Heavy metal infiltration risk prediction method for reclaimed water irrigation mining and metallurgy area greenbelt soil

Abstract

The invention discloses a heavy metal infiltration risk prediction method for reclaimed water irrigation mining and metallurgy area greenbelt soil, which comprises the following steps: detecting the contents of heavy metals and salt ions in mining and metallurgy area reclaimed water and greenbelt soil, and detecting the physicochemical properties and hydraulic parameters of the soil; carrying out experimental simulation on the basis of detection data to obtain heavy metal form distribution and chemical equilibrium parameters of each phase of soil, then constructing a soil mineral phase-organic matter heavy metal adsorption kinetic model, constructing a soil solid phase equilibrium adsorption capacity calculation model, and further constructing a reclaimed water driven heavy metal geochemical migration process model; the heavy metal content of the mining and metallurgy area soil serves as an initial input item of the migration process model, and the heavy metal infiltration flux of the mining and metallurgy area greenbelt soil in the target prediction time is predicted in a rolling mode according to the heavy metal concentration of the recycled water; and calculating the heavy metal pollution index according to the predicted heavy metal infiltration flux. The method can quickly, accurately and economically evaluate the heavy metal infiltration risk of the reclaimed water irrigated green land soil.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental pollution prevention and control, and particularly relates to a method for predicting the heavy metal infiltration risk of green space soil irrigated with reclaimed water in mining and metallurgical areas. Background Art

[0002] Reclaimed water is an important supplementary water source for green space soil irrigation in China. The content of salt ions such as Na + , Cl - , SO4 2- in reclaimed water is high. Under long-term action, it can lead to a decrease in soil porosity and hydraulic conductivity, dispersion of soil aggregates, changes in soil pH, and accumulation of soil salts, thereby affecting the adsorption and migration of heavy metals in the soil. Due to the long-term influence of mining and smelting activities, the content of heavy metals (such as As, Cd, Pb, etc.) in the green space soil of mining and metallurgical areas has increased significantly. At the same time, the lower layer of the green space soil in mining and metallurgical areas is mostly miscellaneous fill soil, with complex material composition, a large proportion of coarse soil particles, high porosity and permeability coefficient, and more serious vertical migration of heavy metals compared with other types of soil. In addition, the reclaimed water used for irrigating the green space soil in mining and metallurgical areas contains both high heavy metal ions and salt ions, which may further exacerbate the risk of heavy metal pollution in the soil and groundwater, endangering the surrounding environment and human health. Therefore, the prevention and control of heavy metal pollution risks in the green space soil and groundwater of mining and metallurgical areas under reclaimed water irrigation is particularly important.

[0003] At present, the methods for evaluating the heavy metal migration risk in green space soil under reclaimed water irrigation mostly adopt on-site long-term fixed-point monitoring or prediction by migration models. However, the spatial heterogeneity of the physical and chemical properties of the soil profile layers in the green space soil of mining and metallurgical areas is obvious, and the cost of on-site long-term monitoring is high. At the same time, the existing solute migration models simplify the coupling mechanism of the mineral phase-organic matter-liquid phase system in the soil on heavy metals, and do not consider the important influence of the dynamic change process of the above system on the heavy metal speciation distribution under the action of reclaimed water salt ions, resulting in low prediction accuracy of the model and being unable to be directly used for the green space soil of mining and metallurgical areas. Summary of the Invention

[0004] The present invention provides a method for predicting the heavy metal infiltration risk of green space soil irrigated with reclaimed water in mining and metallurgical areas, which can quickly, accurately and economically evaluate the long-term heavy metal infiltration pollution risk of green space soil and groundwater in mining and metallurgical areas.

[0005] To achieve the above technical purpose, the present invention adopts the following technical solutions:

[0006] A method for predicting the heavy metal infiltration risk of green space soil irrigated with reclaimed water in mining and metallurgical areas, comprising:

[0007] S1, detecting the heavy metal concentration, salt ion concentration of the reclaimed water in the mining and metallurgical area, the heavy metal content and salt ion content in the green space soil, and detecting the soil physical and chemical properties and hydraulic parameters;

[0008] S2. Based on the detection data in S1, conduct experimental simulations to obtain the heavy metal speciation distributions in each phase of the soil and the chemical equilibrium parameters at each time period.

