Method and system for determining relationship between underground water burial depth and soil ion distribution

Abstract

The invention relates to a method and a system for determining a relationship between underground water burial depth and soil ion distribution. The method comprises the following steps: collecting a soil sample of a target area; measuring the soil water content, the pH value, the conductivity EC value, the TDS value and the content of eight ions of the soil sample, and determining the soil ion type and the main ion source of the soil sample; analyzing the profile change rule of the soil water content, the pH value, the EC value, the TDS value and the eight ion contents, and the proportion and the ratio of soil ions; and performing multivariate statistical analysis based on the profile change rule and the proportion and ratio of the soil ions to obtain the relationship between the underground water burial depth and the soil moisture, the relationship between the underground water burial depth and the salinity, and the relationship between the underground water burial depth and the content of the soil ions and the ratio and composition of the representative ions. According to the method, accurate analysis of the relationship between the groundwater burial depth and the soil ion distribution is realized by integrating multiple technical means, and technical support is provided for reasonable development of groundwater resources and soil environment protection.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogeology, and particularly to a method and system for determining the relationship between groundwater depth and soil ion distribution. Background Art

[0002] Groundwater depth is an important factor affecting the soil environment. Especially in arid and semi-arid regions, the groundwater depth directly affects the soil moisture, ion concentration, and the accumulation and distribution characteristics of salts. The dynamic changes of groundwater affect the vertical migration of ions in the soil profile, and the process of ion accumulation or leaching in the soil will further affect the physical and chemical properties of the soil and the growth environment of crops. Especially in the process of agricultural production, human activities such as irrigation and drainage will also have a significant impact on the groundwater depth and soil ion distribution. Therefore, in the fields of agriculture, environmental protection, urban planning, etc., it is of great significance to accurately master the relationship between groundwater depth and soil ion distribution.

[0003] At present, the following methods are mainly used in the research on the relationship between groundwater depth and soil ion distribution:

[0004] (1) Field investigation method: Through a large number of geological and hydrogeological investigations in the research area, the groundwater depth and soil ion distribution are understood. However, this method is time-consuming and laborious, and limited by human and material resources, it is difficult to achieve large-scale and high-precision research.

[0005] (2) Numerical simulation method: Based on a hydrogeological model, by simulating the groundwater flow and soil ion migration processes, the relationship between groundwater depth and soil ion distribution is analyzed. However, this method is highly dependent on parameters, and the model is complex, and the calculation process takes a long time.

[0006] (3) Remote sensing technology method: Through remote sensing images, the groundwater depth and soil ion distribution information in the research area are obtained. Although remote sensing technology has the characteristics of rapidity and large scale, its accuracy is limited by the remote sensing data itself and the accuracy of the inversion model.

[0007] (4) Statistical analysis method: Using historical monitoring data, methods such as correlation analysis and regression analysis are used to explore the statistical relationship between groundwater depth and soil ion distribution. However, this method is limited by the quantity and quality of the monitoring data, and it is difficult to reflect the real-time changes of groundwater depth and soil ion distribution.

[0008] In summary, the existing methods have certain limitations in the research on the relationship between groundwater depth and soil ion distribution. Therefore, it is necessary to study a new method to accurately and quickly determine the relationship between groundwater depth and soil ion distribution. Summary of the Invention

[0009] The object of the present invention is to overcome the limitations of the prior art in accurately depicting the relationship between groundwater depth and soil ion distribution, such as time-consuming, laborious, complex models, and strong dependence on parameters. A method and system for determining the relationship between groundwater depth and soil ion distribution are provided. By integrating various technical means, accurate analysis of the relationship between groundwater depth and soil ion distribution is achieved, providing technical support for the rational development of groundwater resources and soil environmental protection.

[0010] To achieve the above object, on the one hand, the present invention provides a method for determining the relationship between groundwater depth and soil ion distribution, including:

[0011] Collecting soil samples in the target area;

[0012] Measuring the soil water content, pH value, electrical conductivity EC value, TDS value and the content of eight major ions of the soil sample, and determining the soil ion type and the main source of ions of the soil sample;

[0013] Analyzing the profile change rules of the soil water content, pH value, EC value, TDS value and the content of eight major ions, as well as the proportion and ratio of soil ions;

[0014] Conducting multivariate statistical analysis based on the profile change rules and the proportion and ratio of soil ions to obtain the relationship between groundwater depth and soil moisture, the relationship between groundwater depth and salinity, and the relationship between groundwater depth and soil ion content, representative ion ratio and composition.

[0015] Optionally, collecting the soil samples in the target area includes:

[0016] Sampling at multiple depths of the soil profile under different groundwater depth conditions in the target area at a preset distance interval to obtain the soil samples.

[0017] Optionally, an inductively coupled plasma spectrometer, including a Dionex ion chromatograph, is used to measure the soil water content, pH value, electrical conductivity EC value, TDS value and the content of eight major ions of the soil sample.

[0018] Optionally, a Piper ternary diagram is used to determine the soil ion type of the soil sample. By analyzing the ratio of anions and cations in the soil sample, the ions in the soil are determined;

[0019] A Gibbs diagram is used to determine the main source of ions. By comparing the positions of data points of different soil samples on the Gibbs diagram, the influencing factors of soil hydrochemistry are determined.

