Numerical simulation method for uranium form determination and migration rule in mining area water body

Abstract

The invention provides a numerical simulation method for determining a uranium form and a migration rule in a mining area water body. The method comprises the following steps: collecting mining area hydrogeological data and detecting basic water quality parameters of a water body sample; inputting the basic water quality parameters of the water body sample into PHREEQC software to construct a PHREEQC calculation model so as to calculate a uranium form distribution result, and determining various migration uranium forms according to the uranium form distribution result; the method comprises the following steps: inputting mining area hydrogeological data into GMS software to construct a three-dimensional hydrogeological model, coupling and simulating chemical reactions and solute transport of various migration uranium forms through a PHT3D module of the GMS software, and constructing a reaction solute transport model; operating the reaction solute transport model, and carrying out numerical simulation and result verification on the migration rules of various migration uranium forms; organic coupling of uranium form determination and migration simulation is achieved, the simulation precision is effectively improved, the research period is greatly shortened, the operation difficulty is reduced, and the method has wide engineering application prospects.

Description

Technical Field

[0001] This invention relates to the field of groundwater pollution detection technology, and more specifically, to a numerical simulation method for determining the speciation and migration patterns of uranium in mining area water. Background Technology

[0002] During uranium mining, beneficiation, and tailings accumulation, uranium can easily enter the surrounding aquatic environment, posing a serious threat to groundwater and surface water ecosystems and human health. The migration and transformation capabilities of uranium in water are closely related to its form; different forms of uranium possess different chemical activities, migration characteristics, and biological toxicity. Therefore, accurately determining the distribution of uranium forms in the water bodies of mining areas is a prerequisite for accurately predicting uranium migration patterns and formulating scientific pollution prevention and control measures.

[0003] Currently, research on uranium in mining area waters mainly focuses on total uranium detection or migration simulation of single uranium forms, which has the following shortcomings: First, traditional uranium form analysis methods are mostly experimental detection methods, such as ion chromatography and spectrophotometry, which are complex to operate, time-consuming, and difficult to achieve large-scale, dynamic form distribution monitoring; Second, existing numerical simulation techniques mostly use total uranium ... Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a numerical simulation method for determining the uranium speciation and migration law in mining water, which helps to achieve accurate calculation of uranium speciation distribution and accurate prediction of migration law, in view of the above-mentioned defects of the prior art.

[0005] The technical solution adopted by this invention to solve its technical problem is: a numerical simulation method for determining the speciation and migration law of uranium in mining area water, comprising: Collect basic water quality parameters of mining area hydrogeological data and test water samples; The basic water quality parameters of the water sample are input into the PHREEQC software to construct the PHREEQC calculation model. The PHREEQC calculation model is run to calculate the uranium speciation distribution results. Based on the uranium speciation distribution results, various types of migratory uranium speciations are determined. The hydrogeological data of the mining area is input into GMS software to construct a three-dimensional hydrogeological model. Based on the uranium speciation distribution results and the three-dimensional hydrogeological model, the chemical reactions and solute transport of various migratory uranium speciations are coupled and simulated through the PHT3D module of GMS software to construct a reactive solute transport model. The reaction solute transport model is run to perform numerical simulations and result verification on the migration patterns of the various migratory uranium forms, so as to determine the migration patterns of the various migratory uranium forms.

[0006] In some embodiments, inputting the basic water quality parameters of the water sample into the PHREEQC software to construct the PHREEQC calculation model includes: Input the basic water quality parameters of the water sample into the PHREEQC software, select the appropriate thermodynamic database from the PHREEQC software, and define the chemical composition and reaction type of the various migratory uranium species in the water. The chemical components of the various migratory forms of uranium include, but are not limited to: UO2(CO3)2 2- UO2(CO3)3 4- (UO2)2(OH)2 2+ UO2CO3, UO2 2+ UO2(OH)3 - UO2OH + and UO2SO4; The reaction types include, but are not limited to, dissolution-precipitation reactions, complexation reactions, redox reactions, and hydrolysis reactions.