[0009] S3. Based on the heavy metal speciation distributions and chemical equilibrium parameters of the soil, construct a kinetic model for heavy metal adsorption by the soil mineral phase - organic matter, and construct a calculation model for the equilibrium adsorption capacity of the soil solid phase.

[0010] S4. Based on the kinetic model for heavy metal adsorption and the calculation model for the equilibrium adsorption capacity of the solid phase, construct a model for the geochemical migration process of heavy metals driven by reclaimed water.

[0011] S5. Take the heavy metal content in the soil of the mining and smelting area as the initial input item of the migration process model, and based on the heavy metal concentration in the reclaimed water, roll - predict the heavy metal cumulative content and infiltration concentration in the green space soil of the mining and smelting area during the target prediction period.

[0012] S6. Calculate the corresponding heavy metal pollution index according to the predicted heavy metal cumulative content and infiltration concentration in the soil.

[0013] Further, S2 specifically includes: First, based on the detection data, construct a heavy metal speciation distribution model for the soil mineral phase - organic matter - liquid phase; then, simulate the speciation distribution characteristics of multiple heavy metals in the soil mineral phase, organic matter, and liquid phase, and obtain the following chemical equilibrium parameters: mineral phase dissolution rate constant, mineral ion - state precipitation rate constant, organic matter degradation rate constant, mineral phase heavy metal equilibrium adsorption capacity, organic matter heavy metal equilibrium adsorption capacity, and liquid - phase heavy metal concentration.

[0014] Further, the kinetic model for heavy metal adsorption by the soil mineral phase - organic matter constructed in S3 is expressed as:

[0015]

[0016] In the formula, C MP , C Mn+ , C SOM are the mineral phase content, mineral ion - state content, and organic matter content respectively; t represents the time step, that is, the length of each time period; k dis , k pre , k deg are the mineral phase dissolution rate constant, mineral ion - state precipitation rate constant, and organic matter degradation rate constant respectively, and all belong to chemical equilibrium parameters; I SOM is the increment of organic matter.

[0017] Further, the calculation model for the equilibrium adsorption capacity of the soil solid phase constructed in S3 is expressed as:

[0018] C s = q MP ×CMP +q SOM ×C SOM

[0019] In the formula, C s is the heavy metal equilibrium adsorption capacity of the soil solid phase; C MP , C SOM are the mineral phase content and the organic matter content respectively; q MP , q SOM are the heavy metal equilibrium adsorption capacities of the mineral phase and the organic matter respectively.

[0020] Furthermore, the model of the heavy metal geochemical migration process driven by reclaimed water constructed in S4 is expressed as:

[0021]

[0022] C Total = θC l + ρC s

[0023]

[0024] In the formula, C Total is the heavy metal content in the soil profile of the green space in the mining and smelting area; C Rec is the heavy metal concentration in the reclaimed water; W Rec is the volume of the reclaimed water; v is the hydraulic conductivity, C l is the heavy metal concentration in the soil liquid phase, D is the hydrodynamic dispersion coefficient, θ is the soil moisture content, z is the soil layer depth; C s is the heavy metal equilibrium adsorption capacity of the soil solid phase; is the heavy metal absorption flux of the green space plants, PUF is the plant absorption coefficient, G Bio is the growth rate of the above-ground biomass of the plants, R Per is the percentage of the soil layer roots, and ρ is the soil density.

[0025] Furthermore, for the model of the heavy metal geochemical migration process driven by reclaimed water, the heavy metal concentration C Rec in the reclaimed water, the heavy metal equilibrium adsorption capacity C s of the soil solid phase, the hydraulic conductivity v, the hydrodynamic dispersion coefficient D, the soil moisture content θ, and the soil density ρ, all use the data distribution obtained by Monte Carlo simulation.

