Method and system for detecting migration of rare earth elements in soil
By constructing leaching performance and vertical content characteristic values, and correcting the rare earth element content, the problem of vertical leaching of rare earth elements masking horizontal migration signals was solved by using the ADR diffusion-convection-reaction kinetic model and PCA analysis, thus achieving accuracy and reliability in rare earth element migration detection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XICHANG COLLEGE
- Filing Date
- 2026-05-13
- Publication Date
- 2026-06-09
AI Technical Summary
Vertical leaching of rare earth elements in soil can mask or dilute surface migration signals, leading to inaccurate migration detection results and making it difficult to accurately track and quantitatively characterize their horizontal migration features.
By constructing the leaching performance, vertical content characteristic value, and leaching effect influence of sampling points, the rare earth element content affected by leaching is corrected. Using the ADR diffusion-convection-reaction kinetic model and PCA principal component analysis, key environmental factors affecting rare earth migration are identified, and migration paths and risks are dynamically displayed.
Accurate analysis of the horizontal migration patterns of rare earth elements can correct for surface content deviations caused by leaching effects, providing accurate migration detection results and supporting ecological environment security and sustainable agricultural development.
Smart Images
Figure CN122171655A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of rare earth element migration detection technology, specifically to a method and system for detecting rare earth element migration in soil. Background Technology
[0002] Rare earth element (REE) migration detection in soil refers to a specialized monitoring technique that uses a series of sampling, analysis, and simulation methods to study the transformation of REE occurrence forms and spatial transport patterns at the solid-liquid-gas interface in soil, as well as the processes and influencing factors of REE migration and accumulation in groundwater and plants. Monitoring REE migration in soil can ensure ecological and environmental safety, support sustainable agricultural development, and improve soil environmental quality standards and regulatory systems.
[0003] Rare earth elements (REEs) exhibit low diffusion and convection rates in soil media, and primarily exist in adsorbed or complexed states, tightly bound to soil particles, organic matter, and mineral components. This limits their horizontal migration capacity, manifested as short migration distances and relatively gentle concentration gradient changes. Although horizontal migration of REEs in soil media is not significant, external hydrodynamic processes such as rainfall and irrigation can easily trigger vertical leaching, causing surface-enriched REEs to migrate vertically to subsurface and even deeper soil layers. This process can mask or dilute the surface horizontal migration signal, leading to lower values in REE migration detection results or misjudgments of migration trends. Consequently, it becomes difficult to accurately track and quantify the horizontal migration characteristics of REEs, failing to reflect their true migration patterns. Summary of the Invention
[0004] This invention provides a method and system for detecting the migration of rare earth elements in soil, to solve the problem that vertical leaching causes rare earth elements in soil to migrate downwards, which can mask or dilute the horizontal migration signal in the soil surface, leading to inaccurate detection results. The specific technical solution adopted is as follows: In a first aspect, one embodiment of the present invention provides a method for detecting the migration of rare earth elements in soil, the method comprising the following steps: The soil moisture at the sampling points, the rare earth element content at the sampling points, and the rare earth element content at different depths below the sampling points were collected. The differences in soil moisture and rare earth element content between the sampling point and all adjacent sampling points were analyzed to construct the leaching performance of the sampling point. The leaching performance was used to characterize the possibility that the abnormal rare earth content at the sampling point location was caused by the leaching effect. Based on the rare earth element content at all depths below the sampling point, a vertical content feature value is constructed for the sampling point. The vertical content feature value is used to characterize the vertical distribution characteristics of rare earth elements. Based on the difference in vertical content feature values between the sampling point and all adjacent sampling points, and the correlation between soil moisture at the sampling point and rare earth element content at different depths, the leaching effect influence degree of the sampling point is determined. The leaching effect influence degree is used to characterize the significance of the leaching effect on the location of the sampling point. Based on the leaching performance and rare earth element content of all adjacent sampling points, a reference value for the rare earth element content of the sampling point is constructed. The reference value is used to correct the rare earth element content of the sampling point affected by leaching. Combining the influence of leaching effect and rare earth element content of the sampling point, a migration correction value for the rare earth element content of the sampling point is determined. The migration detection of rare earth elements in the soil is completed based on the migration correction value.