[0007] In some embodiments, the PHREEQC calculation model is used to calculate the uranium speciation distribution results, and various migratory uranium speciations are determined based on the uranium speciation distribution results, including: The PHREEQC calculation model was used to calculate the uranium speciation distribution under multiple pH conditions; wherein the pH range covered the actual pH range of the mining area water body detected in step one. Output the mole fraction and concentration of at least one or more migratory uranium forms at different pH values, analyze the variation of the various migratory uranium forms with pH, ​​and determine the dominant uranium form under different pH conditions. By comparing the experimentally tested data of various migratory uranium forms, the accuracy of the uranium form distribution results is verified. If the relative error exceeds a first preset threshold, the thermodynamic parameters or reaction type are adjusted and the calculation is repeated.

[0008] In some embodiments, the step of inputting the hydrogeological data of the mining area into GMS software to construct a three-dimensional hydrogeological model includes: The hydrogeological data of the mining area were input into GMS software, and a three-dimensional hydrogeological model was constructed using the MODFLOW module of GMS software. The three-dimensional hydrogeological model was meshed, boundary conditions were set, and hydrogeological parameters were assigned. The rationality of the three-dimensional hydrogeological model was verified by simulating the groundwater flow field.

[0009] In some embodiments, the boundary conditions include, but are not limited to, constant head boundaries and constant flow boundaries.

[0010] In some embodiments, the verification criterion for the simulated groundwater flow field is: the relative error between the simulated water level and the measured water level is controlled within a second preset threshold.

[0011] In some embodiments, the construction of a reactive solute transport model based on the uranium speciation distribution results and a three-dimensional hydrogeological model, using the PHT3D module of the GMS software to couple and simulate the chemical reactions and solute transport of various migratory uranium speciations, includes: Based on the uranium speciation results, the initial concentrations and solute transport parameters of each type of migratory uranium speciation are determined, while precipitated uranium is screened out. The initial concentrations of the various migratory uranium forms are input as source terms into the PHT3D module of the GMS software. At the same time, the reaction solute transport parameters and hydrogeological parameters are input to define the reaction types and kinetic parameters of the various migratory uranium forms during the migration process. The chemical reactions and solute transport of the various migratory uranium forms during the migration process are coupled and simulated. The solute transport parameters mentioned include, but are not limited to, diffusion coefficient and retardation coefficient.

[0012] In some embodiments, the diffusion coefficient is an empirical value; the retardation coefficient is calculated through adsorption experiments or an empirical formula, wherein the empirical formula is: (1); In formula (1) ρ b Where n is the dry density of the medium, n is the porosity, and K is the density of the medium. d This is the allocation coefficient.

[0013] In some embodiments, running the reactive solute transport model to numerically simulate and verify the migration patterns of various migratory uranium speciations, in order to determine the migration patterns of these speciations, includes: Run the solute transport model and set the simulation time step and simulation period to calculate the concentration distribution of various migratory uranium species at different time points and spatial locations; The measured concentrations of the various migratory uranium forms monitored at typical monitoring points within the mining area were compared with the simulated concentrations of the various migratory uranium forms. If the relative error between the simulated concentration and the measured concentration exceeds the third preset threshold, the hydrogeological parameters, solute transport parameters, or reaction kinetic parameters are adjusted and recalculated and optimized until the error meets the requirements. Based on the optimized simulation results, the migration paths, migration rates, and concentration decay patterns of uranium in the mining area's water were analyzed, clarifying the contribution percentage of each type of migratory uranium form to total uranium migration.

[0014] In some embodiments, the hydrogeological data of the mining area includes, but is not limited to, the topography, lithology, aquifer distribution, groundwater level, permeability coefficient, porosity, and specific yield of the mining area; The basic water quality parameters of the water samples include, but are not limited to, pH value, Eh value, temperature, total dissolved solids, concentration of major cations, concentration of major anions, and total uranium content.

