Method and system for identifying water-rich lithological boundary zone in front of tunnel and water supply source

Abstract

The present application belongs to the field of hydrogeology, and provides a method and system for identifying water-rich lithology boundary zone and recharge water source in front of a tunnel. Based on the principle that groundwater interacts with different lithology in a characteristic water-rock interaction process, is controlled by the lithology combination and hydrogeological conditions, and leaves unique chemical characteristics in water, the ion composition, characteristic ratio, mineral saturation state and multivariate statistical characteristics in groundwater are analyzed by the system, the lithology sequence and runoff path experienced by the groundwater can be inverted, and thus the spatial position of the water-rich lithology boundary zone and the recharge source of the groundwater can be accurately identified. The present application improves the type identification of discrete point samples of groundwater chemical analysis to lithology detection and water source tracing technology based on the inversion of water-rock interaction process, realizes the spatial positioning of the water-rich lithology boundary zone and the accurate identification of the recharge water source by establishing the quantitative correlation between the water-rock interaction process-chemical characteristics-lithology combination-water source type.

Description

Technical Field

[0001] This invention belongs to the field of hydrogeology, specifically relating to a method and system for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Currently, the identification of water-rich structures mainly relies on two types of techniques: geophysical exploration and drilling water sampling analysis. Geophysical exploration techniques, such as induced polarization, seismic methods, and ground-penetrating radar, can effectively delineate the spatial distribution and scale of water-bearing anomalies by detecting differences in physical parameters such as electrical and elastic properties of rock masses. These methods have advantages in detecting the spatial location and morphology of water-bearing structures and can provide important evidence for locating water-rich areas. However, geophysical parameters mainly reflect differences in the physical properties of rock masses. For delineated water-bearing anomalies, it is difficult to further clarify their specific hydrogeological attributes, especially whether the water-bearing structure is a lithological boundary zone or the type of water recharge source.

[0004] On the other hand, hydrochemical analysis techniques, by measuring and analyzing indicators such as major ions, mineralization, hydrochemical type, and characteristic ion ratios in groundwater samples, can invert the source, runoff path, and evolutionary history of water bodies from the perspective of water-rock interaction, making it a reliable hydrochemical characteristic discrimination technique. This method has the ability to identify groundwater recharge sources, distinguishing between different water source types such as atmospheric precipitation recharge, surface water recharge, and deep circulating water recharge through hydrochemical characteristics. Furthermore, different lithological combinations, such as the boundary between carbonate and sulfate rocks, and the interbedded zones of mudstone and sandstone, can trigger drastically different water-rock interaction processes, thus forming unique hydrochemical characteristics in local areas. Theoretically, hydrochemical methods have the potential to identify lithological boundaries.

[0005] However, for hydrochemical methods to be effectively applied to the identification of lithologic boundaries and recharge sources, improvements and enhancements are needed in the following aspects. Regarding the identification of lithologic boundaries, the characteristic water-rock interaction processes of different lithologic assemblages need to be identified through the establishment of systematic quantitative indicators: the boundary between carbonate and sulfate rocks can be identified through Ca²⁺... + / Mg² + The ratio determines the contribution of carbonate dissolution to sulfate dissolution, using Ca²⁺. + / HCO3 -The ratio can be used to determine the contribution of exogenous acids such as sulfuric acid to water-rock reactions; the chloride-alkali index (CAI) can be used to determine the direction and intensity of cation exchange at the interface of mudstone, shale, or coal-bearing strata rich in clay minerals; and the Na+ ratio can be used to determine the interface of evaporite strata. + / Cl - The ratio indicates the influence of salt rock dissolution; sulfide strata or coal-bearing strata can be influenced by SO4²⁻. - Concentration and Ca² + / HCO3 - The ratio is used to identify the influence of sulfuric acid produced by sulfide oxidation on water-rock interaction. Regarding water source identification, different recharge sources exhibit characteristic hydrochemical compositions and combinations: direct recharge from atmospheric precipitation is characterized by low total dissolved solids (TDS) and Na+. + / Cl - The ratio is close to that of seawater, the hydrochemical type is Na-Cl or Ca-HCO3, and the dissolved oxygen (DO) content is relatively high; the lateral recharge of shallow surface water is characterized by high NO3 content. - High dissolved oxygen levels, significantly affected by human activities; deep confined water recharge is characterized by high TDS and Na+. + / Cl - The ratio is much greater than 1 or much less than 1, the water chemistry is of the Na-HCO3 or Na-Cl type, and the dissolved oxygen content is low; the paleoseawater residue shows Na + / Cl - The ratio is close to that of seawater, with a high Br content. - / Cl - Characteristic ion ratios are often associated with high mineralization; mixed recharge from different aquifers results in a mixed linear distribution of characteristic ion ratios, with hydrochemical types falling between two endmembers. Furthermore, traditional hydrochemical analysis relies on the collection and analysis of discrete point samples, providing only point-like information, making spatial prediction of aquifers in unexposed areas difficult. To effectively apply hydrochemical methods to spatial location at lithologic boundaries, it is necessary to systematically integrate point-like hydrochemical information with regional geological background and lithologic assemblage, transforming discrete hydrochemical data into spatially continuous identification criteria through multi-scale analysis. Summary of the Invention

[0006] To address the aforementioned problems, this invention proposes a method and system for identifying water-rich lithological boundary zones and recharge sources ahead of tunnels. This invention elevates groundwater chemical analysis from identifying the type of discrete point samples to a lithological detection and water source tracing technology based on the inversion of water-rock interaction processes. By establishing a quantitative correlation between water-rock interaction processes, chemical characteristics, lithological combinations, and water source types, it achieves the spatial positioning of water-rich lithological boundary zones and the accurate identification of recharge sources.

[0007] According to some embodiments, the present invention adopts the following technical solution: A method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel includes the following steps: Obtain water sample parameters from each groundwater sampling point; Water quality analysis is conducted to establish a set of indicators covering multiple dimensions of information, which is used to characterize the intensity and characteristics of different water-rock interaction processes. The set of indicators includes ion concentration, ion ratio, characteristic index, mineral saturation index, and auxiliary environmental indicators. Based on the aforementioned index set, a feature identification system for different lithological boundary zones and different water source types is established from the perspective of water-rock interaction processes. Based on the aforementioned index set and feature identification system, a quantitative identification standard is established, and a comprehensive verification is performed using multivariate statistical analysis methods. Through step-by-step analysis, the identification results of lithological boundary zones and water source types are obtained as initial identification results. Data preprocessing was performed on water sample parameters identified as water-rich lithological boundary zones and water supply sources. Based on the preprocessed data, the similarity distance between each water sample is calculated, and cluster analysis is performed based on the similarity distance. The cluster results obtained from the cluster analysis are spatially superimposed and cross-compared with the initial identification results to achieve cluster verification. Based on the preprocessed data, principal component extraction is performed to obtain the loading matrix of each principal component. The loading matrix is ​​then compared with the initial identification results item by item. Based on the comparison results, a hierarchical judgment is made to achieve principal component verification. By combining the results of clustering verification and principal component verification, the spatial location and type of the water-rich lithological boundary zone in the initial identification results were corrected to obtain the final result.

[0008] As an alternative implementation method, the process of obtaining water sample parameters from various groundwater sampling points includes: based on the geological survey data, lithological combination zoning, fault zone distribution and hydrogeological unit division of the target area, systematically deploying groundwater sampling points along the tunnel and surrounding areas, with sampling points covering different lithological zones, fault fracture zones, surface water bodies and groundwater at different depths, and conducting multiple sampling phases during the tunnel construction and operation periods to obtain water samples that are representative of time and space.