[0005] Furthermore, the specific method for determining the leaching performance of the sampling points is as follows: Based on the differences in soil moisture and rare earth element content between the sampling point and all adjacent sampling points, the second adjacent average content and moisture-content difference of the sampling point are calculated. The leaching performance of the sampling points was positively correlated with the average content of the second adjacent sampling points and the humidity-content difference of the sampling points.
[0006] Furthermore, the specific method for determining the second adjacent average content is as follows: Any sampling point is designated as the target sampling point. Other sampling points directly adjacent to the target sampling point are designated as adjacent sampling points of the target sampling point. The average absolute value of the difference between the content of the same type of rare earth element at the target sampling point and all adjacent sampling points is designated as the first adjacent average content of the same type of rare earth element corresponding to the target sampling point. The average content of the first adjacent average content of all rare earth elements corresponding to the target sampling point is denoted as the second adjacent average content of the target sampling point.
[0007] Furthermore, the specific method for determining the humidity-content difference is as follows: The average soil moisture of all adjacent sampling points of a sampling point is recorded as the adjacent average soil moisture of the sampling point. The ratio of the absolute value of the difference between the soil moisture at the sampling point and the adjacent average soil moisture to the second adjacent average content of the sampling point is recorded as the first ratio of the sampling point. The absolute value of the difference between the first ratio of the sampling point and the number 1 is recorded as the first absolute value of the sampling point. The negative correlation result of the first absolute value of the sampling point is recorded as the humidity-content difference of the target sampling point.
[0008] Furthermore, the method for constructing the vertical content feature values of the sampling points is as follows: The depth corresponding to the maximum rare earth element content at all depths below the sampling point is recorded as the maximum content depth of the sampling point. The ratio of the range of rare earth element content at all depths below the sampling point to the maximum content depth of the sampling point is recorded as the second ratio of the sampling point. Calculate the vertical content characteristic value of the sampling point. The vertical content characteristic value of the sampling point is negatively correlated with the rare earth element content of the sampling point, and the vertical content characteristic value of the sampling point is positively correlated with the second ratio of the sampling point.
[0009] Furthermore, the method for determining the influence of the leaching effect at the sampling points is as follows: Calculate the vertical content difference characteristic value of the sampling point based on the difference between the vertical content characteristic values of the sampling point and all adjacent sampling points; The vertical migration correlation strength of the sampling points was calculated based on the correlation between soil moisture and rare earth element content at different depths. The positive correlation between the leaching performance of the sampling point and the correlation strength of vertical migration is denoted as the leaching effect influence of the sampling point.
[0010] Furthermore, the steps for determining the vertical migration association strength are as follows: Based on the soil moisture collected at different times, a soil moisture sequence for the sampling points is constructed. Based on the rare earth element content at different depths of the sampling points at the same time, a content sequence of the sampling points at the same time is constructed. The mean value of the correlation between the soil moisture sequence at the sampling point and the content sequence at all times corresponding to the soil moisture sequence is denoted as the vertical migration correlation strength of the sampling point.
[0011] Furthermore, the specific method for determining the reference value of rare earth element content at the sampling point is as follows: The sum of the products of the leaching performance and the rare earth element content of all adjacent sampling points of the target sampling point is recorded as the weighted rare earth element content of the target sampling point. The sum of the leaching performance of all adjacent sampling points of the target sampling point is recorded as the cumulative weight of the target sampling point; The ratio of the weighted rare earth element content of the sampling point to the cumulative weight is recorded as the reference value of the rare earth element content of the sampling point.
[0012] Furthermore, the rare earth element content migration correction value of the sampling point is the result of weighted summation of the rare earth element content reference value and the rare earth element content of the sampling point using the leaching effect influence degree of the sampling point.
[0013] Secondly, embodiments of the present invention also provide a rare earth element migration detection system in soil, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.