[0020] Optionally, the coefficient of variation and variance analysis are used to analyze the profile change rules of the soil water content, pH value, EC value, TDS value and the content of eight major ions.

[0021] Optionally, analyzing the proportion and ratio of the soil ions includes calculating the sodium adsorption ratio and the ratio of chloride ions to sulfate ions, which are used to evaluate the degree of soil salinization and leaching degree.

[0022] Optionally, the multivariate statistical analysis includes principal component analysis (PCA), hierarchical clustering analysis (HCA), and correlation analysis, which are used for the correlation between the groundwater depth and soil ion distribution, the correlation between ions, and the correlation between ion distributions in different profiles.

[0023] On the other hand, the present invention also provides a determination system for the relationship between groundwater depth and soil ion distribution, including:

[0024] A sample collection module, which is used to collect soil samples in the target area;

[0025] A content determination module, which is used to determine the soil water content, pH value, electrical conductivity (EC) value, total dissolved solids (TDS) value, and the content of eight major ions in the soil sample;

[0026] An ion determination module, which is used to determine the soil ion type and the main source of ions in the soil sample;

[0027] A law analysis module, which is used to analyze the profile change laws of the soil water content, pH value, EC value, TDS value, and the content of eight major ions, as well as the proportion and ratio of soil ions;

[0028] A distribution analysis module, which is used to perform multivariate statistical analysis based on the profile change laws and the proportion and ratio of soil ions, and obtain the relationship between groundwater depth and soil moisture, the relationship between groundwater depth and salinity, and the relationship between groundwater depth and soil ion content, representative ion ratio, and composition.

[0029] The beneficial effects of the present invention are as follows:

[0030] The present invention uses traditional hydrochemical methods combined with methods such as soil ion proportion analysis, variance analysis, principal component analysis (PCA), hierarchical clustering analysis (HCA), and correlation analysis to analyze the relationship between groundwater depth and soil ion distribution, and can quantitatively analyze the change law of soil ion distribution with groundwater depth and ion migration law. It solves the limitations in the prior art such as time-consuming, laborious, complex models, and strong dependence on parameters. Description of the Drawings

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0032] Figure 1 Flow chart of a method for determining the relationship between groundwater depth and soil ion distribution according to an embodiment of the present invention;

[0033] Figure 2 Piper ternary diagram of the soil profile of the Institute of Water Conservancy Science according to an embodiment of the present invention;

[0034] Figure 3 Gibbs diagram of the soil profile of the Institute of Water Conservancy Science according to an embodiment of the present invention;

[0035] Figure 4 ANOVA analysis diagram of each variable according to an embodiment of the present invention;

[0036] Figure 5 PCA loading diagram and PCA score scatter plot according to an embodiment of the present invention;

[0037] Figure 6 Schematic diagram of the clustering clusters of the Institute of Water Conservancy Science and Puhui Farm below the isospecies line according to an embodiment of the present invention. Detailed implementation manners

[0038] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0039] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0040] On the one hand, this embodiment provides a method for determining the relationship between groundwater depth and soil ion distribution, as Figure 1 shown, including:

[0041] Collect soil samples in the target area;

[0042] Measure the soil water content, pH value, electrical conductivity EC value, TDS value, and the content of eight major ions of the soil sample, and determine the soil ion type and the main source of ions of the soil sample;

[0043] Analyze the profile change laws of the soil water content, pH value, EC value, TDS value, and the content of eight major ions, as well as the proportion and ratio of soil ions;

[0044] Based on the profile change law, the proportion and ratio of soil ions, multivariate statistical analysis is carried out to obtain the relationships between the groundwater depth and soil moisture, between the groundwater depth and salinity, and between the groundwater depth and soil ion content, representative ion ratios and compositions.

[0045] Specifically, in view of the limitations of the prior art in accurately depicting the relationship between groundwater depth and soil ion distribution, such as time-consuming, laborious, complex models, and strong dependence on parameters, this embodiment provides a method for determining the relationship between groundwater depth and soil ion distribution. By integrating various technical means, accurate analysis of the relationship between groundwater depth and soil ion distribution is achieved, providing technical support for the rational development of groundwater resources and soil environmental protection.

[0046] Furthermore, the collection of soil samples in the target area includes:

[0047] At multiple depths of the soil profile under different groundwater depth conditions in the target area, sampling is carried out at preset intervals to obtain the soil samples.

[0048] Specifically, the collection of soil samples in this embodiment for the target area includes: collecting soil profiles at multiple different groundwater depths, and sampling each profile according to depth. For example, sampling is carried out every 10 cm or 20 cm, and soil samples of several meters can be taken to discuss the variation law of soil ion distribution, etc. with depth.

[0049] Furthermore, an inductively coupled plasma spectrometer, including a Dionex ion chromatograph, is used to measure the soil water content, pH value, conductivity EC value, TDS value and the content of eight major ions in the soil samples.

[0050] Specifically, during the sampling process in this embodiment, a time domain reflectometer (TDR) is used to measure the soil water content. The collected soil samples are immediately sealed in plastic bags for subsequent laboratory tests.

