: Data Acquisition and Pre-processing; Step 2: Construction of a water-salt transport model; Step 3: Simulation analysis and scheme optimization; Step 4: Alternative model training and multi-objective optimization; Step 5: Project Implementation Guidance: The final plan is directly used to guide the project implementation, specifically including determining the range of terrain adjustment, the location and depth of drainage ditches, the scale of micro-topographic undulations, the volume of earthwork for filling and excavation, and the configuration of shallow drainage paths.

2. The method for simulating and optimizing the desalination of saline soil using a natural regulation method according to claim 1, characterized in that... The specific steps in the first step are as follows: Step 1: Obtain a high-precision DEM of the study area and construct a regional micro-topography model by combining it with UAV lidar or high-resolution imagery; Step 2: Extract the structural features of surface runoff paths, waterlogged depressions, and potential drainage channels through topographic and runoff analysis; Step 3: Construct shallow groundwater level distribution using groundwater monitoring well data, and establish initial salinity field and hydraulic parameter library by combining soil salinity and moisture content monitoring data, so as to provide basic data support for subsequent modeling.

3. The method for simulating and optimizing the desalination of saline soil under natural regulation as described in claim 1, characterized in that... The specific steps of the second step are as follows: Step 1: Based on the data from Step 1 and Step 3, construct a water and salt transport model that considers topographic slope, groundwater dynamics and surface water cycle. The model is built using HYDRUS-2D software. The initial soil salinity is set to 2.1% and the slope is 10%. Simulate the salt discharge process at different drainage channel spacings of 8m, 10m, 12m, 15m and 20m. Step 2: Soil media are generalized into two categories: native soil and rotary tillage soil; the bottom of the model is set to a given water head and concentration boundary, the water level is level with the bottom of the drainage ditch, and the solution concentration corresponds to the saturated extract concentration of 2.1% soil salt content. Step 3: The top of the model is set as the atmospheric boundary, and the meteorological data are the monthly average values ​​of the study area over the years; the irrigation canal is set as the given head boundary, and the drainage canal is set as the seepage surface boundary; Step 4: The simulation period is 2 years. The model parameters are calibrated using monitoring data over several years to ensure that the simulation results are consistent with the measured water salt distribution, water level changes, and evaporation salt accumulation patterns.

4. The method for simulating and optimizing the desalination of saline soil using a natural regulation method according to claim 3, characterized in that... In the second step, step 1, the Hydrus-2D method quantitatively simulates water migration in a variablely saturated porous medium by solving the Richards equation and calculates the relative permeability coefficient using the Van Genuchten-Mualem formula. The combined values ​​and mathematical model formula for groundwater flow simulation are shown below: ； ； ； ； ； ； Where: θ(h) is the moisture content, in m³. 3 ·m -3 h is the pressure head, in meters (m); x and z are the horizontal and vertical coordinates, in meters (m); θ r Residual moisture content, in meters (m). 3 ·m -3 ; α,n,m,l are empirical fitting coefficients; S e θ represents relative saturation; θ0 represents initial water content in cubic meters (m³). 3 ·m -3 ; Given the head boundary; t is time, in days; K(h) is the permeability coefficient, in m / d; S(h) is the source and sink terms; θ s This is the saturated water content, in meters (m). 3 ·m -3 ;K s h0 is the saturated permeability coefficient, in m / d; h0 is the initial head, in m; S is the simulation range; h1 is the given head boundary. The head of water is measured in meters (m). Hydrus-2D quantitatively simulates salt migration by solving the advection–dispersion equation, as shown in the formula below. Since the main ion in the soil and groundwater of the study area is Cl... - and Na + Since it is chemically inert, interionic reactions are not considered. ； ； ； Where: c is the solute concentration in the soil solution, in mol / m³. 3 ; Let i be the spatial coordinates, i = 1, 2; Initial concentration, in mol / m³ 3 ; Given a concentration boundary; The dispersion coefficient is expressed in m. 2 / d; The water flow rate in the i-direction is expressed in m / d. For a given concentration boundary The concentration, in mol / m³ 3 .

5. The method for simulating and optimizing the desalination of saline soil using a natural regulation method according to claim 1, characterized in that... The specific steps of the third step are as follows: Step 1: Based on model calibration, generate different terrain reshaping schemes, including adjusting slope and re-laying shallow ditches, and evaluate the impact of each scheme on shallow water and salt dynamics, salt flux and natural salt discharge efficiency through multi-year scale simulation. Step 2: Taking into account both economic efficiency and salt removal efficiency, the channel spacing should not exceed 12m.

6. The method for simulating and optimizing the desalination of saline soil using a natural regulation method according to claim 1, characterized in that... The specific steps of the fourth step are as follows: Step 1: Use the simulation results to train the alternative model, so that the alternative model can quickly predict the desalination effect and the risk of salt return with terrain parameters as input; Step 2: Based on the alternative model, establish the following key objective functions: ① Maximize the efficiency of natural salt removal; ② Minimize the accumulation of shallow salt; ③ Groundwater level regulation is the most reasonable approach, avoiding excessive drainage or water accumulation; ④ Minimize terrain modification costs; Step 3: Introduce actual engineering constraints, such as ensuring that the slope does not exceed the local stability threshold, the spacing between ditches meets the construction specifications, and the volume of cut and fill is controlled within a feasible range; Step 4: Use multi-objective optimization algorithms, including NSGA-II and MOEA / D, to solve the model and perform Pareto front search in the objective space to obtain a set of non-dominated solutions, i.e., the set of optimization schemes; Step 5: Combining on-site conditions and management requirements, select the optimal micro-topography-flow field co-reshaping scheme from the Pareto solution set to provide a quantitative and controllable design basis for subsequent engineering implementation.

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