[0014] The beneficial effects of this invention are: This application first evaluates the likelihood that the abnormal rare earth element content at a sampling point is caused by leaching based on the differences in soil moisture and rare earth element content between the sampling point and all adjacent sampling points. It then obtains the leaching performance of the sampling point; the greater the leaching performance, the more likely the abnormal rare earth element content at that point is caused by leaching caused by rainwater infiltration. To clarify the true spatial distribution pattern of horizontal migration of rare earth elements in the soil, it is necessary to effectively distinguish between vertical migration and diffusion caused by hydrodynamic processes, and horizontal migration dominated by mechanisms such as adsorption-desorption. Specifically, this is done based on the differences in vertical content characteristic values between the sampling point and all adjacent sampling points, the soil moisture at the sampling point, and the rare earth element content at different depths. The correlation was evaluated to assess the significance of the leaching effect on the sampling point location and to obtain the leaching effect influence of the sampling point. In order to accurately analyze the horizontal migration law of rare earth elements and correct the surface content deviation caused by the leaching effect, the leaching performance and rare earth element content of all adjacent sampling points of the sampling point, as well as the leaching effect influence of the sampling point, were used to correct the sampling point data affected by leaching, determine the rare earth element content migration correction value of the sampling point, and complete the rare earth element migration detection in the soil based on the rare earth element content migration correction value. This solves the problem that vertical leaching causes rare earth elements in the soil to move downwards, which may mask or dilute the horizontal migration signal of the soil surface, resulting in inaccurate rare earth element migration detection results in the soil. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 This is a schematic flowchart of a method for detecting the migration of rare earth elements in soil, provided in one embodiment of the present invention. Detailed Implementation
[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] Please see Figure 1 The diagram illustrates a flowchart of a method for detecting the migration of rare earth elements in soil according to an embodiment of the present invention. The method includes the following steps: Step S001: Collect soil moisture, rare earth element content at the sampling point, and rare earth element content at different depths below the sampling point.
[0019] The soil surface is divided into grids, and the geometric center of each grid is used as a sampling point. Soil moisture and the content of each rare earth element are collected at each sampling point. Sampling is carried out at the sampling points in layers according to a preset depth, and the content of each rare earth element at each sampling location is collected.
[0020] A portable volumetric moisture probe was used to perform insertion measurements at sampling points to obtain soil moisture content. The insertion depth should be greater than or equal to 0 cm and less than or equal to 5 cm. At each sampling point, a stainless steel soil sampler was used to collect soil samples from the surface soil. These samples were independently sealed and preserved according to the sampling point number to avoid sample mixing or metal contamination. In the laboratory, the collected soil samples were air-dried, impurities removed, and ground. The soil samples were sieved through a 2 mm sieve and partially pulverized to less than 63 μm. The processed soil samples were then subjected to acid digestion using microwave digestion to remove impurities from the soil. The rare earth elements were completely dissolved, and quantitative analysis was performed using ICP-MS to obtain the content of each rare earth element at the sampling point. At each sampling location, soil samples were collected layer by layer using a corer according to a preset stratification to avoid mixing of upper and lower soil layers. Each soil sample was individually numbered and sealed for preservation. During the sampling process, the sampler had to be kept clean, and parallel and blank samples were set up in the field to monitor potential contamination. In the laboratory, soil samples from all depths were dried, sieved, crushed, and acid-digested. Quantitative analysis was performed using ICP-MS to obtain the content of each rare earth element at each depth of each sampling location. In this embodiment, when collecting soil samples layer by layer, layers greater than or equal to 0 cm and less than or equal to 10 cm were used as one layer, layers greater than 10 cm and less than or equal to 30 cm were used as another layer, and layers greater than 30 cm and less than or equal to 30 cm were used as yet another layer, for a total of three soil layers. The specific depth was selected by those skilled in the art based on the corresponding soil layer.
[0021] The rare earth element content and soil moisture were denoised and normalized to remove outliers and eliminate dimensional differences. Blank samples, parallel samples, and standard substances were used as references to correct experimental measurement errors, ensuring the accuracy and reliability of the data. The denoising, normalization, and experimental measurement error correction are all well-known techniques and will not be elaborated further.
[0022] Thus, the soil moisture at the sampling point, the rare earth element content at the sampling point, and the rare earth element content at different depths below the sampling point were obtained.
[0023] Step S002: Analyze the differences in soil moisture and rare earth element content between the sampling point and all adjacent sampling points, and construct the leaching performance of the sampling point. The leaching performance is used to characterize the possibility that the abnormal rare earth content at the sampling point location is caused by the leaching effect.