[0051] Before the experimental test, the soil samples need to be air-dried naturally and passed through a 1 mm sieve. In the laboratory, a inductively coupled plasma spectrometer, including a Dionex ion chromatograph, is used to measure the pH value, EC value, TDS value and the content of eight major ions in the soil samples.

[0052] Furthermore, a Piper ternary diagram is used to determine the types of soil ions in the soil samples. By analyzing the ratio of anions and cations in the soil samples, the ions in the soil are determined.

[0053] A Gibbs diagram is used to determine the main sources of ions. By comparing the positions of data points of different soil samples on the Gibbs diagram, the influencing factors of soil hydrochemistry are determined.

[0054] Specifically, in this embodiment, traditional soil hydrochemical analysis is carried out using Piper ternary diagrams, Gibbs diagrams, etc. to determine the soil hydrochemical composition and ion sources, etc.

[0055] The Piper diagram is a classic tool for showing the relative proportions of major cations and anions in natural water. It consists of two triangles and a rhombus: The left triangle represents the relationship among three major cations (Na + +K + , Ca 2+ , Mg 2+ ). The right triangle represents the relationship among three major anions (Cl - , HCO 3 - , SO 4 2- ). The central rhombus connects the left and right triangles and is used to classify water samples. The position of each sample point reflects its chemical characteristics, and different types of water sources or influencing factors will form specific distribution patterns on the diagram.

[0056] The Gibbs diagram helps to understand the main mechanisms controlling hydrochemistry, namely rock weathering, atmospheric precipitation or evaporation concentration. This diagram is based on the relationship between TDS (total dissolved solids) and Cl - concentration to distinguish the above three main forces. By comparing the positions of the actually measured data points on the Gibbs diagram, it can be inferred which processes make important contributions to soil hydrochemistry.

[0057] Furthermore, the coefficient of variation and variance analysis are used to analyze the profile change laws of the soil water content, pH value, EC value, TDS value and the contents of eight major ions.

[0058] Specifically, in this embodiment, the coefficient of variation, variance analysis, etc. are used to analyze the change laws of the pH value, EC value, TDS value and the contents of eight major ions in the soil profile. The coefficient of variation (CV) is a percentage representation obtained by dividing the standard deviation by the mean and is used to measure the relative fluctuation degree of a set of data. Where σ is the standard deviation of the sample and μ is the sample mean. Generally, a CV value less than 10% indicates low-intensity variation, 10% - 100% indicates medium-intensity variation, and over 100% indicates high-intensity variation. Analysis of variance (ANOVA) is used to test whether the differences in means between two or more groups are statistically significant. Before performing ANOVA analysis, it is necessary to determine whether the variables meet the normal distribution. If they do, ANOVA analysis can be carried out; otherwise, the conditions for ANOVA analysis are not met. Separate ANOVA tests are performed for pH value, EC value, TDS value, and each ion. Once the ANOVA results show significant differences, post hoc tests such as Tukey's HSD need to be further performed to clarify which specific two groups have obvious differences.

[0059] Furthermore, analyzing the proportions and ratios of the soil ions includes calculating the sodium adsorption ratio and the ratio of chloride ion to sulfate ion, which are used to evaluate the degree of soil salinization and leaching degree.

[0060] Specifically, the analysis of ion proportions and ratios, such as the sodium adsorption ratio, the ratio of chloride ion to sulfate ion, etc. Determine the degree of soil salinization, leaching degree, ion sources, etc. The sodium adsorption ratio is a measure of the proportion of exchangeable sodium in the soil relative to calcium and magnesium, and is used to evaluate whether the soil is affected by sodium accumulation, which may affect soil structure and plant growth. The sodium adsorption ratio SAR = [Na + / (0.5[Ca 2+ +0.5[Mg 2+ ) 0.5 . Where the unit of each ion concentration is mg / L. Low SAR: indicates a low content of exchangeable sodium in the soil, which is beneficial to maintaining a good soil structure. High SAR: indicates possible problems such as sodium accumulation and salinization, which may lead to soil compaction, decreased air permeability and water permeability. The ratio of chloride ion to sulfate ion is Cl - / SO 4 2- . Chloride ion is more easily affected by water migration than sulfate ion.

[0061] By comparing the change trends of various indicators between different depth levels, the leaching effect within the soil profile can be inferred: lower in the surface layer and higher in the deep layer indicates obvious leaching, and the soluble salts in the upper soil are carried by rainwater or other water sources and migrate towards the deep layer; uniform distribution in the surface layer or the opposite pattern implies less leaching activity or possible re-precipitation phenomenon.

[0062] Furthermore, the multivariate statistical analysis includes principal component analysis (PCA), hierarchical clustering analysis (HCA), and correlation analysis, which are used for the correlation between groundwater depth and soil ion distribution, the correlation between ions, and the correlation between ion distributions in different profiles.