[0015] Compared with existing technologies, the numerical simulation method for determining the speciation and migration patterns of uranium in mining water bodies of the present invention has the following advantages: 1. It achieves the organic coupling of uranium speciation determination and migration simulation. By giving full play to the advantages of PHREEQC software in hydrogeochemical speciation calculation and GMS software in complex solute transport simulation, it solves the problem of the disconnect between the two in traditional technologies. 2. High simulation accuracy: The uranium speciation distribution is calculated based on actual basic water quality parameters. The actual concentration of various migratory uranium speciations is used as the source term for migration simulation, avoiding the bias caused by the traditional simulation using total uranium amount. The simulation results are closer to the actual situation, thus improving the accuracy of uranium migration simulation. 3. Simple operation and high efficiency: The software coupling realizes the whole process numerical simulation, which replaces the traditional complex experimental detection and single simulation method, greatly shortens the research cycle and reduces the difficulty of operation; 4. Significant application value: It can provide scientific and accurate data support for the formulation of uranium pollution prevention and control measures in mining areas and for groundwater environmental risk assessment, and has broad engineering application prospects. Attached Figure Description

[0016] Figure 1 This is a flowchart of the numerical simulation method for determining the speciation and migration patterns of uranium in the water of the mining area in Example 1; Figure 2 This is a graph showing the relationship between uranium speciation and pH based on PHREEQC software in Example 2; Figure 3 This is a mesh partitioning diagram of a three-dimensional hydrogeological model based on GMS software in Example 2; Figure 4 This is a schematic diagram illustrating the migration process of uranium over time using the PHT3D module in Example 2; Figure 5 The dominant uranium form in Example 2 is UO2(CO3)2. 2- A comparison of the measured and simulated curves of uranium concentration decay. Detailed Implementation

[0017] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0018] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0019] "Multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0020] Furthermore, the terms indicating orientation, such as "up," "down," "front," "back," "left," "right," "upper end," and "lower end," are all based on the posture and position of the device or equipment described in this solution during normal use.

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, a clear and complete description will be provided below in conjunction with the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0022] PHREEQC software is a hydrogeochemical simulation software used to accurately calculate the speciation and distribution of various chemical substances in water bodies; GMS software is a groundwater simulation platform used to simulate solute transport under complex hydrogeological conditions. This invention organically couples these two technologies, fully leveraging their respective advantages to achieve synergy between "accurate determination of uranium speciation" and "accurate simulation of migration patterns." This effectively addresses the shortcomings of existing technologies and is of great significance for the prevention and control of uranium pollution in mining areas.

[0023] Example 1: This embodiment of the invention provides a numerical simulation method for determining the speciation and migration patterns of uranium in mining water, used to simulate the determination of uranium speciation and migration patterns, such as... Figure 1 As shown, please refer to steps S1 to S4. The specific steps of this method include: S1. Collect basic water quality parameters of mining area hydrogeological data and test water samples; Specifically, in S1, the hydrogeological data of the mining area includes, but is not limited to, the topography, stratigraphy, aquifer distribution, groundwater level, permeability coefficient, porosity, and specific yield; the basic water quality parameters of the water samples include, but are not limited to, pH value, Eh value, temperature, total dissolved solids (TDS), concentration of major cations, concentration of major anions, and total uranium content. Among these, major cations include, for example, Na+. + K + Ca 2+ Mg 2+ etc.; major anions such as Cl - SO4 2- HCO3 - CO3 2- wait.

[0024] S2. Input the basic water quality parameters of the water sample into the PHREEQC software to build the PHREEQC calculation model, run the PHREEQC calculation model to calculate the uranium speciation distribution results, and determine the various types of migratory uranium speciations based on the uranium speciation distribution results. Specifically, in S2, the basic water quality parameters of the water sample are input into the PHREEQC software to construct the PHREEQC calculation model, which includes: S21: Input the basic water quality parameters of the water sample into the PHREEQC software, select the appropriate thermodynamic database from the PHREEQC software, and define the chemical composition and reaction type of various migratory uranium forms in the water. The chemical components of various migratory forms of uranium include, but are not limited to: UO2(CO3)2 2- UO2(CO3)3 4- (UO2)2(OH)2 2+ UO2CO3, UO2 2+ UO2(OH)3 - UO2OH + And UO2SO4; these eight chemical components are the target uranium speciations that need to be clearly identified and calculated in this embodiment. Reaction types include, but are not limited to, dissolution-precipitation reactions, complexation reactions, redox reactions, and hydrolysis reactions. Uranium speciation calculations based on PHREEQC software need to consider pH dependence; hydrolysis reactions mainly refer to pH-related hydrolysis reactions. Thermodynamic databases include, for example, llnl.dat.