[0024] The migration of rare earth elements (REEs) in soil is controlled by geochemical properties such as adsorption and complexation, and is also strongly dependent on water movement characteristics. Among these factors, leaching caused by rainfall, irrigation, or groundwater seepage significantly alters the distribution pattern of REEs in both surface and deep layers. By analyzing changes in soil surface moisture, areas prone to leaching can be predicted in advance. In the analysis of horizontal REE migration, the vertical interference of leaching effects can be identified, avoiding underestimation or misjudgment of horizontal migration, ensuring the authenticity and reliability of the extracted migration patterns, and ultimately achieving accurate characterization of REE migration behavior in complex soil environments.
[0025] When rainwater or surface water infiltrates into the soil, the descending water preferentially carries water-soluble and exchangeable rare earth elements (REEs) that are more easily migrated from the surface, resulting in a significant decrease in surface REE content and a corresponding increase in deep-seated concentrations. Analyzing the differences in humidity and REE content within the spatial neighborhood of a sampling point can help determine the cause of REE anomalies at that point. Specifically, if the surface humidity at the sampling point is significantly higher than that at surrounding points, and the REE content decreases significantly at the same time, it indicates that the REE anomaly at the sampling point is more likely caused by leaching effects triggered by rainwater infiltration.
[0026] Any sampling point is designated as the target sampling point. All other sampling points directly adjacent to the target sampling point are designated as adjacent sampling points of the target sampling point. The average soil moisture of all adjacent sampling points of the target sampling point is designated as the adjacent average soil moisture of the target sampling point. The average absolute value of the difference between the content of the same type of rare earth element at the target sampling point and all adjacent sampling points is designated as the first adjacent average content of the same type of rare earth element at the target sampling point. The average first adjacent average content of all types of rare earth elements at the target sampling point is designated as the second adjacent average content of the target sampling point. The ratio of the calculated absolute value of the difference between the soil moisture of the target sampling point and the adjacent average soil moisture to the second adjacent average content of the target sampling point is designated as the first ratio of the target sampling point. The absolute value of the difference between the first ratio of the target sampling point and the number 1 is designated as the first absolute value of the target sampling point. The negative correlation result of the first absolute value of the target sampling point is designated as the moisture-content difference of the target sampling point.
[0027] In the process of calculating the ratio, in order to avoid the denominator being zero, a preset value needs to be added to the denominator. In this example, the preset value is 0.01.
[0028] It is understood that negative correlation processing is applied to the first absolute value of the target sampling point, ensuring a negative correlation between the first absolute value of the target sampling point and the humidity-content difference of the target sampling point. It is understood that the negative correlation in this application refers to the relationship between the independent variable and the dependent variable, where the independent variable is the first absolute value of the target sampling point, and the dependent variable is the humidity-content difference of the target sampling point. A negative correlation means that the dependent variable decreases (increases) as the independent variable increases (decreases), and can be an inverse relationship, a subtraction relationship, etc.
[0029] Preferably, as an embodiment of this application, the first absolute value of the target sampling point is used as the exponent value of an exponential function with the natural constant as the base, and the calculation result of the exponential function is recorded as the humidity-content difference of the target sampling point.
[0030] The leaching performance of a sampling point is determined based on the average content of the second adjacent sampling point and the humidity-content difference. The leaching performance of the sampling point is positively correlated with the average content of the second adjacent sampling point and the humidity-content difference of the sampling point.
[0031] It is understood that the positive and negative correlations in this application refer to the relationship between the independent and dependent variables. A positive correlation means that the dependent variable increases (decreases) as the independent variable increases (decreases), and can be an additive or multiplicative relationship. A negative correlation means that the dependent variable decreases (increases) as the independent variable increases (decreases), and can be an inverse relationship or a subtractive relationship.
[0032] Some other embodiments of this application may be that the product of the second adjacent average content of the sampling point and the humidity-content difference is recorded as the leaching performance of the sampling point.
[0033] The greater the leaching performance at the sampling point, the more likely the abnormal rare earth content at the sampling point is caused by the leaching effect triggered by rainwater infiltration.
[0034] At this point, the leaching performance of the sampling points is obtained.