[0063] Specifically, multivariate statistical analysis includes principal component analysis (PCA), hierarchical clustering analysis (HCA), correlation analysis, etc. To determine the correlations between groundwater depth and soil ion distribution, among ions, and among ion distributions in different profiles, due to the large differences in the orders of magnitude of different chemical components, it is usually necessary to standardize the original data (such as Z-score standardization) to eliminate the influence of dimensions in subsequent analyses. PCA aims to reduce the dimension of a multi-dimensional dataset while retaining as much original information as possible, thereby simplifying data analysis and revealing potential patterns.

[0064] The specific steps of PCA are as follows: (1) Construct a covariance matrix or a correlation coefficient matrix: calculated based on the standardized data. (2) Eigenvalue decomposition: Solve the eigenvectors and eigenvalues of the covariance / correlation coefficient matrix. Select the principal components: Select the first few principal components with a cumulative contribution rate reaching 80%-90% or more. (3) Plot the score plot and the loading plot: The score plot shows the positions of the sample points in the new coordinate system; the loading plot represents the projections of the variables on the principal components.

[0065] Analyze the relationship between groundwater depth and soil ion distribution: By observing the trend of the sample points on the score plot with depth, it is possible to preliminarily judge whether there is an association between the two. Analyze the correlations among ions: The loading plot can visually show which ions have similar performances on the same principal component, suggesting possible positive or negative correlation relationships between them.

[0066] HCA is used to group objects with similar attributes to form a tree-like structure for easy identification of different clusters. The specific steps of HCA are as follows: (1) Select the distance metric: Common methods include Euclidean distance, Manhattan distance, etc. (2) Determine the linkage method: Such as the single-linkage method, complete-linkage method, average-linkage method, etc. (3) Construct the clustering tree: Gradually merge the nearest neighbor nodes based on the selected distance metric and linkage rule until all samples are grouped into the same category. (4) Cut the clustering result: Set a threshold according to actual needs to obtain the final cluster division.

[0067] Analyze the correlations between ion distributions in different profiles: By comparing the consistency degrees of the cluster groups to which the sample points in each profile belong, it is possible to evaluate whether there are similarities between them. To evaluate the linear dependence relationship between two or more variables, common indicators include the Pearson correlation coefficient, Spearman rank correlation coefficient, etc. The specific steps of correlation analysis are as follows: (1) Calculate the correlation coefficient: For each pair of variables of interest, calculate the strength of their correlation using an appropriate formula. (2) Significance test: Use a t-test or other statistical tests to determine whether the observed correlation is statistically significant. (3) Visual expression: The size and direction of the correlation can be intuitively presented in the form of a scatter plot, heat map, etc.

[0068] Furthermore, through the above experimental tests and analyses, the relationships between the groundwater depth and soil moisture, between the groundwater depth and soil salinity, and between the groundwater depth and the composition and proportion of soil ions can be quantitatively analyzed.

[0069] Specifically, in this embodiment, traditional hydrochemical methods are combined with methods such as soil ion proportion analysis, variance analysis, principal component analysis (PCA), hierarchical clustering analysis (HCA), and correlation analysis to analyze the relationship between the groundwater depth and soil ion distribution, and the variation law of soil ion distribution with the groundwater depth and the ion migration law can be quantitatively analyzed. This solves the limitations in the prior art such as time-consuming, laborious, complex models, and strong dependence on parameters.

[0070] Taking Korla and Puhui Farm in Xinjiang as the study area, a method for determining the relationship between groundwater depth and soil ion distribution proposed in this embodiment is described in detail, which specifically includes:

[0071] Use a laser-marked water level gauge (Model102, Solinst, Canada) to monitor the groundwater depth of the Water Conservancy Scientific Research Institute of Bayingolin Management Bureau of the Tarim River Basin and Puhui Farm. The groundwater depth of the Water Conservancy Scientific Research Institute is about 16 m, and there are two groundwater depths of about 3 m and 6 m in the sample plots of Puhui Farm. Take 3 groups of soil profiles at the Water Conservancy Scientific Research Institute, and take 1 group of soil profiles in the sample plots with two groundwater depths at Puhui Farm respectively. Drill a soil sample of 180 cm at each sampling point. Shallow to 80 cm, drill a soil sample every 10 cm, and drill a soil sample every 20 cm from 80 to 180 cm. Use a handheld Global Positioning System (GISPO G130BD, Beijing United Sino Strong Technology Co., Ltd., Beijing) to record the longitude, latitude and elevation of the sampling points.