[0026] Furthermore, in S1 to S4, the green space soil is divided into multiple soil layers to construct the corresponding heavy metal migration process models respectively; in S5:

[0027] Heavy metal migration process model for any j-th soil layer. The heavy metal content of this soil layer is used as the initial input item, and the depth of this soil layer and various soil parameters are used as input parameters. Iterative calculations are performed according to the time step to predict the heavy metal infiltration flux at the lower boundary of this soil layer during the target prediction period.

[0028] Among them, the heavy metal flux input at the upper boundary of the first soil layer during a certain period is determined according to the heavy metal concentration of the reclaimed water for irrigation during this period; the heavy metal flux input at the upper boundaries of the remaining soil layers during this period is determined according to the heavy metal infiltration flux at the lower boundary of the previous soil layer during this period.

[0029] According to the difference between the heavy metal fluxes input and output at the upper and lower boundaries of the soil layer at the predicted depth during the target prediction period, calculate the heavy metal content of the soil layer at the predicted depth during the target prediction period, which is the heavy metal cumulative content of the soil layer at the predicted depth during the target prediction period; according to the heavy metal flux output at the lower boundary of the last soil layer at the predicted depth during the target prediction period, calculate the heavy metal concentration at the lower boundary of the last soil layer at the predicted depth during the target prediction period, which is the heavy metal concentration of the groundwater at the predicted depth during the target prediction period.

[0030] Furthermore, the single factor index method is used to calculate the heavy metal pollution index.

[0031] Furthermore, the heavy metal refers to any heavy metal present in the soil of the mining and smelting area; if there are multiple heavy metals in the soil of the mining and smelting area, the pollution index of each heavy metal is calculated according to S1 to S6.

[0032] Furthermore, after obtaining the pollution indices of multiple heavy metals, the comprehensive pollution index of multiple heavy metals is calculated according to the Nemerow pollution index method, and finally the heavy metal infiltration risk is rated according to the comprehensive pollution index.

[0033] Beneficial effects

[0034] Based on the elemental geochemical migration process, the present invention first constructs an integrated assessment technology for predicting the heavy metal infiltration risk of green space soil in the mining and smelting area irrigated with reclaimed water. According to the data characteristics of the reclaimed water in the mining and smelting area and the parameters of each soil layer in the green space soil profile, the heavy metal speciation distribution model of soil mineral phase - organic matter - liquid phase and the heavy metal adsorption kinetics model of soil mineral phase - organic matter are coupled, and a heavy metal geochemical migration process model driven by reclaimed water is constructed in combination with Monte Carlo simulation to predict the heavy metal infiltration flux, effectively determining the occurrence probability and risk level of heavy metal pollution risks in green space soil and groundwater. This integrated assessment technology has high prediction accuracy and low cost, and is of great significance for the assessment of heavy metal infiltration pollution risks in green space soil irrigated with reclaimed water in the mining and smelting area and the prevention and control of heavy metal pollution in groundwater. Description of the drawings

[0035] Figure 1It is the flowchart of the method described in the embodiments of the present invention.

[0036] Figure 2 It is the probability map of the occurrence of As and Cd pollution risks in different types of soil layers and groundwater in the green space soil profile in the mining and smelting area of the embodiments of the present invention.

[0037] Figure 3 It is the risk level map of heavy metal infiltration pollution in different types of soil layers and groundwater in the green space soil profile in the mining and smelting area of the embodiments of the present invention, where (a), (b), (c), and (d) represent green space soil, miscellaneous fill, completely weathered slate, and groundwater respectively. Detailed implementation manners

[0038] The embodiments of the present invention will be described in detail below. Based on the technical solutions of the present invention, detailed implementation manners and specific operation processes are given, and the technical solutions of the present invention are further explained.

[0039] Taking the risk assessment of heavy metal pollution in the soil and groundwater of the green space irrigated by reclaimed water in a lead-zinc smelting area in Hunan Province as an example. A method for predicting the heavy metal infiltration risk of the green space soil irrigated by reclaimed water in the mining and smelting area includes the following steps:

[0040] S1, detecting the heavy metal concentration, salt ion concentration of the reclaimed water in the mining and smelting area, the heavy metal content, salt ion content in the green space soil, and detecting the soil physical and chemical properties and hydraulic parameters.