[0035] Step S003: Based on the rare earth element content at all depths below the sampling point, construct the vertical content feature value of the sampling point. The vertical content feature value is used to characterize the vertical distribution characteristics of rare earth elements. Based on the difference in vertical content feature values between the sampling point and all adjacent sampling points, and the correlation between soil moisture at the sampling point and rare earth element content at different depths, determine the leaching effect influence degree of the sampling point. The leaching effect influence degree is used to characterize the significance of the leaching effect affecting the location of the sampling point.
[0036] To clarify the true spatial distribution patterns of horizontal migration of rare earth elements (REEs) in soil, it is necessary to effectively distinguish between vertical migration and diffusion induced by hydrodynamic processes, and horizontal migration dominated by mechanisms such as adsorption-desorption. It is important to note that leaching can cause surface REEs to be carried downwards by rainwater or irrigation water, weakening or even masking their original horizontal migration signals. Relying solely on surface sampling data can easily lead to underestimation of migration intensity or misjudgment of direction. Therefore, it is necessary to analyze the interference effect of leaching on the horizontal migration of REEs, establish the coupling relationship between vertical leaching and horizontal diffusion, and quantify its impact on REE content to reconstruct the true horizontal migration characteristics at the sampling location.
[0037] The typical characteristic of leaching in the vertical distribution of rare earth elements (REEs) is a decrease in content at the surface and enrichment at deeper layers. When leaching occurs, rainwater or seepage water carries mobile REEs from the surface into deeper soil layers, leading to a significant decrease in surface REE content. Simultaneously, the REE content at multiple depths shows a relative increase or a significantly larger range of variation. If the REE content at different depths of a sampling point exhibits a significantly lower level at the surface and a larger range of variation at deeper layers, it can be determined that the sampling point is likely located in a typical vertical distribution pattern dominated by the leaching effect.
[0038] The depth corresponding to the maximum rare earth element content at all depths below the sampling point is denoted as the maximum content depth of the sampling point. The ratio of the range of rare earth element content at all depths below the sampling point to the maximum content depth of the sampling point is denoted as the second ratio of the sampling point. Based on the second ratio of the sampling point and the rare earth element content of the sampling point, the vertical content characteristic value of the sampling point is calculated. The vertical content characteristic value of the sampling point is negatively correlated with the rare earth element content of the sampling point, and the vertical content characteristic value of the sampling point is positively correlated with the second ratio of the sampling point.
[0039] Some other embodiments of this application may be that the product of the negative correlation processing result of the rare earth element content of the sampling point and the second ratio of the sampling point is recorded as the vertical content characteristic value of the sampling point.
[0040] Preferably, as an embodiment of this application, the rare earth element content of the sampling point is taken as the exponent value of an exponential function with the natural constant as the base, and the calculation result of the exponential function is recorded as the first power value of the sampling point. The first power value of the sampling point is the negative correlation processing result of the rare earth element content of the sampling point.
[0041] The vertical content difference characteristic value of the target sampling point is calculated based on the difference between the vertical content characteristic values of the target sampling point and all adjacent sampling points.
[0042] The mean of the vertical content characteristic values of all adjacent sampling points of the target sampling point is recorded as the adjacent vertical content characteristic value of the target sampling point, and the absolute value of the difference between the vertical content characteristic value of the target sampling point and the adjacent vertical content characteristic values is recorded as the vertical content difference characteristic value of the target sampling point.
[0043] The same method can be used to obtain the vertical content difference feature value of any sampling point.
[0044] Higher soil surface moisture indicates more thorough infiltration of rainfall or surface water, and a greater likelihood of leaching. Joint analysis of soil surface moisture and vertical rare earth element (REE) distribution characteristics allows for more reliable identification of leaching signals. When soil moisture increases, leaching is more likely to occur, and surface REEs migrate more easily downwards with water, resulting in more significant changes in their content across the vertical profile. Based on this analysis, the correlation between soil surface moisture and vertical REE migration is further analyzed.
[0045] Based on the soil moisture collected at different times, a soil moisture sequence for the sampling point is constructed. Based on the rare earth element content at different depths at the same time, a content sequence for the sampling point at the same time is constructed. The mean of the correlation between the soil moisture sequence of the sampling point and the content sequence at all times corresponding to the soil moisture sequence is denoted as the vertical migration correlation strength of the sampling point.