[0072] During the sampling process, use a time domain reflectometer (TDR) to measure the soil moisture content. The collected soil samples are immediately stored in plastic bags and numbered for subsequent experiments. The soil conductivity (EC1:5), pH value and total dissolved solids (TDS) are measured from the leaching solution after mixing with a soil-water ratio of 1:5, shaking, centrifuging and filtering. The EC1:5 and pH value are measured by a pH-EC water quality tester (H1991301, HANNA, Italy), and the TDS is measured by JENCO TDS (3010M, Ren's Electronic Co., Ltd., Shanghai). The average value of the three measurement results is taken as the final result. Before the soil ion test, first air-dry, grind the soil in the sample bag, and pass it through a 1 mm sieve. The soil anions Cl - 、SO 4 2- are measured using a Dionex ion chromatograph (ICS1100, Dionex Corporation, USA), and CO 32- and HCO 3 - The titration method is adopted. For cations (Ca 2+ , Mg 2+ , Na + , K + ), an inductively coupled plasma spectrometer (5100 ICP-OES, Agilent Technologies, USA) is used. A total of 78 soil samples were measured in the experiment. Taking a soil sample from the Water Conservancy Scientific Research Institute as an example, the measured results of each variable are as follows: soil volumetric water content 3.2%, pH value 7.87, EC 1:5 value 0.24 mS / cm, TDS value 145.6 mg / L, potassium ion concentration 7.89 mg / L, sodium ion concentration 11.36 mg / L, calcium ion concentration 14.5911.36 mg / L, magnesium ion concentration 8.08 mg / L, sulfate ion concentration 31.05 mg / L, chloride ion concentration 17.6 mg / L, bicarbonate ion concentration 68.37 mg / L, carbonate ion concentration 0 mg / L.

[0073] Traditional soil hydrochemical analysis is carried out using Piper ternary diagrams, Gibbs diagrams, etc. Determine the hydrochemical composition and ion sources of each soil profile, etc. Taking a soil profile from the Water Conservancy Scientific Research Institute as an example, as Figure 2 , Figure 3 shown, its hydrochemical composition is of the Ca-Mg-SO4-Cl type. The ion sources are mainly affected by the types of rock minerals in the soil profile and human factors.

[0074] The variation coefficients, analysis of variance, etc. are used to analyze the variation laws of the pH value, EC value, TDS value and the contents of eight major ions in each soil profile. Taking a soil profile from the Water Conservancy Scientific Research Institute as an example, its coefficient of variation of soil volumetric water content is 26.09, coefficient of variation of pH is 5.95, coefficient of variation of EC is 31.11, coefficient of variation of TDS is 37.84, coefficient of variation of potassium ion is 42.82, coefficient of variation of sodium ion is 55.14, coefficient of variation of calcium ion is 31.78, coefficient of variation of magnesium ion is 41.54, coefficient of variation of chloride ion is 37.38, coefficient of variation of sulfate ion is 49.37, coefficient of variation of carbonate ion is 266.9, and coefficient of variation of bicarbonate ion is 41.4. Analysis of variance is used to analyze the differences between the average values of each variable among different profiles. Taking the soil volumetric water content as an example, taking four soil profiles from the Water Conservancy Scientific Research Institute and two profiles from Puhui Farm, as Figure 4As shown, the ANOVA results show significant differences, and the results of Tukey's HSD are A, A, B, C, D, E. The same letters indicate no significant differences, and different letters indicate significant differences. That is, the average values of the soil volumetric water content of two of the profiles have no significant differences, while significant differences exist among the other profiles. The same applies to other variables.

[0075] ANOVA analysis of each variable. CO 3 2- The distribution of [CO] does not satisfy the normal distribution, and ANOVA analysis was not performed.

[0076] Analysis of ion ratios and proportions, such as sodium adsorption ratio, ratio of chloride ion to sulfate ion, etc. Determine the degree of salinization, leaching degree, ion sources, etc. of each soil profile. Taking a soil profile in Puhui Farm as an example, along the depth direction, its sodium adsorption ratios are: 19.847, 19.392, 17.454, 17.938, 21.937, 27.716, 30.522, 36.615, 34.389, 33.179, 36.781, 30.636, 35.586. Its ratios of chloride ion to sulfate ion are: 0.345, 0.431, 0.578, 0.804, 0.708, 0.594, 0.561, 0.534, 0.588, 0.552, 0.605, 0.574, 0.676. Both the sodium adsorption ratio and the ratio of chloride ion to sulfate ion show an increasing trend along the depth direction, indicating obvious leaching. The sodium adsorption ratio content is higher in the deep layer, and the degree of salinization is stronger.

[0077] Multivariate statistical analysis, including principal component analysis, hierarchical clustering, correlation analysis, etc. Determine the correlations between the groundwater depth and soil ion distribution, between ions, and between ion distributions of different profiles. All 78 samples were included in the analysis scope, and the sample characteristics include soil volumetric water content, pH value, EC value, contents of eight major ions, groundwater depth, etc. First, perform Z-score standardization on all characteristics. Obtain the score plot and loading plot using PCA analysis, as Figure 5 shown, where the first principal component PC1 = 53.96%, and the second principal component PC2 = 13.24%.

[0078] The HCA analysis used the Ward clustering method and Euclidean distance to divide the clusters into 2 categories. There are obvious differences in the groundwater depth of different categories. As Figure 6 shown, below the isotype line (Euclidean distance is 25), the Water Conservancy Research Institute (Korla area) and Puhui Farm are divided into two obvious clusters.