[0009] As an alternative implementation, the index set includes: The main ion concentration indicators, including the mass concentrations of the main anions and cations, serve as the basic data for hydrochemical characteristics to reflect the fundamental features of carbonate dissolution, sulfate dissolution, and evaporite dissolution in water-rock processes. Characteristic ion ratio index, calculates the molar ratio of each major anion and cation, used to distinguish the contribution ratio of carbonate dissolution and sulfate dissolution, judge the influence of evaporite dissolution, and identify the hydrolysis and cation exchange of silicate minerals; Characteristic indexes include the chlor-alkali index (CAI) and the sodium adsorption ratio (SAR). The chlor-alkali index is used to determine the direction and intensity of cation exchange, while the sodium adsorption ratio is used to assess the impact of cation exchange on sodium ion enrichment. Mineral saturation index (SI) indicators, including calcite saturation index (SI_c), dolomite saturation index (SI_d), gypsum saturation index (SI_g), and rock salt saturation index (SI_h), are used to determine the dissolution and precipitation trends of each mineral and to invert the equilibrium state and evolution direction of water-rock reaction. Auxiliary environmental indicators, including total dissolved solids (TDS), dissolved oxygen (DO), dissolved organic carbon (DOC), pH, iron (Fe), and manganese (Mn), are used to assess redox environment, organic matter input characteristics, and the degree of mixing with shallow surface water.

[0010] As an alternative implementation method, the process of establishing a feature identification system for different lithological boundaries and different water source types based on the aforementioned index set, from the perspective of water-rock interaction processes, includes: The water-rock interaction characteristics of lithological boundary zones include several types: the boundary zone between carbonate and sulfate rocks, the boundary zone between mudstone, shale or coal-bearing strata rich in clay minerals, the boundary zone between evaporite strata, and the boundary zone between sulfide strata. The corresponding manifestations or value ranges of each type of water-rock interaction are analyzed in the index set, and the correlation is established. The characteristics of water source types include: direct recharge from atmospheric precipitation, lateral recharge from shallow surface water, cross-flow recharge from deep confined water, paleosea remnants, and mixed recharge from different aquifers. The corresponding manifestations or value ranges of the indicators in each water source type are analyzed, and the correlation is established.

[0011] As an alternative implementation method, the process of data preprocessing for water sample parameters identified as water-rich lithological boundary zones and water supply sources includes: standardizing all water sample data based on the main ion concentrations, characteristic ion ratios, characteristic indices, mineral saturation indices, and auxiliary environmental indicators of the index set, eliminating the influence of dimensions, and constructing the original data matrix.

[0012] As an alternative implementation method, the similarity distance between each water sample is calculated. The process of cluster analysis based on the similarity distance includes: calculating the similarity distance between each water sample based on the standardized data matrix; using the Ward method (i.e., the sum of squared deviations method) to perform clustering based on the distance calculation until all water samples are merged into one large class, generating a cluster dendrogram; and cutting the dendrogram at a set appropriate distance threshold to divide the water samples into several groups with similar hydrochemical characteristics.

[0013] As an optional implementation method, the process of spatially overlaying and cross-comparing the cluster results obtained from cluster analysis with the initial identification results includes: spatially overlaying and cross-comparing the cluster results obtained from cluster analysis with the lithological boundary zone type and water source type identified in the initial identification; for each cluster, the frequency of type classification of each water sample under the quantitative identification criteria is counted, and the type consistency index within the cluster is calculated, i.e., the percentage of the number of water samples of the same type to the total number of water samples in the cluster; if the consistency index of the cluster is greater than the first set value, and the spatial location of all water samples in the cluster is within the corresponding lithological boundary zone or hydrogeological unit range indicated by the geological data, it is determined to be strongly consistent, and a high-confidence identification conclusion is obtained; If the consistency index is between the first and second set values, or if there is a partial offset in the spatial superposition but the centroid of the group is still within the corresponding geological zone, it is judged as weak consistency, and the principal component analysis results are introduced for auxiliary verification. If the consistency index is lower than the second set value, or if the spatial distribution of the taxonomy does not correspond to any known geological division, it is judged as inconsistent, and the taxonomy is identified as a mixed influence area or a data anomaly area.

[0014] As a further defined implementation method, for inconsistent clusters, the quantitative identification results of each water sample are analyzed to see if two or more types coexist but are grouped into one category during clustering. If so, it is identified as a composite zone influenced by multiple water sources or multiple lithologies, and the conclusion is marked as mixed or composite. At the same time, the order of dominant and secondary types is given according to the proportion of each type of water sample in the cluster. If not, the key ion concentrations of the original data are checked, and after confirming the data quality, it is decided to remove or mark it as a local outlier.

[0015] As an alternative implementation method, based on the preprocessed data, principal component extraction is performed to obtain the loading matrix of each principal component. The loading matrix of each principal component is then compared with the initial identification results item by item. The process of principal component verification is carried out by classifying and judging according to the comparison results. The process includes: performing principal component extraction on the standardized hydrochemical data to obtain the loading matrix of each principal component, and identifying one or more dominant water-rock interaction processes according to the pre-constructed direct mapping rules between the loading combination and the lithological boundary zone type. The identified dominant process is compared item by item with the lithological boundary zone type of the initial identification result. The results are graded and judged according to the comparison. When the dominant process of load identification is completely consistent with the quantitative identification standard, it is judged as verified. When the dominant process of load identification only partially matches, it is judged as partially verified. It is also recommended to increase the sampling density in the corresponding area. When the dominant process of load identification completely contradicts the quantitative identification standard, it is judged as verified as not passing, triggering an abnormal review or determining whether the threshold of the quantitative identification standard is applicable.

[0016] A system for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel includes: The parameter acquisition module is configured to acquire water sample parameters from each groundwater sampling point. The index set construction module is configured to perform water quality analysis and establish an index set covering multi-dimensional information to characterize the intensity and characteristics of different water-rock interaction processes. The index set includes ion concentration, ion ratio, characteristic index, mineral saturation index, and auxiliary environmental indicators. The feature recognition module is configured to establish a feature recognition system for different lithological boundary zones and different water source types from the perspective of water-rock interaction processes, based on the index set. The initial identification module is configured to establish quantitative identification criteria based on the index set and feature recognition system, and to conduct comprehensive verification by combining multivariate statistical analysis methods. Through step-by-step analysis, the identification results of lithological boundary zones and water source types are obtained as the initial identification results. The preprocessing module is configured to preprocess the data parameters of water samples identified as water-rich lithological boundary zones and water supply sources. The clustering verification module is configured to calculate the similarity distance between each water sample based on the preprocessed data, perform clustering analysis based on the similarity distance, and spatially overlay and cross-compare the clustering results with the initial identification results to achieve clustering verification. The principal component verification module is configured to extract principal components based on preprocessed data, obtain the loading matrix of each principal component, compare it item by item with the initial identification results, and make a graded judgment based on the comparison results to achieve principal component verification. The comprehensive judgment module is configured to combine the results of cluster verification and principal component verification to correct the spatial location and type of the water-rich lithological boundary zone in the initial identification results, and obtain the final result.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention is based on the characteristic water-rock interactions that occur between groundwater and different lithologies during runoff, including carbonate dissolution, sulfate dissolution, silicate hydrolysis, cation exchange, and redox reactions. These processes are controlled by the lithological assemblage and hydrogeological conditions through which the water flows, and leave unique chemical characteristics in the water. By systematically analyzing the ionic composition, characteristic ratios, mineral saturation state, and multivariate statistical characteristics of groundwater, the lithological sequence and runoff path experienced by the groundwater can be deduced, thereby accurately identifying the spatial location of the water-rich lithological boundary zone and the source of groundwater recharge.