[0025] Specifically, in S2, the PHREEQC calculation model is run to calculate the uranium speciation distribution results. Based on the uranium speciation distribution results, various migratory uranium speciations are determined, including: S22: Calculate the uranium speciation distribution under multiple pH conditions using the PHREEQC calculation model; wherein the pH range covers the actual pH range of the mining area water body detected in step one; The pH range is distinguished, for example, by a gradient of acidic, neutral, and alkaline.

[0026] S23: Output the mole fraction and concentration of at least one or more migratory uranium forms at different pH values, analyze the variation of various migratory uranium forms with pH, ​​and determine the dominant uranium form under different pH conditions. Specific simulation results include, for example, UO2CO3 and UO2 under pH=5~6 conditions. 2+ UO2(CO3)2 is dominant under pH conditions of 6-7.7. 2- Dominant; UO2(CO3)3 under pH=7.7~10 conditions 4- Dominant; UO2(CO3)3 under pH=10~11 conditions 4- UO2(OH)3 - Dominant.

[0027] S24: Compare the data of various migratory uranium forms tested in experiments to verify the accuracy of the uranium form distribution results. If the relative error exceeds the first preset threshold, adjust the thermodynamic parameters or reaction type and recalculate.

[0028] Among them, experimental detection methods, such as ion-selective electrode method, are used to detect UO2. 2+ The concentration of UO2CO3 was determined by high-performance liquid chromatography (HPLC). The first preset threshold was, for example, 5%.

[0029] S3. Input the hydrogeological data of the mining area into GMS software to construct a three-dimensional hydrogeological model. Based on the uranium speciation distribution results and the three-dimensional hydrogeological model, use the PHT3D module of GMS software to couple and simulate the chemical reactions and solute transport of various migratory uranium speciations to construct a reactive solute transport model. Specifically, in S3, the hydrogeological data of the mining area is input into the GMS software to construct a three-dimensional hydrogeological model, which includes: S31: Input the hydrogeological data of the mining area into GMS software, and use the MODFLOW module of GMS software to construct a three-dimensional hydrogeological model; S32: Mesh the three-dimensional hydrogeological model, set boundary conditions, and assign hydrogeological parameters. Verify the rationality of the three-dimensional hydrogeological model by simulating the groundwater flow field.

[0030] The boundary conditions include, but are not limited to, constant head boundaries and constant flow boundaries. The verification criterion for the simulated groundwater flow field is that the relative error between the simulated water level and the measured water level is controlled within a second preset threshold. For example, the second preset threshold is 0.5m.

[0031] Specifically, in S3, based on the uranium speciation distribution results and the three-dimensional hydrogeological model, the chemical reactions and solute transport of various migratory uranium speciations are coupled and simulated using the PHT3D module of GMS software to construct a reactive solute transport model, which includes: S33: Based on the uranium speciation distribution results, determine the initial concentration and solute transport parameters of various migratory uranium speciations, and screen out precipitated uranium. The solute transport parameters in the reaction include, but are not limited to, the diffusion coefficient and the retardation coefficient. The diffusion coefficient is an empirical value; the retardation coefficient is calculated through adsorption experiments or empirical formulas, the empirical formulas being: (1); In formula (1) ρ b Where n is the dry density of the medium, n is the porosity, and K is the density of the medium. d This is the allocation coefficient.

[0032] S34: Input the initial concentrations of various migratory uranium forms as source terms into the PHT3D module of the GMS software, and simultaneously input reaction solute transport parameters and hydrogeological parameters to define the reaction types and kinetic parameters of various migratory uranium forms during the migration process, and couple the simulation of chemical reactions and solute transport of various migratory uranium forms during the migration process. The reaction types here are the same as those mentioned above, such as complexation reactions and redox reactions.

[0033] S4. Run the reaction solute transport model to conduct numerical simulations and verify the migration patterns of various migratory uranium forms in order to determine the migration patterns of various migratory uranium forms.