[0046] In this embodiment, soil moisture at sampling points collected at 20 consecutive time points is selected to construct a soil moisture sequence for the sampling points. In the content sequence of the sampling points, the rare earth element content at different depths is sorted from smallest to largest according to the depth corresponding to the rare earth element content. In this embodiment, Pearson correlation coefficient is used to evaluate the correlation of the sequence. Based on achieving the purpose of measuring the correlation between two sequences, the implementer may use other methods in the prior art, such as Spearman correlation coefficient, to obtain the correlation between two sequences. This application does not impose any special restrictions.
[0047] Soil surface moisture reflects the probability of leaching, which significantly affects the vertical migration of rare earth elements (REEs). By analyzing the correlation between surface moisture and the vertical distribution of REE content, the location of leaching interference can be accurately identified. Specifically, the criteria are: if the vertical REE content distribution at a sampling point differs significantly from other sampling points in its spatial neighborhood, and the vertical distribution at other locations in the neighborhood shows a high degree of regularity and consistency, then the abnormal REE distribution at that sampling point can be determined to be mainly caused by the leaching effect. Based on this, the degree to which the REE content at each sampling point is affected by the leaching effect can be further obtained.
[0048] The positive correlation between the leaching performance of the sampling point and the correlation strength of vertical migration is denoted as the leaching effect influence of the sampling point.
[0049] It is understood that a positive correlation is applied to the leaching performance and vertical migration correlation strength of the sampling points, ensuring that both the leaching performance and vertical migration correlation strength of the sampling points are positively correlated with the leaching effect influence of the sampling points. It is understood that the positive correlation in this application refers to the relationship between the independent and dependent variables, where the independent variable is the leaching performance and vertical migration correlation strength of the sampling points, and the dependent variable is the leaching effect influence of the sampling points. A positive correlation means that the dependent variable increases (decreases) as the independent variable increases (decreases), and can be an additive or multiplicative relationship.
[0050] Preferably, as an embodiment of this application, the normalized value of the product of the leaching performance of the sampling point and the vertical migration correlation strength is denoted as the leaching effect influence of the sampling point.
[0051] In this embodiment, the tanh function is used to calculate the normalized value. The tanh function is a well-known technique and will not be described in detail here. As other implementation methods, implementers can use other methods of the prior art, such as the sigmoid function.
[0052] At this point, the influence of the leaching effect at the sampling point is obtained.
[0053] Step S004: Based on the leaching performance and rare earth element content of all adjacent sampling points, construct a reference value for the rare earth element content of the sampling point. The reference value is used to correct the rare earth element content of the sampling point affected by leaching. Combining the influence of leaching effect and rare earth element content of the sampling point, determine the migration correction value of rare earth element content of the sampling point. Complete the migration detection of rare earth elements in the soil based on the migration correction value of rare earth element content.
[0054] The actual horizontal migration of rare earth elements (REEs) in soil is significantly affected by hydrodynamic processes such as rainfall and irrigation. Without correction for leaching interference, the detection results cannot accurately reflect the true horizontal migration patterns. The leaching effect causes surface REEs to migrate downwards with water, resulting in an abnormally low REE content at the surface. This can easily be misinterpreted as weakened migration due to horizontal diffusion or adsorption, leading to incorrect inferences about the migration rate, direction, and range. Therefore, leaching correction is necessary based on the degree to which the REE content at each sampling point is affected by the leaching effect, in order to distinguish the contribution of vertical and horizontal migration and eliminate migration errors caused by vertical leaching.
[0055] To accurately analyze the horizontal migration patterns of rare earth elements, it is necessary to correct for surface content deviations caused by leaching. Specifically, the surface rare earth element content of other sampling points within the spatial neighborhood of a sampling point can be used as a reference. When the vertical distribution of rare earth elements in the neighborhood of sampling points shows low leaching interference and strong regularity, its surface content can be used as a reliable reference value to correct the sampling point data affected by leaching.
[0056] The sum of the products of leaching performance and rare earth element content of all adjacent sampling points of the target sampling point is recorded as the weighted rare earth element content of the target sampling point. The sum of the leaching performance of all adjacent sampling points of the target sampling point is recorded as the cumulative weight of the target sampling point. The cumulative weight of any sampling point can be obtained in the same way. The ratio of the weighted rare earth element content of the sampling point to the cumulative weight is recorded as the reference value of the rare earth element content of the sampling point.