[0018] This invention elevates groundwater chemical analysis from identifying the type of discrete point samples to a lithological detection and water source tracing technology based on the inversion of water-rock interaction processes. By establishing a quantitative correlation between water-rock interaction processes, chemical characteristics, lithological combinations, and water source types, it enables the spatial positioning of water-rich lithological boundaries and the accurate identification of recharge sources.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0020] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0021] Figure 1 This is a schematic diagram of a quantitative identification process in one embodiment; Figure 2 This is a schematic diagram of a comprehensive verification and correction process for one embodiment; Figure 3 This is a lithological zoning and recharge source map of one embodiment; Figure 4 This is a scatter plot of the measured concentrations of the main ions in one embodiment; Figure 5 A graph showing the characteristic ratios, chlor-alkali index, and mineral saturation index of one embodiment; Figure 6 This is an auxiliary identification parameter diagram of one embodiment; Figure 7 This is a confidence graph for one embodiment. Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0023] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0024] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0025] Where there is no conflict, the embodiments and features described in this application may be combined with each other.

[0026] Example 1 This embodiment provides a method for identifying the water-rich lithological boundary zone and water supply source in front of the tunnel, including the following steps: The first step is systematic sampling and collection. Based on the geological survey data, lithological zoning, fault zone distribution, and hydrogeological unit division of the target area, groundwater sampling points are systematically deployed along the tunnel and in the surrounding area. Sampling points need to cover different lithological zones, such as carbonate rock zones, clastic rock zones, igneous rock zones, fault fracture zones, surface water bodies, and groundwater at different depths. Multiple sampling sessions are conducted during the tunnel construction and operation periods to obtain spatiotemporally representative water samples. Sample collection and preservation strictly follow relevant specifications; on-site parameter measurements, including pH and dissolved oxygen, are performed before sampling.

[0027] The second step is the establishment of a hydrochemical index set. A systematic water quality analysis is performed on the collected water samples to establish an index set encompassing multi-dimensional information, used to characterize the intensity and characteristics of different water-rock interaction processes: (1) Main ion concentration indicators: Measurement of Ca² + Mg² + Na + HCO3 - SO4² - Cl - NO3 - The mass concentrations of major anions and cations serve as fundamental data for hydrochemical characteristics, reflecting the basic features of water-rock interactions such as carbonate dissolution, sulfate dissolution, and evaporite dissolution.

[0028] (2) Characteristic ion ratio index: Calculate Ca² + / Mg² + Ca² + / HCO3- Na + / Cl - HCO3 - / SO4² - Na + / Ca² + ,Br - / Cl - The plasma molar ratio is used to distinguish the contribution ratio of carbonate dissolution to sulfate dissolution, to determine the influence of evaporite dissolution, and to identify the hydrolysis and cation exchange of silicate minerals.

[0029] (3) Characteristic index indicators: Calculate the chlor-alkali index to determine the direction and intensity of cation exchange; calculate the sodium adsorption ratio to assess the effect of cation exchange on sodium ion enrichment. The calculation formula is as follows: ; ; ; (4) Mineral saturation index: The saturation index of calcite (SI_c), dolomite (SI_d), gypsum (SI_g), and rock salt (SI_h) were calculated using PHREEQC hydrogeochemical simulation software. These indices were used to determine the dissolution and precipitation trends of each mineral and to invert the equilibrium state and evolution direction of the water-rock reaction. Saturation index SI>0: The groundwater is supersaturated with the mineral and there is a tendency to precipitate. Saturation index SI=0: The mineral is in a state of dissolution equilibrium. Saturation index SI<0: The mineral is unsaturated and there is a tendency to continue to dissolve.

[0030] The formula for the mineral saturation index is as follows: ; in: IAP is the product of the activities of the ions that make up the mineral in groundwater; Ksp is the ion activity product of the mineral when it is in dissolution equilibrium at a specific temperature.

[0031] (5) Auxiliary environmental indicators: The total dissolved solids (TDS), dissolved oxygen (DO), dissolved organic carbon (DOC), pH, iron (Fe), manganese (Mn) and other indicators are measured to determine the redox environment, the characteristics of organic matter input and the degree of mixing of shallow surface water.

[0032] The third step is to identify the characteristics of lithological boundaries and water source types. Based on the above indicator set, a characteristic identification system for different lithological boundaries and different water source types is established from the perspective of water-rock interaction processes. Characteristics of water-rock interaction at lithological boundaries: (1) Boundary between carbonate and sulfate rocks: When groundwater flows to this boundary, carbonate dissolution occurs simultaneously (CaCO3+H2O+CO2→Ca²).+ +2HCO3 - ) and sulfate dissolution (CaSO4→Ca²) + +SO4² - ), leading to Ca² + / Mg² + A ratio greater than 2 indicates that Ca² + / HCO3 - A ratio greater than 1 indicates that SO4² - When the concentration is greater than 100 mg / L, the gypsum saturation index is unsaturated (SI_g<0), indicating that sulfate minerals continue to dissolve. (2) The boundary zone between mudstone, shale or coal-bearing strata rich in clay minerals: When groundwater meets the strata rich in clay minerals, reverse cation exchange occurs (2Na + (Adsorption) + Ca² + (Water) → Ca² + (Adsorption) + 2Na + (Water)), resulting in negative values ​​for both the chlor-alkali indices CAI-1 and CAI-2, Na + / Cl - A ratio greater than 1 indicates that Ca² + Mg² + The concentration is relatively low, and the TDS is at a moderate level, between 500 and 1500 mg / L. The calcite saturation index may be in a supersaturated state. (3) Evaporite layer boundary zone: When groundwater flows to evaporite layers such as rock salt and potash, salt dissolution occurs (NaCl → Na + +Cl - ), leading to Na + / Cl - The ratio is close to 1, Cl - The concentration abnormally increased to more than 500 mg / L, TDS greater than 2000 mg / L, and the rock salt saturation index was unsaturated, i.e., SI_h < 0. (4) Sulfide strata boundary zone: When groundwater meets strata containing pyrite and other sulfides, sulfide oxidation occurs (FeS2 + 3.5O2 + H2O → Fe²). + +2SO4² - +2H + ), producing sulfuric acid and lowering the pH, leading to SO4²⁻ - The concentration increased significantly to greater than 200 mg / L, Ca² + / HCO3 - When the ratio is greater than 1, the pH is weakly acidic to neutral, between 5.5 and 7.0, the concentrations of Fe and Mn are high, and the dissolved oxygen content is low, generally less than 3 mg / L.

[0033] Identification of water source types: (1) Direct recharge by atmospheric precipitation: Groundwater has a short runoff path and a short water-rock contact time, and the water-rock interaction is weak, which is reflected in TDS less than 200mg / L and Na + / Cl - The ratio is close to or slightly higher than that of seawater (0.86). The hydrochemical type is mainly Na-Cl or Ca-HCO3. The dissolved oxygen is greater than 5 mg / L. The mineral saturation index is unsaturated. (2) Lateral recharge of shallow surface water: Groundwater is recharged by surface water bodies, carrying nitrates, dissolved oxygen and organic matter input from the surface, which manifests as NO3. - Concentrations are high, exceeding 20 mg / L; dissolved oxygen is greater than 5 mg / L; DOC content is high; Cl... - With NO3 - / Cl - The relationship diagram shows a linear distribution, with TDS ranging from 200 to 500 mg / L. (3) Deep confined water recharge: Groundwater has a long flow path and sufficient water-rock contact time, undergoing carbonate dissolution, silicate hydrolysis, and cation exchange, resulting in TDS greater than 500 mg / L and Na + / Cl - The ratio is much greater than 1 due to the enrichment of sodium by silicate hydrolysis or cation exchange, or much less than 1 due to the residue of ancient seawater. The water chemistry type is mainly Na-HCO3 or Na-Cl, the dissolved oxygen is less than 2 mg / L, and the saturation index of calcite and dolomite is saturated (SI_c>0), indicating that the water-rock reaction is close to equilibrium. (4) Residual of ancient seawater: The groundwater is ancient seawater sealed during geological history. It has undergone long-term water-rock interaction but has retained the basic characteristics of seawater, which is manifested as Na + / Cl - The ratio is close to 0.86, Cl - Concentration greater than 1000 mg / L, TDS greater than 3000 mg / L, Br - / Cl - Between 0.0015 and 0.002, the water chemistry type is Na-Cl type, and the dissolved oxygen is extremely low, less than 1 mg / L. (5) Mixed recharge from different aquifers: Groundwater is formed by the mixing of two or more water sources. The water-rock interaction is manifested as the superposition of multiple end-members, and the characteristic ion ratio is such as Na + / Cl - Ca² + / Mg² + It lies between two end-source water sources, and its mineral saturation index lies between the two end-source water sources.