[0079] Pearson correlation coefficient is used to calculate the correlation in the correlation analysis. Pearson correlation coefficient is usually used to measure the linear correlation degree between two variables X and Y. Its value ranges from -1 to 1, where 1 represents a perfect positive correlation, -1 represents a perfect negative correlation, and 0 represents no linear correlation. Its calculation formula is: where r xy is the Pearson correlation coefficient between variables x and y, x i and y i are the observed values of variables x and y respectively, and are the average values of x and y respectively, ∑ represents the summation symbol, meaning summing over all paired observed values. The correlations between each index and the groundwater depth are as follows: the correlation between soil volumetric water content and groundwater depth is -0.75, the correlation between pH and groundwater depth is -0.12, the correlation between EC and groundwater depth is -0.75, the correlation between TDS and groundwater depth is -0.74, the correlation between potassium ion and groundwater depth is -0.7, the correlation between sodium ion and groundwater depth is -0.76, the correlation between calcium ion and groundwater depth is -0.61, the correlation between magnesium ion and groundwater depth is -0.82, the correlation between chloride ion and groundwater depth is -0.69, the correlation between carbonate ion and groundwater depth is -0.69, the correlation between bicarbonate ion and groundwater depth is -0.22, the correlation between sodium adsorption ratio and groundwater depth is -0.63, and the correlation between the ratio of chloride ion to sulfate ion and groundwater depth is 0.41.

[0080] Analyze the relationships between groundwater depth and soil moisture, groundwater depth and soil salinity, and groundwater depth and soil ion composition and proportion. (1) Relationship between groundwater depth and soil moisture: ① Shallow groundwater has a significant impact: When the soil profile is close to the groundwater level, higher soil moisture is usually observed because groundwater rises to near the surface through capillary action. ② Deep soil moisture is relatively stable: As the distance from the groundwater level increases, the soil moisture content gradually decreases, and it is more significantly affected by precipitation and evaporation. (2) Relationship between groundwater depth and soil salinity: This is because shallow groundwater often contains a relatively high concentration of dissolved salts. When it rises to the soil surface and evaporates, the water evaporates while the salts remain, easily leading to soil salinization. On the contrary, when the groundwater depth is relatively deep, the soil lacks sufficient salt sources, and the accumulation of salts is limited. In addition, the recharge rate of deep groundwater is slow, which also reduces the migration of salts to the soil surface. (3) There is a significant negative correlation between the groundwater depth and SAR in the study area, while with Cl - / SO 4 2-The ratio shows a significant positive correlation. When the groundwater depth is relatively shallow, the soil moisture content is relatively high, which is conducive to the migration and accumulation of sodium ions, resulting in an increase in the SAR value. At the same time, the strong soil evaporation and the easy accumulation of salts on the surface layer will also lead to an increase in the SAR value, ultimately resulting in the destruction of the soil structure and the aggravation of salinization. On the contrary, as the groundwater depth increases, the SAR value decreases, which is conducive to maintaining the stability of the soil structure and reducing the risk of salinization.

[0081] On the other hand, this embodiment also provides a determination system for the relationship between groundwater depth and soil ion distribution, including:

[0082] A sample collection module for collecting soil samples in the target area;

[0083] A content determination module for measuring the soil moisture content, pH value, electrical conductivity EC value, TDS value and the content of eight major ions in the soil sample;

[0084] An ion determination module for determining the soil ion type and the main source of ions in the soil sample;

[0085] A law analysis module for analyzing the profile change laws of the soil moisture content, pH value, EC value, TDS value and the content of eight major ions, as well as the proportion and ratio of soil ions;

[0086] A distribution analysis module for performing multivariate statistical analysis based on the profile change laws and the proportion and ratio of soil ions to obtain the relationship between groundwater depth and soil moisture, the relationship between groundwater depth and salinity, and the relationship between groundwater depth and soil ion content, representative ion ratio and composition.

[0087] Further, the sample collection module collecting the soil samples in the target area includes:

[0088] Sampling is carried out at multiple depths of the soil profile under different groundwater depth conditions in the target area at preset intervals to obtain the soil samples.

[0089] Specifically, the collection of soil samples in the target area in this embodiment includes: collecting soil profiles at multiple different groundwater depths, and sampling each profile according to depth. For example, sampling is carried out every 10 cm or 20 cm, and soil samples of several meters can be taken to discuss the change laws of soil ion distribution, etc. with depth.

[0090] Further, the content determination module measures the soil moisture content, pH value, electrical conductivity EC value, TDS value and the content of eight major ions in the soil sample using an inductively coupled plasma spectrometer, including a Dionex ion chromatograph.

[0091] Specifically, during the sampling process of this embodiment, a time domain reflectometer (TDR) is used to measure the soil water content. The collected soil samples are immediately sealed in plastic bags for subsequent laboratory tests.

[0092] Before the experimental tests, the soil samples need to be air-dried naturally and passed through a 1-mm sieve. In the laboratory, the pH value, EC value, TDS value, and the contents of eight major ions of the soil samples are measured using an inductively coupled plasma spectrometer, including a Dionex ion chromatograph.

[0093] Furthermore, the ion determination module determines the types of soil ions in the soil sample using a Piper trilinear diagram. By analyzing the ratio of anions and cations in the soil sample, the ions in the soil are determined.

[0094] To determine the main sources of ions, a Gibbs diagram is used. By comparing the positions of data points of different soil samples on the Gibbs diagram, the influencing factors of soil water chemistry are determined.

[0095] Specifically, this embodiment uses a Piper trilinear diagram, a Gibbs diagram, etc. for traditional soil water chemistry analysis to determine the soil water chemical composition, ion sources, etc.