[0041] In this embodiment, a water quality sampler is used to collect samples of the reclaimed water for green space irrigation in the mining and smelting area; the green space soil (0 - 1m), miscellaneous fill (1 - 3m), and completely weathered slate (3 - 5m) are collected according to the stratification of the green space soil profile in the smelting area.

[0042] After collecting the reclaimed water and soil samples, the reclaimed water and the profile soil layer samples are pretreated respectively: the reclaimed water is filtered through a 0.45μm filter membrane to obtain a filtrate, and the profile soil layer soil samples are sieved through a 100 - mesh sieve and digested with HNO3 - HCl - H2O2; the concentrations of As, Cd, Fe, Al, and Na in the pretreated samples are measured by an inductively coupled plasma mass spectrometer, and the Cl - , SO4 2- concentrations are measured by an ion chromatograph.

[0043] Detect the depths of each soil layer underground in the green space soil of the mining and metallurgical area, as well as various physical and chemical properties and hydraulic parameters of the soil. Specifically: the soil layer depth z is obtained through on-site measurement, the soil temperature T is measured using a geothermal thermometer, the soil density ρ is measured using the cutting ring method, the soil moisture content θ is measured using the drying method, the soil pH value is measured using the glass electrode method, the soil organic matter (SOM) is measured using the low-temperature external heating potassium dichromate oxidation-colorimetric method, the amorphous iron (hydr)oxide (AIO) and amorphous aluminum (hydr)oxide (AAO) in the soil are both extracted using the ammonium oxalate method and measured using inductively coupled plasma mass spectrometry, the crystalline iron (hydr)oxide (CIO) and crystalline aluminum (hydr)oxide (CAO) in the soil are both measured using the subtraction method, the hydraulic conductivity v is measured using a disk infiltrometer, and the hydraulic dispersion coefficient D is measured using a column leaching experiment.

[0044] S2. Based on the detection data in S1, conduct experimental simulations to obtain the heavy metal speciation distributions in each phase of the soil and the chemical equilibrium parameters at each time period.

[0045] First, construct a heavy metal speciation distribution model for the soil mineral phase - organic matter - liquid phase based on the detection data; then, simulate the speciation distribution characteristics of various heavy metals in the soil mineral phase, organic matter, and liquid phase, and obtain the following chemical equilibrium parameters: mineral phase dissolution rate constant, mineral ion precipitation rate constant, organic matter degradation rate constant, heavy metal equilibrium adsorption capacity of the mineral phase, heavy metal equilibrium adsorption capacity of the organic matter, and heavy metal concentration in the liquid phase.

[0046] In this embodiment, based on the detection data obtained in step 1, use the CD - MUSIC model and the SHM model to construct a heavy metal speciation distribution model for the soil mineral phase - organic matter - liquid phase, and simulate the speciation distribution characteristics of the ionic state, amorphous iron (hydr)oxide - bound state, crystalline iron (hydr)oxide - bound state, amorphous aluminum (hydr)oxide - bound state, crystalline aluminum (hydr)oxide - bound state, and organic matter - bound state of As and Cd under different environmental conditions (pH, Na + , Cl - , SO4 2- ). Through experimental simulations, obtain the following chemical equilibrium parameters at each environmental condition and each time period: mineral phase dissolution rate constant k dis , mineral ion precipitation rate constant k pre , organic matter degradation rate constant k deg , heavy metal equilibrium adsorption capacity of the mineral phase q MP , heavy metal equilibrium adsorption capacity of the organic matter q SOM , and heavy metal concentration in the soil liquid phase C l .

[0047] S3. Based on the heavy metal speciation distribution and chemical equilibrium parameters of the soil, construct a heavy metal adsorption kinetic model for the soil mineral phase - organic matter, and construct a calculation model for the equilibrium adsorption capacity of the soil solid phase.