[0034] The fourth step is the identification criteria and comprehensive analysis. Based on the above indicator set and the characteristics of water-rock interaction, quantitative identification criteria are established, and comprehensive verification is carried out using multivariate statistical analysis methods. The final conclusion is drawn through step-by-step analysis: Quantitative identification criteria for lithological boundary zones: (1) Boundary zone between carbonate and sulfate rocks: Ca² + / Mg² + >2, Ca² + / HCO3 - >1, SO4² - >100mg / L, gypsum saturation index SI_g<0. (2) Mudstone, shale or coal-bearing strata boundary zone rich in clay minerals: chloride-alkali index CAI-1<0, CAI-2<0, Na + / Cl - >1, TDS is 500-1500 mg / L, sodium adsorption ratio SAR>2, SI_c>0. (3) Evaporation rock boundary zone: Na + / Cl - The ratio is between 0.8 and 1.2, Cl - >500mg / L, TDS>2000mg / L, rock salt saturation index SI_h<0. (4) Sulfide stratigraphic boundary zone: SO4² - >200mg / L, Ca² + / HCO3 - >1, pH between 5.5 and 7.0, Fe >0.5 mg / L or Mn >0.1 mg / L, dissolved oxygen <3 mg / L.

[0035] Quantitative identification criteria for water source type: (1) Direct recharge from atmospheric precipitation: TDS < 200 mg / L, DO > 5 mg / L, Na + / Cl - The ratio is between 0.8 and 1.0, and the calcite saturation index SI_c < 0. (2) Lateral recharge of shallow surface water: NO3 - >20mg / L, DO>5mg / L, TDS is 200-500mg / L, DOC>2mg / L. (3) Deep confined water recharge: TDS>500mg / L, DO<2mg / L, Na + / Cl - The ratio is >1.5 or <0.5, the calcite saturation index SI_c >0, and the dolomite saturation index SI_d >0. (4) Ancient seawater residue: Na + / Cl - The ratio is between 0.8 and 0.9, Cl - >1000mg / L, TDS>3000mg / L, Br - / Cl - The ratio is between 0.0015 and 0.002. (5) Mixed recharge from different aquifers: data such as ion concentration and characteristic ion ratio are between the two end-source water sources.

[0036] In this embodiment, as Figure 2 As shown, for water sample parameters identified as belonging to the water-rich lithological boundary zone and the water supply source, the following steps are also included: By combining quantitative identification criteria with multivariate statistical analysis, and through a verification mechanism of mutual corroboration and stepwise convergence, the identification results of water-rich lithological boundaries and water recharge sources are comprehensively verified and corrected. Specifically, the following steps are included: Step 1: Data Standardization and Preprocessing. Based on the water chemistry index set established in Step 2 of the above method, including the concentration of major ions, the ratio of characteristic ions, characteristic indices, mineral saturation indices, and auxiliary environmental indicators, all water sample data are standardized to eliminate the influence of dimensions and construct the original data matrix.

[0037] In this embodiment, z-score standardization is used, and the calculation formula is as follows: ; in, Let be the standardized value of the i-th water sample for the j-th index; Let be the original measured value of the i-th water sample on the j-th index, and n be the total number of water samples; The arithmetic mean of all water samples for the j-th index; Let be the standard deviation of all water samples on the j-th index.

[0038] Step two: Verification of the combination of Q-type cluster analysis and quantitative identification criteria. Using Q-type cluster analysis, with water samples as the object, and based on the standardized data matrix from step one, the similarity distance between water samples is calculated. The distance is calculated using the Euclidean distance formula: ; in: Let be the Euclidean distance between the i-th water sample and the k-th water sample; Let be the standardized value of the i-th water sample for the j-th index; This is the standardized value of the k-th water sample for the j-th index; This represents the total number of indicators participating in the cluster analysis.

[0039] Based on distance calculation, the Ward method (also known as the sum of squared deviations method) is used for hierarchical clustering. The basic idea of ​​this method is to merge two classes at each step, minimizing the increase in the sum of squared deviations within each merged class. The sum of squared deviations within a class is defined as the sum of the squared Euclidean distances from all water samples in that class to the center of that class.

[0040] For a certain class A, its sum of squared deviations is: ; in: This is the vector of the center of class A, i.e., the mean values ​​of all indicators in that class; The number of water samples of class A.

[0041] When considering merging two different classes A and B into a new class AB, the resulting increase in the sum of squared deviations is: ; Wardfa makes choices at every step The two smallest classes are merged. Initially, each water sample belongs to its own class. The two water samples with the closest Euclidean distance are selected for merging. The samples are then repeatedly merged until all water samples are grouped into one large category, thus generating a clustering dendrogram. By cutting the dendrogram at a suitable distance threshold, the water samples can be divided into several groups with similar hydrochemical characteristics.

[0042] The cluster analysis results are spatially superimposed and cross-referenced with the lithological boundary zone types and water source types identified according to the quantitative identification criteria in step four. This process is not a simple superposition comparison, but a mutual verification mechanism designed in this invention. First, for each cluster, the frequency of each water sample's type classification under the quantitative identification criteria is counted, and the type consistency index within the cluster is calculated, i.e., the percentage of water samples of the same type in the total number of water samples in the cluster. If the consistency index of the cluster is greater than 90%, and the spatial location of all water samples in the cluster is within the corresponding lithological boundary zone or hydrogeological unit indicated by the geological data, it is judged as strongly consistent. In this case, the quantitative identification criteria and cluster analysis mutually verify each other, directly outputting a high-confidence identification conclusion. If the consistency index is between 70% and 90%, or there is a partial offset in the spatial superposition but the centroid of the cluster is still within the corresponding geological partition, it is judged as weakly consistent. In this case, principal component analysis results need to be introduced for auxiliary verification. If the consistency index is less than 70%, or the spatial distribution of the cluster does not correspond to any known geological partition, it is judged as weakly consistent. If no corresponding relationship exists, it is judged as inconsistent. At this time, the system automatically identifies the group as a mixed influence zone or a data anomaly zone. For inconsistent groups, further analysis is conducted to see if the quantitative identification results of each water sample show two or more types coexisting but are grouped into one category by clustering. If so, it is identified as a composite zone influenced by multiple water sources or multiple lithologies, and the conclusion is marked as mixed or composite. At the same time, the order of dominant and secondary types is given according to the proportion of each type of water sample in the group. If not, the key ion concentrations of the original data are checked, and after confirming the data quality, it is decided to remove or mark it as a local anomaly. Through this progressive mutual verification mechanism based on consistency index grading, spatial superposition verification, and anomaly screening, this invention elevates cluster analysis from a simple classification tool to an objective verification module for quantitative identification standards, realizing deep coupling between empirical thresholds and data structures, and significantly enhancing the reliability and engineering applicability of the identification results.

[0043] Step 3: Verification of the combination of principal component analysis and quantitative identification criteria. This invention does not use principal component analysis as an independent dimensionality reduction or classification tool, but rather designs it as a statistical verification module for quantitative identification criteria. The specific verification process is as follows: First, principal component extraction was performed on the standardized hydrochemical data to obtain the loading matrix of each principal component.