[0096] The Piper diagram is a classic tool for showing the relative proportions of major anions and cations in natural waters. It consists of two triangles and a rhombus: The left triangle represents the relationship between three major cations (Na + +K + , Ca 2+ , Mg 2+ ). The right triangle represents the relationship between three major anions (Cl - , HCO 3 - , SO 4 2- ). The central rhombus connects the left and right triangles and is used to represent the classification of water samples. The position of each sample point reflects its chemical characteristics, and different types of water sources or influencing factors will form specific distribution patterns on the diagram.

[0097] The Gibbs diagram helps to understand the main mechanisms controlling water chemistry, namely rock weathering, atmospheric precipitation, or evaporation concentration. This diagram is based on the relationship between TDS (total dissolved solids) and Cl - concentration to distinguish the above three main forces. By comparing the positions of the actually measured data points on the Gibbs diagram, it can be inferred which processes contribute significantly to soil water chemistry.

[0098] Furthermore, the law analysis module analyzes the profile change laws of the soil water content, pH value, EC value, TDS value, and the contents of eight major ions using the coefficient of variation and variance analysis.

[0099] Specifically, in this embodiment, the variation coefficients, variance analysis, etc. are used to analyze the variation laws of the pH value, EC value, TDS value and the contents of eight major ions in the soil profile. The coefficient of variation (CV) is expressed as the percentage of the standard deviation divided by the mean, and is used to measure the relative fluctuation degree of a set of data. Where σ is the standard deviation of the sample, and μ is the sample mean. Generally speaking, a CV value less than 10% is low-intensity variation, 10% - 100% is medium-intensity variation, and more than 100% is high-intensity variation. Analysis of variance (ANOVA) is used to test whether the difference in means between two or more groups is statistically significant. Before performing ANOVA analysis, it is necessary to determine whether the variable satisfies the normal distribution. If it is satisfied, ANOVA analysis can be performed; otherwise, the conditions for ANOVA analysis are not met. Separate ANOVA tests are performed for the pH value, EC value, TDS value and each ion respectively. Once the ANOVA results show significant differences, post hoc tests such as Tukey's HSD need to be further performed to clarify which specific two groups have obvious differences.

[0100] Furthermore, the rule analysis module analyzes the proportion and ratio of the soil ions, including calculating the sodium adsorption ratio and the ratio of chloride ion to sulfate ion, for evaluating the soil salinization degree and leaching degree.

[0101] Specifically, the analysis of the ion proportion and ratio, such as the sodium adsorption ratio, the ratio of chloride ion to sulfate ion, etc. Determine the soil salinization degree, leaching degree, ion source, etc. The sodium adsorption ratio is a measure of the proportion of exchangeable sodium relative to calcium and magnesium in the soil, and is used to evaluate whether the soil is affected by sodium accumulation, which may affect the soil structure and plant growth. The sodium adsorption ratio SAR = [Na + / (0.5[Ca 2+ +0.5[Mg 2+ ) 0.5 . Where the unit of each ion concentration is mg / L. Low SAR: indicates that the content of exchangeable sodium in the soil is low, which is beneficial to maintaining a good soil structure. High SAR: indicates that there may be problems such as sodium accumulation and salinization, which may lead to soil compaction, decreased air permeability and water permeability. The ratio of chloride ion to sulfate ion is Cl - / SO 4 2- . Chloride ion is more easily affected by water migration than sulfate ion.

[0102] By comparing the changing trends of various indicators among different depth levels, the leaching effect within the soil profile can be inferred: lower in the surface layer and increasing in the deeper layer indicates obvious leaching, where soluble salts in the upper soil are carried by rainwater or other water sources and migrate towards the deeper layer; uniform distribution in the surface layer or the opposite pattern implies less leaching activity or possible reprecipitation.

[0103] Furthermore, the multivariate statistical analysis adopted by the distribution analysis module includes principal component analysis (PCA), hierarchical clustering analysis (HCA), and correlation analysis, which are used for the correlation between groundwater depth and soil ion distribution, the correlation between ions, and the correlation between ion distributions in different profiles. Through the above experimental tests and analyses, quantitative analyses can be conducted on the relationships between groundwater depth and soil moisture, between groundwater depth and soil salinity, and between groundwater depth and soil ion composition and proportion.

[0104] Specifically, the multivariate statistical analysis includes principal component analysis (PCA), hierarchical clustering analysis (HCA), correlation analysis, etc. To determine the correlations between groundwater depth and soil ion distribution, between ions, and between ion distributions in different profiles, etc., since the orders of magnitude of different chemical components vary greatly, it is usually necessary to standardize the original data (such as Z - score standardization) to eliminate the influence of dimensions in subsequent analyses. PCA aims to reduce the dimension of a multi - dimensional data set while retaining as much original information as possible, thus simplifying data analysis and revealing potential patterns.