[0048] Among them, the constructed heavy metal adsorption kinetic model of soil mineral phase-organic matter is used to simulate the heavy metal equilibrium adsorption processes of mineral phase and organic matter under different environmental conditions, and obtain the solid-phase heavy metal equilibrium adsorption amount. It is expressed as:

[0049]

[0050] In the formula, C MP , C Mn+ , C SOM are the mineral phase content, mineral ion state content, and organic matter content respectively; t represents the time step, that is, the length of each time period, such as 1 month or 1 year; k dis , k pre , k deg are the mineral phase dissolution rate constant, mineral ion state precipitation rate constant, and organic matter degradation rate constant respectively, and all belong to chemical equilibrium parameters; I SOM is the organic matter increment.

[0051] Among them, the constructed calculation model of soil solid-phase equilibrium adsorption amount is expressed as:

[0052] C s =q MP ×C MP +q SOM ×C SOM

[0053] In the formula, C s is the heavy metal equilibrium adsorption amount of soil solid phase; C MP , C SOM are the mineral phase content and organic matter content respectively; q MP , q SOM are the heavy metal equilibrium adsorption amounts of mineral phase and organic matter respectively.

[0054] S4. Based on the heavy metal adsorption kinetic model and the solid-phase equilibrium adsorption amount calculation model, construct a model for the geochemical migration process of heavy metals driven by reclaimed water.

[0055] Among them, the constructed model for the geochemical migration process of heavy metals driven by reclaimed water is expressed as:

[0056]

[0057] C Total =θC l +ρC s

[0058]

[0059] In the formula, C TotalC is the heavy metal content in the soil profile of the green space in the mining and metallurgy area; Rec C Rec is the heavy metal concentration in the reclaimed water; W Rec W Rec is the volume of the reclaimed water; v is the hydraulic conductivity, C l C l is the heavy metal concentration in the soil liquid phase, D is the hydrodynamic dispersion coefficient, θ is the soil moisture content, and z is the soil layer depth; s C s is the equilibrium adsorption amount of heavy metals in the soil solid phase; G is the heavy metal absorption flux of the green space plants, and PUF is the plant absorption coefficient; Bio R Bio is the growth rate of the above-ground biomass of the plants; Per R Per is the percentage of the soil layer roots, and ρ is the soil density.

[0060] In a more preferred embodiment, the heavy metal concentration C Rec in the reclaimed water in the process model of the heavy metal geochemical migration driven by the reclaimed water Rec 、the equilibrium adsorption amount C s of heavy metals in the soil solid phase s 、the hydraulic conductivity v, the hydrodynamic dispersion coefficient D, the soil moisture content θ, and the soil density ρ are all obtained by Monte Carlo simulation to obtain the data distribution, so as to predict the heavy metal migration flux and the lower boundary output flux of the soil layer from a probabilistic perspective, and obtain the corresponding heavy metal cumulative content and infiltration concentration. Specifically, based on the data characteristics (such as normal distribution, lognormal distribution, etc.) of the heavy metal concentration in the reclaimed water, the heavy metal content in the soil, and each soil parameter detected in step 1, Monte Carlo simulation is carried out. In this embodiment, the number of simulation times is set to 10,000 times, and 10,000 groups of data of the heavy metal concentration in the reclaimed water, the heavy metal content in the soil, and each soil parameter in their respective data distribution intervals are obtained, so as to solve the problem of large result errors caused by using fixed values in the parameter research of the traditional solute migration model.

[0061] S5. Use the heavy metal content in the soil of the mining and metallurgy area as the initial input item of the migration process model, and roll predict the heavy metal cumulative content and infiltration concentration of the green space soil in the mining and metallurgy area during the target prediction period according to the heavy metal concentration in the reclaimed water.

[0062] In this embodiment, in S1 to S4, the green space soil is divided into multiple soil layers to construct the corresponding heavy metal migration process models respectively; in S5:

[0063] For the heavy metal migration process model of any soil layer, use the heavy metal content of this soil layer as the initial input item, use the depth of this soil layer and each soil parameter as input parameters, and perform iterative calculations according to the time step to predict the heavy metal infiltration flux at the lower boundary of this soil layer during the target prediction period;

[0064] Among them, the heavy metal flux input at the upper boundary of the first soil layer during a certain period is determined according to the heavy metal concentration of the recycled water for irrigation during this period; the heavy metal fluxes input at the upper boundaries of the remaining soil layers during this period are determined according to the heavy metal infiltration fluxes at the lower boundaries of the previous soil layers during this period.