[0044] This embodiment establishes a direct mapping rule between load combinations and lithological boundary zone types: if Ca² in a certain principal component... + Mg² + HCO3 - The absolute values ​​of the loadings are all greater than 0.7, and SO4² in the same or another principal component - Ca² +If the absolute values ​​of the loads are all greater than 0.7, it is determined to represent the combined effects of carbonate and sulfate dissolution, corresponding to the boundary zone between carbonate and sulfate rocks; if Na in a certain principal component + Cl - The absolute values ​​of the loads are all greater than 0.7, and Ca² + Mg² + If the loading is significantly low or negative, it is determined to represent a cation exchange process, corresponding to the boundary zone of mudstone, shale, or coal-bearing strata rich in clay minerals; if the Na content of a certain principal component is significantly low or negative, it indicates a cation exchange process. + Cl - The absolute values ​​of the loads are all greater than 0.7, and combined with the original data, Cl - If the concentration is greater than 500 mg / L and the TDS is greater than 2000 mg / L, it is determined to represent the evaporite dissolution process, corresponding to the evaporite layer boundary zone; if Fe, Mn and SO4²⁻ are present in a certain main component... - If the absolute values ​​of the loads are all greater than 0.7, it is determined that they represent sulfide oxidation processes, corresponding to sulfide strata boundaries. Based on the strength of the load combinations, one or more dominant water-rock processes can be identified.

[0045] Secondly, the dominant process identified by the above loads is compared item by item with the lithological boundary zone type inferred by the quantitative identification criteria in step four.

[0046] The comparison rules are as follows: If the quantitative identification standard identifies a water sample or a region as a boundary zone between carbonate and sulfate rocks, then the loading matrix should simultaneously show high-load Ca² values. + Mg² + HCO3 - Combining SO4² to represent carbonate dissolution and high loading - Ca² + The combination represents sulfate dissolution; if the quantitative identification criteria identify it as a boundary zone of clay mineral-rich mudstone, shale, or coal-bearing strata, then the loading matrix should show high Na loadings. + Cl - Combination and Ca² + Mg² + A significantly low or negative loading indicates cation exchange; if the quantitative identification criteria identify it as an evaporite layer boundary, then the loading matrix should show a high Na loading. + Cl - Combining, and combining with Cl in the original data - A concentration greater than 500 mg / L and a TDS greater than 2000 mg / L are considered indicative of evaporite dissolution. If the quantitative identification criteria identify it as a sulfide stratigraphic boundary, then the loading matrix should show high loads for Fe, Mn, and SO4²⁻. - The combination represents sulfide oxidation.

[0047] Next, a tiered judgment is made based on the comparison results. When the dominant process of load identification is completely consistent with the quantitative identification standard, the verification is considered successful. When the dominant process of load identification only partially matches, it is considered partial verification, and it is recommended to increase sampling density in the corresponding area. When the dominant process of load identification completely contradicts the quantitative identification standard, the verification is considered unsuccessful, triggering an anomaly review: further analysis of the water sample, or determination of whether the threshold of the quantitative identification standard is inapplicable in the corresponding area.

[0048] Step 4: Outputting the comprehensive identification conclusion. Based on the clustering verification results from Step 2 and the principal component analysis results from Step 3, this embodiment establishes a three-level confidence level identification rule. For the type of water-rich lithological boundary zone: when the quantitative identification standard, Q-type cluster analysis, and principal component analysis are completely consistent (i.e., the consistency index of the cluster groups is greater than 90%, and the principal component loading combination completely matches the water-rock interaction type inferred by the quantitative standard), a high-confidence identification conclusion is output, directly determining the spatial location and type of the water-rich lithological boundary zone; when two of the three methods are consistent and the other method is partially consistent (e.g., the clustering verification is strongly consistent but the principal component analysis is only partially consistent), a medium-confidence identification conclusion is output, and the conclusion indicates the steps requiring further intensive sampling or verification. When there are significant contradictions among the three conclusions, a comprehensive assessment process is triggered: cross-analysis is performed using regional geological background data to identify the causes of the contradictions, such as mixed water sources, multiple lithological complexes, local data anomalies, or inapplicable thresholds. Based on this, a revised identification conclusion is given, along with suggestions for subsequent verification, such as supplementary sampling, adjustment of identification thresholds, or conducting tracer experiments. Regarding the type of groundwater recharge source: the comprehensive results of quantitative identification criteria and cluster analysis are used as the standard, with principal component analysis results used as a reference for verification. The verification process involves first extracting principal components from the standardized hydrochemical data and checking whether NO3, representing a shallow oxidation environment, appears in the loading matrix. - The absolute values ​​of DO and DOC loads are all greater than 0.5 and TDS and Cl - Low load, or deep reduction environment, i.e., TDS, Na + Cl - Load greater than 0.6 and DO, NO3 -Auxiliary principal components with negative loadings are used; then, these water source indicative principal components, such as PC2 and PC3, are selected to draw a two-dimensional score map, and representative water samples of known water source types, such as shallow well water as atmospheric precipitation end-members and deep confined water boreholes as overflow recharge end-members, are marked as end-member reference points on the map; if the projection position of the water sample to be identified falls near a certain end-member, it is judged as reference consistency, providing support for the conclusions of quantitative identification and cluster analysis; if it falls between two end-members, it is judged as reference mixing, indicating that there may be mixed recharge; if it deviates significantly from all known end-members, it is judged as reference inconsistency, triggering comprehensive judgment. The final confidence level of the water source type is determined based on a combination of quantitative identification criteria and the consistency index of cluster analysis: if the consistency index of the clusters is greater than 90% and the principal component projection references are consistent, the confidence level is high; if the consistency index is between 70% and 90% and the principal component projection references are consistent, the confidence level is medium; if the principal component projection result is a reference mixture, it indicates the possibility of mixed replenishment, requiring comprehensive judgment based on both quantitative identification criteria and cluster analysis, and the confidence level is not directly output; if the consistency index is less than 70% or the principal component projection references are inconsistent, a comprehensive judgment is made directly. The final water source identification conclusion is still based on the combined results of quantitative identification criteria and cluster analysis, with the principal component analysis score projection result serving as an auxiliary basis for confidence level determination, thereby achieving quantifiable and traceable auxiliary verification of water source type identification. Through this three-level confidence level output rule, this invention achieves quantifiable, traceable, and verifiable identification results, providing a clear and reliable decision-making basis for the risk assessment and prevention of water inrush in tunnel engineering. The final identification conclusions include: the spatial location and type of the water-rich lithological boundary zone, the type of groundwater recharge source, and are accompanied by the confidence level and necessary verification explanations.

[0049] In summary, this embodiment is based on the characteristic water-rock interactions between groundwater and different lithologies during runoff, including carbonate dissolution, sulfate dissolution, silicate hydrolysis, cation exchange, and redox reactions. These processes are controlled by the lithological assemblage and hydrogeological conditions through which the water flows, and leave unique chemical characteristics in the water. A method for identifying the water-rich lithological boundary zone and recharge source in front of the tunnel using groundwater chemistry is proposed. By systematically analyzing the ionic composition, characteristic ratios, mineral saturation state, and multivariate statistical characteristics of groundwater, the lithological sequence and runoff path experienced by the groundwater can be deduced, thereby accurately identifying the spatial location of the water-rich lithological boundary zone and the recharge source of the groundwater.