[0034] Specifically, in S4, a reactive solute transport model is run to numerically simulate and verify the migration patterns of various migratory uranium speciations, in order to determine the migration patterns of these speciations. This includes: S41: Run the reactive solute transport model, set the simulation time step and simulation period, and calculate the concentration distribution of various migratory uranium species at different time points and spatial locations; S42: Select the measured concentrations of various migratory uranium forms monitored at typical monitoring points in the mining area and compare them with the simulated concentrations of various migratory uranium forms. S43: If the relative error between the simulated concentration and the measured concentration exceeds the third preset threshold, adjust the hydrogeological parameters, reaction solute transport parameters or reaction kinetic parameters and recalculate and optimize until the error meets the requirements; The third preset threshold is, for example, 5%. Hydrogeological parameters include, for example, the permeability coefficient.

[0035] S44: Based on the optimized simulation results, analyze the migration path, migration rate and concentration decay law of uranium in the water body of the mining area, and clarify the contribution ratio of various migratory uranium forms to the total uranium migration.

[0036] It should be noted that the hydrogeological parameters, reaction kinetic parameters and other related parameters in this embodiment can be designed and selected according to the actual application requirements. This embodiment does not impose specific limitations and should be based on the actual application.

[0037] Example 2: This example of the invention takes the simulation of uranium pollution in groundwater of a uranium mining area as the research object. It uses the numerical simulation method for determining the speciation and migration patterns of uranium in the mining area's water provided in Example 1 to simulate the determination of uranium speciation and migration patterns. The specific steps are as follows: Step 1: Basic Data Collection and Testing Hydrogeological data of the uranium mining area: The terrain of the uranium mining area is low mountains and hills, the main strata are sandstone and mudstone, the aquifer is a sandstone pore-fracture aquifer, and the permeability coefficient is 5×10⁻⁶. -4 ~2×10 -3 The water density is 0.25 cm / s, the porosity is 0.12, and the groundwater level is 2-8m deep.

[0038] Basic water quality parameters of the water samples: Groundwater samples were collected from this uranium mining area, and the pH value was 7.1, Eh value was 597.3 mV, temperature was 25℃, and total dissolved solids (TDS) was 319.15 mg / L; the concentration of major cations (mg / L) was: Na + 6.67, K + 6.67, Ca 2+ 66.53, Mg 2+ 5.59; Major anion concentration (mg / L): Cl - 6.03, SO4 2- 13.45, HCO3 - 220.88; Total uranium content 2 mg / L.

[0039] Step 2: PHREEQC uranium speciation calculation (considering pH dependence) Constructing the PHREEQC calculation model: Input the above basic water quality parameters into the PHREEQC software, select the llnl.dat thermodynamic database of the PHREEQC software, and define the chemical components, including the target uranium form: UO2(CO3)2. 2- UO2(CO3)3 4- (UO2)2(OH)2 2+ UO2CO3, UO2 2+ UO2(OH)3 - UO2OH + UO2SO4 and Na + K + Ca 2+ Mg 2+ Cl - SO4 2- HCO3 - Conventional ions; reaction types include complexation reactions, redox reactions, and hydrolysis reactions (corresponding to different uranium forms).

[0040] Results and Verification: Based on the actual pH of the water in the mining area being 7.1, and combined with calculations using multiple pH gradients (5~11), the core law governing the change of uranium speciation with pH was clarified: under pH=5~6 conditions, UO2CO3 and UO2... 2+ UO2(CO3)2 is dominant under pH conditions of 6-7.7. 2- Dominant; UO2(CO3)3 under pH=7.7~10 conditions 4- Dominant; UO2(CO3)3 under pH=10~11 conditions 4- UO2(OH)3 - Dominant; the actual pH (7.1) in the mining area is between 6 and 7.7. Please see [link / reference]. Figure 2 , Figure 2 Used to demonstrate the eight target uranium forms (UO2(CO3)2) in step two. 2- UO2(CO3)3 4- (UO2)2(OH)2 2+ UO2CO3, UO2 2+ UO2(OH)3 - UO2OH + The mole fraction variation curves of UO2(CO3)2 in the pH range of 5–11 visually demonstrate the dependence of uranium speciation on pH. The results show that uranium is mainly in the carbonate complex state within the pH range of 5–11, and the mole fraction variation curves of UO2(CO3)2 in the 7.2–7.7 sub-range are also significant. 2- The mole fraction is 55.28%~76.73%; the sub-interval of UO2(CO3)3 is 7.7~8.3. 4-The mole fraction increased to 44.39%~83.69%, UO2(CO3)2 2- The mole fraction decreased to 16.21%~40.11%, and the mole fraction of UO2CO3 was 0.01%~0.28%; the hydrolyzed state ((UO2)2(OH)2) 2+ UO2OH + UO2(OH)3 - The total proportion is less than 0.5%, and there is no precipitated uranium. The concentration of UO2CO3 can be detected by high performance liquid chromatography. When the relative error between the measured values ​​of the three monitoring points (P1~P3) and the PHREEQC simulated values ​​is less than 5%, the accuracy requirement is met, proving that the method of this invention is accurate and reliable in identifying uranium speciation.