[0065] According to the difference between the heavy metal fluxes input and output at the upper and lower boundaries of the soil layer at the predicted depth during the target prediction period, calculate the heavy metal content in the soil layer at the predicted depth during the target prediction period, which is the heavy metal cumulative content in the soil layer at the predicted depth during the target prediction period; according to the heavy metal flux output at the lower boundary of the last soil layer at the predicted depth during the target prediction period, calculate the heavy metal concentration at the lower boundary of the last soil layer at the predicted depth during the target prediction period, which is the heavy metal concentration in the groundwater at the predicted depth during the target prediction period.

[0066] S6. Calculate the corresponding heavy metal pollution index according to the predicted heavy metal cumulative content and infiltration concentration.

[0067] The heavy metals in this embodiment refer to any one of the heavy metals existing in the soil of the mining and smelting area, and the pollution index of this any one heavy metal is calculated by the single factor index method.

[0068] If there are multiple heavy metals in the soil of the mining and smelting area, the pollution index of each heavy metal is calculated according to S1 to S6. After obtaining the pollution indices of multiple heavy metals, calculate the comprehensive pollution index of multiple heavy metals according to the Nemerow pollution index method, and finally rate the heavy metal infiltration risk according to the comprehensive pollution index.

[0069] In this embodiment, according to the contents of two heavy metals, As and Cd, in the profile soil layer at the target prediction period and the concentrations of the two heavy metals, As and Cd, at the lower boundary of the profile soil layer output by the heavy metal geochemical migration process model driven by recycled water in step S5, they are respectively compared with the background values of the contents of As (13.6 mg / kg) and Cd (0.08 mg / kg) in the soil of the case area and the class III limits of the contents of As (0.01 mg / L) and Cd (0.005 mg / L) specified in the "Groundwater Quality Standard" (GB / T 14848 - 2017). The heavy metal pollution risks of the soil and groundwater in the mining and smelting area are characterized by the single factor index method and the Nemerow pollution index method, and the occurrence probability and risk pollution level of the heavy metal pollution risks of the green space soil and groundwater in the mining and smelting area are evaluated.

[0070] (1) Calculate the pollution index of each heavy metal according to the single factor index method:

[0071]

[0072] In the formula, P i is the pollution index of the i-th heavy metal; C iis the model-predicted output content of the i-th heavy metal; C si is the standard content of the i-th heavy metal; when P i > 1, it indicates that this heavy metal has exceeded the standard, and the larger P i , the more serious the exceeding of the standard; the soil standard content C si refers to the local soil heavy metal background value, and the groundwater standard content C si refers to "Groundwater Quality Standard" (GB / T 14848 - 2017).

[0073] After obtaining the pollution index of this heavy metal for each group of data, calculate the proportion of the pollution index of the i-th heavy metal greater than 1 in the cumulative N groups of data, and count the cumulative probability as the occurrence probability of the i-th heavy metal exceeding the standard.

[0074] (2) After calculating the pollution index of each heavy metal, calculate the comprehensive heavy metal pollution index according to the Nemerow pollution index method:

[0075]

[0076] In the formula, P is the comprehensive heavy metal pollution index; P imax is the maximum value among the pollution indexes of all heavy metals; P iavg is the average value of the pollution indexes of all heavy metals;

[0077] When P < 0.70, the predicted depth soil is unpolluted; when 0.70 ≤ P < 0.10, there is a pollution risk in the predicted depth soil; when 0.10 ≤ P < 0.20, the predicted depth soil is slightly polluted; when 0.20 ≤ P < 0.30, the predicted depth soil is moderately polluted; when P ≥ 3.00, the soil is severely polluted;

[0078] When P < 0.59, the predicted depth water quality category is Class I; when 0.59 ≤ P < 0.74, the predicted depth water quality category is Class II; when 0.74 ≤ P < 1, the predicted depth water quality category is Class III; when 1 ≤ P < 3.50, the predicted depth water quality category is Class IV; when P ≥ 3.50, the predicted depth water quality category is Class V.