[0105] The specific steps of PCA include: (1) Constructing the covariance matrix or correlation coefficient matrix: calculated based on the standardized data. (2) Eigenvalue decomposition: solving the eigenvectors and eigenvalues of the covariance / correlation coefficient matrix. Selecting the principal components: selecting the first few principal components with a cumulative contribution rate reaching 80% - 90% or more. (3) Drawing the score plot and loading plot: The score plot shows the positions of sample points in the new coordinate system; the loading plot represents the projections of each variable on the principal components.

[0106] Analyzing the relationship between groundwater depth and soil ion distribution: By observing the trend of sample points changing with depth on the score plot, it can be preliminarily judged whether there is an association between the two. Analyzing the correlation between ions: The loading plot can visually show which ions have similar performances on the same principal component, indicating that there may be a positive or negative correlation between them.

[0107] HCA is used to group objects with similar attributes to form a tree structure, which facilitates the identification of different clusters. The specific steps of HCA include: (1) Distance metric selection: Common methods include Euclidean distance, Manhattan distance, etc. (2) Linkage method determination: Such as single linkage method, complete linkage method, average linkage method, etc. (3) Construction of the clustering tree: Based on the selected distance metric and linkage rule, gradually merge the nearest neighbor nodes until all samples are classified into the same category. (4) Truncation of the clustering result: Set a threshold according to actual needs to obtain the final cluster division.

[0108] Analyze the correlation between ion distributions in different profiles: By comparing the consistency degree of the cluster groups to which the sample points in each profile belong, it is possible to evaluate whether there is similarity between them. To evaluate the linear dependence between two or more variables, common indicators include Pearson correlation coefficient, Spearman rank correlation coefficient, etc. The specific steps of correlation analysis include: (1) Calculate the correlation coefficient: For each pair of variables of interest, use an appropriate formula to calculate the strength of their correlation. (2) Significance test: Use a t-test or other statistical tests to determine whether the observed correlation is statistically significant. (3) Visualization expression: The size and direction of the correlation can be visually presented in the form of scatter plots, heat maps, etc.

[0109] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for determining the relationship between groundwater depth and soil ion distribution, characterized in that: include: Collect soil samples from target areas; Determine the soil water content, pH value, electrical conductivity EC value, TDS value and eight ion contents of the soil sample, and determine the soil ion type and main ion source of the soil sample; Analyze the profile variation patterns of soil water content, pH value, EC value, TDS value and eight ion contents, as well as the proportion and ratio of soil ions; Based on the profile change rules and the proportions and ratios of soil ions, multivariate statistical analysis was performed to obtain the relationship between groundwater depth and soil moisture, the relationship between groundwater depth and salinity, and the relationship between groundwater depth and soil ion content and representative ion ratios and composition.

2. The method for determining the relationship between groundwater depth and soil ion distribution according to claim 1, characterized in that: The collection of soil samples in the target area includes: At multiple depths of the soil profile under different groundwater depths in the target area, sampling is performed every preset distance to obtain the soil samples.

3. The method for determining the relationship between groundwater depth and soil ion distribution according to claim 1, characterized in that: The soil water content, pH value, electrical conductivity EC value, TDS value and eight ion contents of the soil sample were measured using an ion spectrometer, including a Dionex ion chromatograph and an inductively coupled instrument.

4. The method for determining the relationship between groundwater depth and soil ion distribution according to claim 1, characterized in that: The soil ion type of the soil sample is determined by using a piper three-line diagram, and the ions in the soil are determined by analyzing the ratio of anions and cations in the soil sample; The Gibbs diagram was used to determine the main sources of ions, and the influencing factors of soil water chemistry were determined by comparing the positions of data points of different soil samples on the Gibbs diagram.

5. The method for determining the relationship between groundwater depth and soil ion distribution according to claim 1, characterized in that: The coefficient of variation and variance analysis were used to analyze the profile changes of the soil moisture content, pH value, EC value, TDS value and the contents of eight major ions.

6. The method for determining the relationship between groundwater depth and soil ion distribution according to claim 1, characterized in that: The analysis of the proportion and ratio of the soil ions includes calculating the sodium adsorption ratio and the ratio of chloride ions to sulfate ions, which are used to evaluate the degree of soil salinization and leaching.

7. The method for determining the relationship between groundwater depth and soil ion distribution according to claim 1, characterized in that: The multivariate statistical analysis includes principal component analysis (PCA), hierarchical cluster analysis (HCA), and correlation analysis, which are used for the correlation between groundwater depth and soil ion distribution, the correlation between ions, and the correlation between ion distributions in different profiles.

8. A system for determining the relationship between groundwater depth and soil ion distribution, characterized in that: include: A sample collection module, used to collect soil samples from the target area; A content determination module, used to determine the soil moisture content, pH value, electrical conductivity EC value, TDS value and eight ion contents of the soil sample; An ion determination module, used to determine the soil ion type and main ion source of the soil sample; A rule analysis module is used to analyze the profile change rules of the soil water content, pH value, EC value, TDS value and eight ion contents, as well as the proportion and ratio of soil ions; The distribution analysis module is used to perform multivariate statistical analysis based on the profile change law and the proportion and ratio of soil ions to obtain the relationship between groundwater depth and soil moisture, the relationship between groundwater depth and salinity, and the relationship between groundwater depth and soil ion content and representative ion ratios and composition.

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