[0050] Example 2 The first step was system site selection and sample collection. A tunnel project was used as the implementation target; the tunnel is 776m long with a maximum burial depth of 54m. According to geological survey data, the strata traversed by the tunnel from the entrance to the exit are as follows: carbonate rock area; 0-220m section, mainly limestone and dolomitic limestone, carbonate-sulfate boundary zone; 220-350m section, interbedded limestone with gypsum and anhydrite, sulfide strata boundary zone; 350-520m section, pyrite-bearing carbonaceous shale contact zone with limestone, evaporite strata boundary zone; 520-700m section, interbedded rock salt, potash, and mudstone; the exit section (700-776m) returns to the carbonate rock area. Fault zones are well-developed in the area, with fault F1 crossing the carbonate-sulfate boundary zone and fault F2 located within the sulfide strata boundary zone. The hydrogeological unit is divided into a shallow fractured aquifer system, mainly recharged by atmospheric precipitation, and a deep confined aquifer system, mainly recharged by regional overflow. Grouting was carried out during tunnel construction, with the grouting-affected areas concentrated in the 260-300m and 480-520m sections. Groundwater sampling points were systematically deployed along the tunnel's direction and surrounding area, covering different lithological zones, fault fracture zones, surface water bodies, and different depths. Multiple sampling phases were conducted during tunnel construction, collecting a total of 35 water samples. Before sampling, parameters such as pH and dissolved oxygen (DO) were measured on-site, and the samples were sealed, refrigerated, and sent to the laboratory for analysis.

[0051] The second step is to establish a set of water chemistry indicators. Water quality analysis is performed on each water sample to determine the indicators used for identification: the main ion Ca²⁺. + Mg² + Na + HCO3 - SO4 2- Cl - NO3 - The mass concentration; auxiliary indicators: total dissolved solids, dissolved oxygen, pH, Fe, Mn. Calculate the characteristic ion ratio Ca². + / Mg² + Ca² + / HCO3 - Na + / Cl - Calculate the chlor-alkali indices CAI-1 and CAI-2; calculate the calcite saturation index (SI_c), gypsum saturation index (SI_g), and rock salt saturation index (SI_h) using PHREEQC. Remove unqualified data by verifying the charge balance of anions and cations (error <5%).

[0052] The third step is to identify the characteristics of lithological boundaries and water source types. Based on the key indicators of water samples from different mileage sections, the water-rock interaction characteristics and water supply types of each lithological boundary zone are identified.

[0053] In the carbonate rock area, 0-220m, outside the grouting-affected section: a water sample taken from the working face at mileage 70m showed a pH of 7.4, TDS of 186 mg / L, DO of 6.3 mg / L, and Ca²⁺ of... + / Mg² + The ratio is 3.27, Ca² + / HCO3 - The ratio is 0.44, Na + / Cl - The ratio is 0.88, and SI_c is -0.18. At a water sample taken at 150m, Ca²... + / Mg² + The ratio is 3.29, Ca² + / HCO3 - The ratio is 0.44, Na + / Cl - The ratio is 0.89, and SI_c is -0.09. This indicates that the main process in this section is carbonate dissolution, influenced by atmospheric precipitation and lateral recharge from shallow surface water.

[0054] Shallow well water sample, representing direct atmospheric precipitation recharge: pH 7.1, TDS 142 mg / L, DO 7.5 mg / L, Na... + / Cl - The ratio is 0.87 and SI_c is -0.62, indicating that it is directly supplied by atmospheric precipitation.

[0055] Carbonate-sulfate interface zone, 220-350m, avoiding the grouting section: water sample taken at 250m, pH 7.2, Ca²⁺ + / Mg² + The ratio is 5.42, Ca² + / HCO3 - The ratio is 1.07, SO4 2- The concentration was 162 mg / L, and SI_g was -0.41. In a water sample taken at mileage 310 m, Ca²... + / Mg² + The ratio is 5.47, Ca² + / HCO3 - The ratio is 1.11, SO4 2- The concentration is 178 mg / L, and SI_g is -0.38. This satisfies the Ca² standard. + / Mg² + >2. Ca² + / HCO3 - 1. SO4 2- With a concentration >100 mg / L and SI_g <0, it is identified as a boundary zone between carbonate and sulfate rocks.

[0056] In the grouting-affected zone, 260-300m and 480-520m: Borehole water samples taken within the grouting section at mileage 280m showed a pH of 10.5 and a Ca²⁺ content of [missing information]. + The concentration is 28 mg / L, Mg² + Below 0.5 mg / L, Na + / Cl - The ratio was 3.31, CAI-1 was -1.78, CAI-2 was -4.56, and SI_c was 1.42. Borehole water samples taken within the 500m grouting section had a pH of 10.1 and Ca²⁺... + The concentration is 24 mg / L, Na + / Cl - The ratio is 3.16, CAI-1 is -1.65, CAI-2 is -4.28, and SI_c is 1.35. This characteristic differs from natural water-rock interaction and is identified as a special chemical boundary zone formed by the influence of artificial materials.

[0057] At the sulfide strata boundary, 350-520m, avoiding the grouting section: a water sample taken at mileage 390m showed a pH of 6.1 and high SO4 content. 2- The concentration is 288 mg / L, Ca² + / HCO3 - The ratio was 1.58, the Fe concentration was 0.91 mg / L, and the DO concentration was 1.9 mg / L. A water sample taken at a distance of 450 m had a pH of 5.9 and an SO42- concentration of [missing information]. 2- The concentration is 315 mg / L, Ca² + / HCO3 - The ratio is 1.65, the Fe concentration is 1.12 mg / L, and the DO concentration is 1.6 mg / L. This satisfies the SO42- requirement. 2- >200mg / L, Ca² + / HCO3 - >1. pH 5.5-7.0, Fe > 0.5 mg / L, DO < 3 mg / L, identified as a sulfide stratum boundary zone, with recharge mainly from deep confined water flow.

[0058] Evaporite layer boundary zone, 520-700m: Water sample at mileage 570m, Na + / Cl - The ratio is 1.02, Cl - The concentration was 635 mg / L, TDS was 2780 mg / L, and SI_h was -0.28. At a water sample taken at mileage 640 m, Na... + / Cl - The ratio is 1.01, Cl - The concentration was 685 mg / L, TDS was 2950 mg / L, and SI_h was -0.32. At a water sample taken at 680 m, Na... + / Cl- The ratio is 1.01, Cl - The concentration is 608 mg / L, TDS is 2640 mg / L, and SI_h is -0.25. This satisfies the Na... + / Cl - 0.8-1.2, Cl - The concentrations were >500 mg / L, TDS >2000 mg / L, and SI_h <0, indicating an evaporite layer boundary zone, with recharge source being deep confined water overflow recharge.

[0059] Outflow carbonate rock zone, 700–776m: Water sample at mileage 730m, TDS 445 mg / L, DO 3.2 mg / L, Ca² + / Mg² + The ratio was 3.29, and SI_c was 0.08. The TDS of this water sample was between that of the shallow atmospheric precipitation recharge endmember (TDS < 200 mg / L) and the deep confined water overflow recharge endmember (TDS > 500 mg / L). DO was between these two endmembers. Na... + / Cl - The ratio is 1.08, which falls between the atmospheric precipitation end-member (0.8-1.0) and the deep confined water end-member (greater than 1.5). Based on the identification characteristics of mixed recharge from different aquifers in this invention, it is identified as a mixed recharge type of atmospheric precipitation and deep confined water.

[0060] like Figure 3 - Figure 7 As shown, the fourth step is the identification criteria and comprehensive analysis. The above indicators are compared with the quantitative standards: the carbonate-sulfate interface satisfies Ca²... + / Mg² + >2. Ca² + / HCO3 - 1. SO4 2- >100 mg / L, SI_g <0; the sulfide stratigraphic boundary zone satisfies SO4 2- >200mg / L, Ca² + / HCO3 - 1. pH 5.5-7.0, Fe > 0.5 mg / L, DO < 3 mg / L; the boundary zone of the evaporite layer satisfies Na + / Cl - 0.8-1.2, Cl - >500mg / L, TDS>2000mg / L, SI_h<0; direct atmospheric precipitation recharge meets TDS<200mg / L, DO>5mg / L, Na + / Cl - 0.8-1.0, SI_c<0; Deep confined water recharge meets TDS>500mg / L, DO<2mg / L, Na+ / Cl - >1.5, SI_c>0, SI_d>0. The grouting-affected zone does not meet the natural standards, exhibiting high pH and low Ca². + , Gao Na + The presence of a negative chlor-alkali index and SI_c supersaturation indicates an artificial chemical boundary zone. Preliminary delineation includes: a 0-220m carbonate rock zone, primarily fed by atmospheric precipitation; a 220-350m carbonate-sulfate boundary zone, with a mixture of atmospheric precipitation and shallow surface water; a 350-520m sulfide strata boundary zone, primarily fed by deep confined aquifers; a 520-700m evaporite strata boundary zone, with deep confined aquifers; and a 700-776m carbonate rock zone, replenished by a mixture of atmospheric precipitation and deep confined aquifers.