[0057] In the process of calculating the ratio, in order to avoid the denominator being zero, a preset value needs to be added to the denominator. In this example, the preset value is 0.01.
[0058] It is understandable that for each type of rare earth element, there is a reference value for the rare earth element content at a sampling point.
[0059] Based on the degree of influence of leaching effect on the rare earth element content of each sampling point, and combined with the rare earth element content in its spatial neighborhood, the rare earth element content of the sampling point is corrected. If the sampling point is significantly affected by leaching interference, resulting in a low or abnormal surface rare earth content, a more significant correction needs to be implemented based on the content data of sampling points with low leaching interference in the neighborhood, ultimately obtaining the migration detection correction value of the rare earth element content of each sampling point.
[0060] The influence of leaching effect at the sampling point is used as the weight of the reference value of rare earth element content at the sampling point. The difference between the number 1 and the influence of leaching effect at the sampling point is used as the weight of rare earth element content at the sampling point. The weighted sum is then calculated, and the result of the weighted sum is recorded as the migration correction value of rare earth element content at the sampling point.
[0061] The formula for calculating the rare earth element content migration correction value at the sampling point is as follows: Indicates the first Migration correction values for rare earth element content at each sampling point; Indicates the first The influence of leaching effect at each sampling point; Indicates the first Rare earth element content at each sampling point; Indicates the first Reference values for rare earth element content at each sampling point.
[0062] It is understandable that for each type of rare earth element, there is a rare earth element content migration correction value for a sampling point.
[0063] Based on the migration correction values of rare earth element content at all sampling points, an ADR diffusion-convection-reaction kinetic model was constructed. Using this model, parameters such as horizontal migration coefficient, migration rate, and speciation rate were obtained. Principal component analysis (PCA) was then used to identify key environmental factors influencing rare earth migration. Furthermore, a risk index method was employed to classify and visualize the risks of different soil regions. This dynamically and quantitatively reveals the migration pathways, migration rates, and potential environmental risks of rare earth elements in the soil, providing a scientific basis for soil environmental management and pollution control.
[0064] It is understood that the diffusion-convection-reaction kinetic model is used to describe the migration and speciation process of rare earth elements in soil. It can comprehensively consider the horizontal diffusion, convective migration, and transformation kinetics between exchangeable, water-soluble and stationary states of rare earth elements, and describe the concentration change law of each speciation by establishing governing equations.
[0065] In this embodiment, the PSO particle swarm optimization algorithm is used to solve the diffusion-convection-reaction kinetic model. The PSO particle swarm optimization algorithm simulates the iterative search of "particles" in the parameter space to achieve the optimal match between the model prediction value and the corrected rare earth content.
[0066] Among them, the construction of the ADR diffusion-convection-reaction kinetic model, PCA principal component analysis, and risk index method are all well-known techniques and will not be elaborated further.
[0067] This completes the detection of rare earth element migration in the soil.
[0068] Based on the same inventive concept as the above methods, embodiments of the present invention also provide a rare earth element migration detection system in soil, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above methods for detecting rare earth element migration in soil.
[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for detecting the migration of rare earth elements in soil, characterized in that, The method includes the following steps: The soil moisture at the sampling points, the rare earth element content at the sampling points, and the rare earth element content at different depths below the sampling points were collected. The differences in soil moisture and rare earth element content between the sampling point and all adjacent sampling points were analyzed to construct the leaching performance of the sampling point. The leaching performance was used to characterize the possibility that the abnormal rare earth content at the sampling point location was caused by the leaching effect. Based on the rare earth element content at all depths below the sampling point, a vertical content feature value is constructed for the sampling point. The vertical content feature value is used to characterize the vertical distribution characteristics of rare earth elements. Based on the difference in vertical content feature values between the sampling point and all adjacent sampling points, and the correlation between soil moisture at the sampling point and rare earth element content at different depths, the leaching effect influence degree of the sampling point is determined. The leaching effect influence degree is used to characterize the significance of the leaching effect on the location of the sampling point. Based on the leaching performance and rare earth element content of all adjacent sampling points, a reference value for the rare earth element content of the sampling point is constructed. The reference value is used to correct the rare earth element content of the sampling point affected by leaching. Combining the influence of leaching effect and rare earth element content of the sampling point, a migration correction value for the rare earth element content of the sampling point is determined. The migration detection of rare earth elements in the soil is completed based on the migration correction value.