[0041] It should be noted that, for ease of distinction, Figure 2 The text also uses lowercase letters a~h (which serve only as identifiers and have no other meaning) to represent the mole fraction change curves of the aforementioned eight target uranium forms: where a represents UO2(CO3)2 2- The curve showing the change in mole fraction, where b represents UO2(CO3)3. 4- The curve showing the change in mole fraction, where c represents (UO2)2(OH)2. 2+ The curves showing the change in mole fraction of UO2CO3 are shown, where d represents the change in mole fraction of UO2CO3 and e represents the change in mole fraction of UO2CO3. 2+ The curve showing the change in mole fraction, where f represents UO2(OH)3. - The curve showing the change in mole fraction, where g represents UO2OH. + The curve showing the change in mole fraction is given by h, where h represents the change in mole fraction of UO2SO4.

[0042] Step 3: Construction of GMS Reaction Solute Transport Model A three-dimensional hydrogeological model was constructed: This simulation adopted a simplified model, constructing a cuboid three-dimensional model with X×Y×Z dimensions of 300m×180m×150m in GMS software. The mesh generation followed the principle of "balancing computational accuracy and efficiency, and refining the core area," specifically: the planar direction (XY direction) was uniformly divided according to the study area to ensure accurate capture of the core uranium migration path (from tailings dam to discharge area), while avoiding excessive mesh count that would reduce computational efficiency; therefore, a 50×50 structured mesh was used. The vertical direction (Z direction) was layered according to aquifer distribution characteristics to match the actual lithological homogeneity, using a 3-layer structured mesh to ensure the rationality of the vertical transport simulation. Boundaries were set as a constant head boundary on the west side, a constant flow boundary on the east side, and other boundaries as impermeable boundaries. Parameters such as permeability coefficient and porosity were input to simulate the groundwater flow field. The maximum error between the simulated water level and the measured water level was 0.3m, indicating a reasonable model. Please refer to [link to relevant documentation]. Figure 3 , Figure 3This method is used to demonstrate the meshing results of the simplified cuboid model (X×Y×Z=300m×180m×150m) in this step, clarify the planar (XY direction) and vertical (Z direction) distribution of the 50×50×3 structured mesh, mark the core uranium migration path (from tailings dam to discharge area) and boundary conditions (constant head boundary, constant flow boundary, water-isolated boundary), and reflect the meshing principle of "balancing computational accuracy and efficiency, and densifying the core area".

[0043] Determination of solute transport parameters in the reaction: Ki of three uranium speciations was determined by adsorption experiments. d Value, medium dry density ρ b And porosity n, according to formula (1) The retardation coefficients for the three uranium speciations were calculated; the diffusion coefficients were calculated using empirical values. The initial concentrations of the three uranium speciations were input as source terms into the PHT3D module of the GMS software. Simultaneously, the aforementioned retardation coefficients, diffusion coefficients, and other reaction solute transport parameters, as well as hydrogeological parameters, were input. Complexation reaction kinetic parameters were defined, and the chemical reaction-transport coupling simulation function of the PHT3D module was used to simulate the migration process of multiple uranium speciations. Please refer to... Figure 4 , Figure 4 This is used to illustrate the reactive solute transport involved in the uranium speciation process during this step.