[0079] After obtaining the corresponding comprehensive heavy metal pollution index for each group of data, count the proportion of various soil pollution degrees and various water qualities in 10,000 groups of data. If the proportions of unpolluted soil and Class I water quality reach the preset values (such as preset to 80%), it is considered that the pollution risk of soil and groundwater is low.

[0080] Figure 2The results of the single-factor index show that after 10 years, the occurrence probabilities of As pollution risks in the green soil, miscellaneous fill soil, and completely weathered slate in the soil profile of the green space in the mining and metallurgy area are 5.31%, 4.28%, and 2.96% respectively, and the occurrence probabilities of Cd pollution risks are 8.99%, 7.57%, and 5.02% respectively; the occurrence probabilities of As and Cd pollution in groundwater are 2.06% and 3.89% respectively.

[0081] Figure 3 The Nemerow pollution index shows that after 10 years, the probabilities that the green soil, miscellaneous fill soil, and completely weathered slate in the soil profile of the green space in the mining and metallurgy area reach the unpolluted level are 90.8%, 91.2%, and 94.3% respectively; the probability that the leaching water quality of groundwater reaches Class I standard is 95.5%. Through engineering verification, this method can predict the infiltration and migration risks of heavy metals in the green space soil of the mining and metallurgy area irrigated with reclaimed water with high efficiency and low cost, and has high accuracy.

[0082] The above embodiments are the preferred embodiments of the present application. Those of ordinary skill in the art can also make various transformations or improvements on this basis. Without departing from the general concept of the present application, these transformations or improvements should all fall within the scope protected by the present application.

Claims

1. A method for predicting the heavy metal infiltration risk of reclaimed water-irrigated green space soil in mining and metallurgical areas, characterized in that Including: S1. Detect the heavy metal concentration and salt ion concentration of reclaimed water in the mining and metallurgy area, and the heavy metal content and salt ion content in the green space soil, and detect the soil physical and chemical properties and hydraulic parameters; S2. Conduct experimental simulations based on the detection data in S1 to obtain the heavy metal speciation distribution in each phase of the soil and the chemical equilibrium parameters at each time period; S3. Based on the heavy metal speciation distribution and chemical equilibrium parameters of the soil, construct a kinetic model for heavy metal adsorption on soil mineral phase - organic matter, and construct a calculation model for the equilibrium adsorption capacity of the soil solid phase; S4. Based on the kinetic model for heavy metal adsorption and the calculation model for the equilibrium adsorption capacity of the solid phase, construct a model for the geochemical migration process of heavy metals driven by reclaimed water; S5. Take the heavy metal content of the soil in the mining and metallurgy area as the initial input item of the migration process model, and according to the heavy metal concentration of the reclaimed water, roll - predict the heavy metal accumulation content and infiltration concentration in the green space soil of the mining and metallurgy area during the target prediction period; S6. Calculate the corresponding heavy metal pollution index according to the predicted heavy metal accumulation content and infiltration concentration in the soil; 2. The heavy metal infiltration risk prediction method according to claim 1, wherein S2 specifically includes: First, construct a heavy metal speciation distribution model for soil mineral phase - organic matter - liquid phase based on the detection data; then, simulate the speciation distribution characteristics of multiple heavy metals in the soil mineral phase, organic matter, and liquid phase, and obtain the following chemical equilibrium parameters: mineral phase dissolution rate constant, mineral ionic precipitation rate constant, organic matter degradation rate constant, heavy metal equilibrium adsorption capacity of the mineral phase, heavy metal equilibrium adsorption capacity of the organic matter, and heavy metal concentration in the liquid phase.

3. The heavy metal infiltration risk prediction method according to claim 1, wherein The kinetic model for heavy metal adsorption on soil mineral phase - organic matter constructed by S3 is expressed as: where C MP , C SOM are the mineral phase content, the mineral ionic state content, and the organic matter content respectively; t represents the time step, that is, the length of each time period; k dis , k pre , k deg are the mineral phase dissolution rate constant, the mineral ionic state precipitation rate constant, and the organic matter degradation rate constant respectively, all of which belong to the chemical equilibrium parameters; I SOM is the increment of organic matter.