2. The method for detecting the migration of rare earth elements in soil according to claim 1, characterized in that, The specific method for determining the leaching performance of the sampling points is as follows: Based on the differences in soil moisture and rare earth element content between the sampling point and all adjacent sampling points, the second adjacent average content and moisture-content difference of the sampling point are calculated. The leaching performance of the sampling points was positively correlated with the average content of the second adjacent sampling points and the humidity-content difference of the sampling points, respectively. The specific method for determining the second adjacent average content is as follows: Any sampling point is designated as the target sampling point. Other sampling points directly adjacent to the target sampling point are designated as adjacent sampling points of the target sampling point. The average absolute value of the difference between the content of the same type of rare earth element at the target sampling point and all adjacent sampling points is designated as the first adjacent average content of the same type of rare earth element corresponding to the target sampling point. The average content of the first adjacent average content of all rare earth elements corresponding to the target sampling point is denoted as the second adjacent average content of the target sampling point. The specific method for determining the humidity-content difference is as follows: The average soil moisture of all adjacent sampling points of a sampling point is recorded as the adjacent average soil moisture of the sampling point. The ratio of the absolute value of the difference between the soil moisture at the sampling point and the adjacent average soil moisture to the second adjacent average content of the sampling point is recorded as the first ratio of the sampling point. The absolute value of the difference between the first ratio of the sampling point and the number 1 is recorded as the first absolute value of the sampling point. The negative correlation result of the first absolute value of the sampling point is recorded as the humidity-content difference of the target sampling point.
3. The method for detecting the migration of rare earth elements in soil according to claim 1, characterized in that, The method for constructing the vertical content feature values of the sampling points is as follows: The depth corresponding to the maximum rare earth element content at all depths below the sampling point is recorded as the maximum content depth of the sampling point. The ratio of the range of rare earth element content at all depths below the sampling point to the maximum content depth of the sampling point is recorded as the second ratio of the sampling point. Calculate the vertical content characteristic value of the sampling point. The vertical content characteristic value of the sampling point is negatively correlated with the rare earth element content of the sampling point, and the vertical content characteristic value of the sampling point is positively correlated with the second ratio of the sampling point.
4. The method for detecting the migration of rare earth elements in soil according to claim 1, characterized in that, The method for determining the influence of the leaching effect at the sampling points is as follows: Calculate the vertical content difference characteristic value of the sampling point based on the difference between the vertical content characteristic values of the sampling point and all adjacent sampling points; The vertical migration correlation strength of the sampling points was calculated based on the correlation between soil moisture and rare earth element content at different depths. The positive correlation between the leaching performance of the sampling point and the correlation strength of vertical migration is denoted as the leaching effect influence of the sampling point.
5. The method for detecting the migration of rare earth elements in soil according to claim 4, characterized in that, The steps for determining the vertical migration correlation strength are as follows: Based on the soil moisture collected at different times, a soil moisture sequence for the sampling points is constructed. Based on the rare earth element content at different depths of the sampling points at the same time, a content sequence of the sampling points at the same time is constructed. The mean value of the correlation between the soil moisture sequence at the sampling point and the content sequence at all times corresponding to the soil moisture sequence is denoted as the vertical migration correlation strength of the sampling point.
6. The method for detecting the migration of rare earth elements in soil according to claim 2, characterized in that, The specific method for determining the reference value of rare earth element content at the sampling point is as follows: The sum of the products of the leaching performance and the rare earth element content of all adjacent sampling points of the target sampling point is recorded as the weighted rare earth element content of the target sampling point. The sum of the leaching performance of all adjacent sampling points of the target sampling point is recorded as the cumulative weight of the target sampling point; The ratio of the weighted rare earth element content of the sampling point to the cumulative weight is recorded as the reference value of the rare earth element content of the sampling point.
7. The method for detecting the migration of rare earth elements in soil according to claim 1, characterized in that, The migration correction value of rare earth element content at the sampling point is the result of weighted summation of the reference value and the rare earth element content at the sampling point using the leaching effect influence degree of the sampling point.
8. A system for detecting the migration of rare earth elements in soil, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as claimed in any one of claims 1-7.