[0061] Next, we will verify: Data standardization and preprocessing. z-score standardization was performed on 35 sets of water sample data.

[0062] Verification using a combination of Q-type cluster analysis and quantitative identification criteria. Euclidean distance and Ward's method were used for systematic clustering, dividing the water samples into five groups: Group I: Shallow well water + tunnel entrance section (10 samples); Group II: Carbonate-sulfate boundary zone (ungrouted section) (7 samples); Group III: Sulfide strata boundary zone (ungrouted section) (8 samples); Group IV: Evaporite boundary zone (5 samples); Group V: Grouting-affected area (5 samples). Group I showed a consistency index of 100% (strong consistency); Group II showed a consistency index of 100% (strong consistency); Group III showed a consistency index of 87.5% (weak consistency, requiring principal component analysis); Group IV showed a consistency index of 100% (strong consistency); and Group V showed a consistency index of 100% (independent group).

[0063] Validation of the combination of principal component analysis and quantitative identification criteria. The cumulative variance contribution rate of the first three principal components is 83.2%. Loading matrix: Ca² in PC1 + Mg² + HCO3 - Loads > 0.7 indicate carbonate dissolution; SO4 in PC2 2- Fe and Mn loadings >0.7 indicate sulfide oxidation and sulfate dissolution; Na in PC3 + Cl -A load > 0.7 indicates cation exchange, specifically a negative CAI load absolute value > 0.7. Comparison results: Group I represents a carbonate rock region primarily fed by precipitation, with high loads on PC1 and lower loads on PC2 and PC3, validating the design. Group II represents a carbonate-sulfate boundary zone, with high loads on both PC1 and PC2, validating the design. Group III represents a sulfide strata boundary zone, with high load on PC2, validating the design. Group IV represents an evaporite boundary zone, with high load on PC3 and low loads on PC1 and PC2, validating the design. Group V represents a grouting-affected area, with a load pattern containing high pH and low Ca². + High K + Unlike natural features, it was determined to be an artificial anomaly.

[0064] Furthermore, to verify the water source type, the presence of indicative combinations of water sources was checked in the load matrix. The results showed that TDS and Na in PC3... + Cl - All loads are greater than 0.6, and the DO load is -0.5, NO3 - A load of -0.4 represents a deep reduction environment; NO3 in PC2 - The DO loads were 0.3 and 0.2 respectively, not forming a high load combination. Score maps were plotted using PC2 and PC3, with shallow well water and deep borehole water as reference points. The projection showed that Groups I and II were consistent with the reference point when close to the well end-member; Groups III and IV were consistent with the reference point when close to the deep borehole end-member; and Group V was inconsistent with the reference point when deviating from all end-members, triggering a comprehensive assessment indicating the influence of grouting. This reference verification result supports the quantitative identification and cluster analysis conclusions regarding the water source.

[0065] Comprehensive judgment conclusions are output. High confidence: The 0-220m carbonate rock area is recharged by atmospheric precipitation; the 220-350m carbonate-sulfate boundary zone is recharged by a mixture of atmospheric precipitation and shallow surface water; the 520-700m evaporite layer boundary zone is recharged by deep confined water overflow; and the 700-776m carbonate rock area is recharged by a mixture of atmospheric precipitation and deep confined water, i.e., a mixed transition zone.

[0066] Medium confidence level: The sulfide strata boundary zone at 350-520m is mainly recharged by deep confined water flow; it is recommended to increase sampling density at 410m and 490m. Special indication: The grouting-affected zones at 260-300m and 480-520m are artificial chemical boundaries and do not belong to natural water-rich structures.

[0067] Final output: Within the 776m length of the tunnel, the following zones are identified: 0-220m is a carbonate rock zone, a non-water-rich lithological boundary zone, primarily replenished by atmospheric precipitation; 220-350m is a carbonate-sulfate boundary zone, a water-rich lithological boundary zone, replenished by a mixture of atmospheric precipitation and shallow surface water; 350-520m is a sulfide stratum boundary zone, a water-rich lithological boundary zone, primarily replenished by deep confined water overflow; 520-700m is an evaporite stratum boundary zone, a water-rich lithological boundary zone, replenished by deep confined water overflow; and 700-776m is a carbonate rock zone, a non-water-rich lithological boundary zone, replenished by a mixture of atmospheric precipitation and deep confined water. In the above conclusions, 0-220m, 220-350m, 520-700m, and 700-776m are considered high confidence levels, 350-520m is considered medium confidence level and it is recommended to increase sampling frequency, and the grouting-affected areas of 260-300m and 480-520m have been separately identified as artificial chemical boundary zones.

[0068] Example 3 A system for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel includes: The parameter acquisition module is configured to acquire water sample parameters from each groundwater sampling point. The index set construction module is configured to perform water quality analysis and establish an index set covering multi-dimensional information to characterize the intensity and characteristics of different water-rock interaction processes. The index set includes ion concentration, ion ratio, characteristic index, mineral saturation index, and auxiliary environmental indicators. The feature recognition module is configured to establish a feature recognition system for different lithological boundary zones and different water source types from the perspective of water-rock interaction processes, based on the index set. The initial identification module is configured to establish quantitative identification criteria based on the index set and feature recognition system, and to conduct comprehensive verification by combining multivariate statistical analysis methods. Through step-by-step analysis, the identification results of lithological boundary zones and water source types are obtained as the initial identification results. The preprocessing module is configured to preprocess the data parameters of water samples identified as water-rich lithological boundary zones and water supply sources. The clustering verification module is configured to calculate the similarity distance between each water sample based on the preprocessed data, perform clustering analysis based on the similarity distance, and spatially overlay and cross-compare the clustering results with the initial identification results to achieve clustering verification. The principal component verification module is configured to extract principal components based on preprocessed data, obtain the loading matrix of each principal component, compare it item by item with the initial identification results, and make a graded judgment based on the comparison results to achieve principal component verification. The comprehensive judgment module is configured to combine the results of cluster verification and principal component verification to correct the spatial location and type of the water-rich lithological boundary zone in the initial identification results, and obtain the final result.

[0069] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of one or more computer-usable storage media (including, but not limited to, disk storage, etc.) containing computer-usable program code. CD - ROM It takes the form of a computer program product implemented on (such as optical memory, etc.).

[0070] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0071] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0072] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0073] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made by those skilled in the art without creative effort within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel, characterized in that, Includes the following steps: Obtain water sample parameters from each groundwater sampling point; Water quality analysis is conducted to establish a set of indicators covering multiple dimensions of information, which is used to characterize the intensity and characteristics of different water-rock interaction processes. The set of indicators includes ion concentration, ion ratio, characteristic index, mineral saturation index, and auxiliary environmental indicators. Based on the aforementioned index set, a feature identification system for different lithological boundary zones and different water source types is established from the perspective of water-rock interaction processes. Based on the aforementioned index set and feature identification system, a quantitative identification standard is established, and a comprehensive verification is performed using multivariate statistical analysis methods. Through step-by-step analysis, the identification results of lithological boundary zones and water source types are obtained as initial identification results. Data preprocessing was performed on water sample parameters identified as water-rich lithological boundary zones and water supply sources. Based on the preprocessed data, the similarity distance between each water sample is calculated, and cluster analysis is performed based on the similarity distance. The cluster results obtained from the cluster analysis are spatially superimposed and cross-compared with the initial identification results to achieve cluster verification. Based on the preprocessed data, principal component extraction is performed to obtain the loading matrix of each principal component. The loading matrix is ​​then compared with the initial identification results item by item. Based on the comparison results, a hierarchical judgment is made to achieve principal component verification. By combining the results of clustering verification and principal component verification, the spatial location and type of the water-rich lithological boundary zone in the initial identification results were corrected to obtain the final result.

2. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, The process of obtaining water sample parameters from various groundwater sampling points includes: based on the geological survey data, lithological combination zoning, fault zone distribution and hydrogeological unit division of the target area, systematically deploying groundwater sampling points along the tunnel and surrounding areas. The sampling points cover different lithological zones, fault fracture zones, surface water bodies and groundwater at different depths. Multiple sampling sessions are conducted during the tunnel construction and operation periods to obtain water samples that are representative of time and space.

3. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, The indicator set includes: The main ion concentration indicators, including the mass concentrations of the main anions and cations, serve as the basic data for hydrochemical characteristics to reflect the fundamental features of carbonate dissolution, sulfate dissolution, and evaporite dissolution in water-rock processes. Characteristic ion ratio index, calculates the molar ratio of each major anion and cation, used to distinguish the contribution ratio of carbonate dissolution and sulfate dissolution, judge the influence of evaporite dissolution, and identify the hydrolysis and cation exchange of silicate minerals; Characteristic index indicators include the chlor-alkali index and sodium adsorption ratio. The chlor-alkali index is used to determine the direction and intensity of cation exchange, while the sodium adsorption ratio is used to assess the effect of cation exchange on sodium ion enrichment. Mineral saturation indexes, including calcite saturation index, dolomite saturation index, gypsum saturation index, and rock salt saturation index, are used to determine the dissolution and precipitation trends of each mineral and to invert the equilibrium state and evolution direction of water-rock reactions. Auxiliary environmental indicators, including total dissolved solids, dissolved oxygen, dissolved organic carbon, pH, iron, and manganese, are used to assess redox environment, organic matter input characteristics, and the degree of mixing with shallow surface water.

4. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, Based on the aforementioned index set, the process of establishing a feature identification system for different lithological boundaries and different water source types from the perspective of water-rock interaction processes includes: The water-rock interaction characteristics of lithological boundary zones include several types: the boundary zone between carbonate and sulfate rocks, the boundary zone between mudstone, shale or coal-bearing strata rich in clay minerals, the boundary zone between evaporite strata, and the boundary zone between sulfide strata. The corresponding manifestations or value ranges of each type of water-rock interaction are analyzed in the index set, and the correlation is established. The characteristics of water source types include: direct recharge from atmospheric precipitation, lateral recharge from shallow surface water, cross-flow recharge from deep confined water, paleosea remnants, and mixed recharge from different aquifers. The corresponding manifestations or value ranges of the indicators in each water source type are analyzed, and the correlation is established.

5. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, The process of data preprocessing for water sample parameters identified as water-rich lithological boundary zones and water supply sources includes: standardizing all water sample data based on the main ion concentrations, characteristic ion ratios, characteristic indices, mineral saturation indices, and auxiliary environmental indicators of the index set, eliminating the influence of dimensions, and constructing the original data matrix.

6. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, The process of calculating the similarity distance between water samples and performing cluster analysis based on the similarity distance includes: calculating the similarity distance between water samples based on the standardized data matrix; using the Ward method (i.e., the sum of squared deviations method) to perform clustering based on the distance calculation until all water samples are merged into one large class, generating a cluster dendrogram; and dividing the water samples into several groups with similar hydrochemical characteristics by cutting at a set appropriate distance threshold according to the dendrogram.

7. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, The process of spatially overlaying and cross-comparing the cluster results obtained from cluster analysis with the initial identification results includes: spatially overlaying and cross-comparing the cluster results obtained from cluster analysis with the lithological boundary zone type and water source type identified in the initial identification; for each cluster, the frequency of the type of each water sample under the quantitative identification standard is counted, and the type consistency index within the cluster is calculated, which is the percentage of the number of water samples of the same type to the total number of water samples in the cluster. If the consistency index of the cluster is greater than the first set value, and the spatial location of all water samples in the cluster is within the corresponding lithological boundary zone or hydrogeological unit range indicated by the geological data, it is judged as strongly consistent, and a high-confidence identification conclusion is obtained. If the consistency index is between the first and second set values, or if there is a partial offset in the spatial superposition but the centroid of the group is still within the corresponding geological zone, it is judged as weak consistency, and the principal component analysis results are introduced for auxiliary verification. If the consistency index is lower than the second set value, or if the spatial distribution of the taxonomy does not correspond to any known geological division, it is judged as inconsistent, and the taxonomy is identified as a mixed influence area or a data anomaly area.

8. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 7, characterized in that, For inconsistent clusters, analyze whether the quantitative identification results of each water sample show two or more types coexisting but are classified into one category by clustering. If so, identify it as a composite zone influenced by multiple water sources or multiple lithologies, and mark it as mixed or composite in the conclusion. At the same time, give the order of dominant and secondary types according to the proportion of each type of water sample in the cluster. If not, check the original data, confirm the data quality, and decide whether to remove or mark it as a local outlier.

9. The method for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel as described in claim 1, characterized in that, Based on the preprocessed data, principal component extraction is performed to obtain the loading matrix of each principal component. The loading matrix of each principal component is then compared with the initial identification results item by item. The classification is then performed based on the comparison results. The process of principal component verification includes: principal component extraction is performed on the standardized hydrochemical data to obtain the loading matrix of each principal component. Based on the pre-constructed direct mapping rule between the loading combination and the lithological boundary zone type, one or more dominant water-rock interaction processes are identified. The identified dominant process is compared item by item with the lithological boundary zone type of the initial identification result. The results are graded and judged according to the comparison. When the dominant process of load identification is completely consistent with the quantitative identification standard, it is judged as verified. When the dominant process of load identification only partially matches, it is judged as partially verified. It is also recommended to increase the sampling density in the corresponding area. When the dominant process of load identification completely contradicts the quantitative identification standard, it is judged as verified as not passing, triggering an abnormal review or determining whether the threshold of the quantitative identification standard is applicable.

10. A system for identifying the water-rich lithological boundary zone and water supply source in front of a tunnel, characterized in that, include: The parameter acquisition module is configured to acquire water sample parameters from each groundwater sampling point. The index set construction module is configured to perform water quality analysis and establish an index set covering multi-dimensional information to characterize the intensity and characteristics of different water-rock interaction processes. The index set includes ion concentration, ion ratio, characteristic index, mineral saturation index, and auxiliary environmental indicators. The feature recognition module is configured to establish a feature recognition system for different lithological boundary zones and different water source types from the perspective of water-rock interaction processes, based on the index set. The initial identification module is configured to establish quantitative identification criteria based on the index set and feature recognition system, and to conduct comprehensive verification by combining multivariate statistical analysis methods. Through step-by-step analysis, the identification results of lithological boundary zones and water source types are obtained as the initial identification results. The preprocessing module is configured to preprocess the data parameters of water samples identified as water-rich lithological boundary zones and water supply sources. The clustering verification module is configured to calculate the similarity distance between each water sample based on the preprocessed data, perform clustering analysis based on the similarity distance, and spatially overlay and cross-compare the clustering results with the initial identification results to achieve clustering verification. The principal component verification module is configured to extract principal components based on preprocessed data, obtain the loading matrix of each principal component, compare it item by item with the initial identification results, and make a graded judgment based on the comparison results to achieve principal component verification. The comprehensive judgment module is configured to combine the results of cluster verification and principal component verification to correct the spatial location and type of the water-rich lithological boundary zone in the initial identification results, and obtain the final result.

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