4. The heavy metal infiltration risk prediction method according to claim 1, wherein The calculation model for the equilibrium adsorption capacity of the soil solid phase constructed by S3 is expressed as: C s = q MP × C MP + q SOM × C SOM where C s is the equilibrium adsorption amount of heavy metals in the soil solid phase; C MP , C SOM are the mineral phase content and the organic matter content respectively; q MP , q SOM are the equilibrium adsorption amounts of heavy metals in the mineral phase and the organic matter respectively.

5. The heavy metal infiltration risk prediction method according to claim 1, wherein The model for the geochemical migration process of heavy metals driven by reclaimed water constructed by S4 is expressed as: C Total = θC l + ρC s Where C Total is the heavy metal content in the soil of the green space section in the mining and metallurgy area; C Rec is the heavy metal concentration in the reclaimed water; W Rec is the volume of reclaimed water; v is the hydraulic conductivity, C l is the heavy metal concentration in the soil liquid phase, D is the hydrodynamic dispersion coefficient, θ is the soil moisture content, and z is the soil layer depth; C s is the heavy metal equilibrium adsorption amount in the soil solid phase; is the heavy metal absorption flux of the green space plants, PUF is the plant absorption coefficient, G Bio is the growth rate of the above-ground biomass of the plants, R Per is the percentage of the soil layer roots, and ρ is the soil density.

6. The heavy metal infiltration risk prediction method according to claim 5, characterized in that, The model for the process of heavy metal geochemical migration driven by reclaimed water, in which the heavy metal concentration C in the reclaimed water Rec , the equilibrium adsorption amount C s of heavy metals in the soil solid phase, the hydraulic permeability coefficient v, the hydraulic dispersion coefficient D, the soil moisture content θ, and the soil density ρ are all obtained by Monte Carlo simulation for data distribution.

7. The heavy metal infiltration risk prediction method according to claim 1, wherein In S1 to S4, the green space soil is divided into multiple soil layers to construct the corresponding heavy metal migration process models respectively; in S5: For the heavy metal migration process model of any j - th soil layer, use the heavy metal content of this soil layer as the initial input item, use the depth and various soil parameters of this soil layer as input parameters, and perform iterative calculations according to the time step to predict the heavy metal infiltration flux at the lower boundary of this soil layer during the target prediction period; Among them, the heavy metal flux input at the upper boundary of the first soil layer during a certain time period is determined according to the heavy metal concentration of the reclaimed water for irrigation during this time period; the heavy metal flux input at the upper boundaries of the remaining soil layers during this time period is determined according to the heavy metal infiltration flux at the lower boundary of the previous soil layer during this time period; According to the difference between the heavy metal fluxes input and output at the upper and lower boundaries of the predicted depth soil layer during the target prediction period, calculate the heavy metal content in the predicted depth soil layer during the target prediction period, which is the heavy metal accumulation content in the predicted depth soil layer during the target prediction period; according to the heavy metal flux output at the lower boundary of the last soil layer with the predicted depth during the target prediction period, calculate the heavy metal concentration at the lower boundary of the last soil layer with the predicted depth during the target prediction period, which is the heavy metal concentration in the groundwater at the predicted depth during the target prediction period.

8. The heavy metal infiltration risk prediction method according to claim 1, characterized in that The single - factor index method is used to calculate the heavy metal pollution index.

9. The heavy metal infiltration risk prediction method according to claim 1, characterized in that The heavy metal refers to any heavy metal present in the soil of the mining and smelting area; if there are multiple heavy metals in the soil of the mining and smelting area, the pollution index of each heavy metal is calculated according to S1 to S6.

10. The heavy metal infiltration risk prediction method according to claim 9, characterized in that, After obtaining the pollution indices of multiple heavy metals, the comprehensive pollution index of multiple heavy metals is calculated according to the Nemerow pollution index method, and finally the heavy metal leaching risk is rated according to the comprehensive pollution index.

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