[0044] Step 4: Numerical simulation and result verification of uranium migration laws Simulation calculation: The simulation period was set to 400 days and the time step was 1 day. The spatial concentration distribution of each uranium species at different time points was obtained by running the model.

[0045] Results Verification and Error Analysis: The core innovation of this invention is "accurate identification of uranium speciation → accurate simulation of migration". Therefore, the focus is on verifying the simulation accuracy of each dominant uranium speciation. Here, we take the dominant speciation UO2(CO3)2 as an example. 2- For example: ① Spatial concentration verification: A 400-day node was selected, with 3 monitoring points (P1~P3) for UO2(CO3)2. 2- Comparison of measured and simulated concentrations of (dominant form): The relative error is generally less than 5%; see Table 1 below. Table 1 records the dominant uranium form UO2(CO3)2 at different monitoring points (P1~P3) and different time points (0d~400d). 2- The measured and simulated concentrations of uranium concentration decay. The measured concentration refers to the UO2CO3 concentration detected by high performance liquid chromatography (HPLC) as described above, for comparison with the PHREEQC simulated concentration.

[0046] ② Time decay verification: using 3 monitoring points (P1~P3) to verify the dominant uranium speciation UO2(CO3)2 2- As the research subject, concentration decay verification was carried out at 16 time points from 0 to 400 days; please refer to [link to relevant documentation]. Figure 5 , Figure 5 The dominant uranium form, UO2(CO3)2, was observed at different monitoring points (P1~P3). 2- Comparison of measured and simulated curves of uranium concentration decay at different time points (0d~400d), with G1~G16 representing water injection wells. Data fitting analysis shows that the simulated curves and measured curves have a good fit, verifying the accuracy of this invention in simulating the time migration process of uranium speciation. ③ Migration Pattern Analysis: Simulation results show that the main migration path of uranium is from P1 (tailings pond) eastward along the X-axis to P3 (discharge zone), with a migration rate of approximately 10 m / year; UO2(CO3)2 2- The migration ability is the strongest (with the smallest hindrance coefficient), contributing approximately 92% of the total uranium migration and being the dominant migration form; see Table 1 below. Table 1 also records the measured and simulated concentrations of total uranium concentration decay at different monitoring points (P1~P3) and different time nodes (0d~400d). By comparison, it can be seen that the pattern obtained by the simulation method is almost consistent with the measured migration trend, proving that the present invention can accurately predict the migration pattern of uranium forms.

[0047]

[0048] Table 1 Furthermore, regarding the analysis of error sources: the errors mainly stem from the spatial heterogeneity of hydrogeological parameters (simplified to uniform parameters), but the morphological precision input in this embodiment has significantly reduced the errors of traditional total simulation.

[0049] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A numerical simulation method for determining the speciation and migration patterns of uranium in water bodies within mining areas, characterized in that, include: Collect basic water quality parameters of mining area hydrogeological data and test water samples; The basic water quality parameters of the water sample are input into the PHREEQC software to construct the PHREEQC calculation model. The PHREEQC calculation model is run to calculate the uranium speciation distribution results. Based on the uranium speciation distribution results, various types of migratory uranium speciations are determined. The hydrogeological data of the mining area is input into GMS software to construct a three-dimensional hydrogeological model. Based on the uranium speciation distribution results and the three-dimensional hydrogeological model, the chemical reactions and solute transport of various migratory uranium speciations are coupled and simulated through the PHT3D module of GMS software to construct a reactive solute transport model. The reaction solute transport model is run to perform numerical simulations and result verification on the migration patterns of the various migratory uranium forms, so as to determine the migration patterns of the various migratory uranium forms.

2. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 1, characterized in that, The step of inputting the basic water quality parameters of the water sample into the PHREEQC software to construct the PHREEQC calculation model includes: Input the basic water quality parameters of the water sample into the PHREEQC software, select the appropriate thermodynamic database from the PHREEQC software, and define the chemical composition and reaction type of the various migratory uranium species in the water. The chemical components of the various migratory forms of uranium include, but are not limited to: UO2(CO3)2 2- UO2(CO3)3 4- (UO2)2(OH)2 2+ UO2CO3, UO2 2+ UO2(OH)3 - UO2OH + and UO2SO4; The reaction types include, but are not limited to, dissolution-precipitation reactions, complexation reactions, redox reactions, and hydrolysis reactions.

3. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 2, characterized in that, The PHREEQC calculation model is used to calculate the uranium speciation distribution results. Based on the uranium speciation distribution results, various migratory uranium speciations are determined, including: The PHREEQC calculation model was used to calculate the uranium speciation distribution under multiple pH conditions; wherein the pH range covered the actual pH range of the mining area water body detected in step one. Output the mole fraction and concentration of at least one or more migratory uranium forms at different pH values, analyze the variation of the various migratory uranium forms with pH, ​​and determine the dominant uranium form under different pH conditions. By comparing the experimentally tested data of various migratory uranium forms, the accuracy of the uranium form distribution results is verified. If the relative error exceeds a first preset threshold, the thermodynamic parameters or reaction type are adjusted and the calculation is repeated.

4. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 1, characterized in that, The step of inputting the hydrogeological data of the mining area into GMS software to construct a three-dimensional hydrogeological model includes: The hydrogeological data of the mining area were input into GMS software, and a three-dimensional hydrogeological model was constructed using the MODFLOW module of GMS software. The three-dimensional hydrogeological model was meshed, boundary conditions were set, and hydrogeological parameters were assigned. The rationality of the three-dimensional hydrogeological model was verified by simulating the groundwater flow field.

5. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 4, characterized in that, The boundary conditions include, but are not limited to, constant head boundary and constant flow boundary.

6. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 4 or 5, characterized in that, The verification standard for the simulated groundwater flow field is: the relative error between the simulated water level and the measured water level is controlled within a second preset threshold.

7. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 4, characterized in that, Based on the uranium speciation distribution results and the three-dimensional hydrogeological model, the chemical reactions and solute transport of various migratory uranium speciations are coupled and simulated using the PHT3D module of the GMS software to construct a reactive solute transport model, including: Based on the uranium speciation results, the initial concentrations and solute transport parameters of each type of migratory uranium speciation are determined, while precipitated uranium is screened out. The initial concentrations of the various migratory uranium forms are input as source terms into the PHT3D module of the GMS software. At the same time, the reaction solute transport parameters and hydrogeological parameters are input to define the reaction types and kinetic parameters of the various migratory uranium forms during the migration process. The chemical reactions and solute transport of the various migratory uranium forms during the migration process are coupled and simulated. The solute transport parameters mentioned include, but are not limited to, diffusion coefficient and retardation coefficient.

8. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 7, characterized in that, The diffusion coefficient is an empirical value; the retardation coefficient is calculated through adsorption experiments or an empirical formula, the empirical formula being: （1）； In formula (1) ρ b Where n is the dry density of the medium, n is the porosity, and K is the density of the medium. d This is the allocation coefficient.

9. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 1, characterized in that, The process involves running the solute transport model to numerically simulate and verify the migration patterns of various migratory uranium species, thereby determining the migration patterns of these species, including: Run the solute transport model and set the simulation time step and simulation period to calculate the concentration distribution of various migratory uranium species at different time points and spatial locations; The measured concentrations of the various migratory uranium forms monitored at typical monitoring points within the mining area were compared with the simulated concentrations of the various migratory uranium forms. If the relative error between the simulated concentration and the measured concentration exceeds the third preset threshold, the hydrogeological parameters, solute transport parameters, or reaction kinetic parameters are adjusted and recalculated and optimized until the error meets the requirements. Based on the optimized simulation results, the migration paths, migration rates, and concentration decay patterns of uranium in the mining area's water were analyzed, clarifying the contribution percentage of each type of migratory uranium form to total uranium migration.

10. The numerical simulation method for determining the speciation and migration patterns of uranium in mining area water as described in claim 1, characterized in that, The hydrogeological data of the mining area includes, but is not limited to, the topography, lithology, aquifer distribution, groundwater level, permeability coefficient, porosity, and specific yield of the mining area; The basic water quality parameters of the water samples include, but are not limited to, pH value, Eh value, temperature, total dissolved solids, concentration of major cations, concentration of major anions, and total uranium content.

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