Method for environmental risk assessment of geophysical prospecting in groundwater enrichment area of subway construction zone

Abstract

This invention relates to the field of geophysical exploration technology and discloses a method for environmental risk assessment of geophysical mapping in groundwater-rich areas of subway construction zones. The method includes the following steps: S1, Data Acquisition and Fusion Step: Collecting ground-penetrating radar (GPR) data, surveying data, and engineering geological information from the subway construction area; spatially registering the GPR data and surveying data in a unified coordinate system to establish a comprehensive dataset containing the reflection characteristics of the subsurface medium and the spatial locations of surface and subsurface structures. By spatially registering and fusing GPR data, surveying data, and engineering geological information in a unified coordinate system, a comprehensive dataset containing the reflection characteristics of the subsurface medium and the precise spatial locations of surface and subsurface structures is established. This method overcomes the problem of disconnect between traditional geophysical interpretation and engineering spatial location, laying a reliable data foundation for subsequent accurate modeling and risk assessment.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration technology, specifically to a method for environmental risk assessment of geophysical mapping in groundwater-rich areas of subway construction zones. Background Technology

[0002] With the rapid development of urban rail transit construction, the geological environmental risks faced during subway construction are becoming increasingly prominent. Among them, water inrush and track bed voids caused by groundwater-rich areas are key factors affecting construction safety and structural stability. At present, the industry often uses geophysical exploration methods, especially ground-penetrating radar, to detect underground anomalies. Ground-penetrating radar can detect the distribution characteristics of underground media, including water-bearing areas, by emitting high-frequency electromagnetic waves and receiving their reflected signals in a non-invasive manner.

[0003] Existing technologies primarily rely on single ground-penetrating radar data to identify and interpret water-rich anomaly areas. These methods typically rely on single features such as enhanced reflected wave amplitude for judgment, lacking multi-feature fusion verification and systematic spatial integration with accurate surveying data and engineering geological information. This results in significant uncertainty in determining the spatial location, extent, and three-dimensional morphology of groundwater-rich areas, making it prone to misjudgment or omission, and failing to provide accurate spatial positioning basis for construction risks.

[0004] In the risk assessment stage, existing technology 2 often treats hydrogeological analysis and structural stability assessment as two separate steps. Even if water-rich areas are identified, the assessment of their impact on construction is mostly based on experience or qualitative analysis. It fails to quantitatively couple the three-dimensional spatial distribution of groundwater-rich areas, hydrogeological conditions such as stratum permeability, and the design parameters, load requirements, and stratum mechanical properties of the track bed structure. This method is difficult to accurately assess the interaction between water inrush potential and structural stability, and cannot form a comprehensive and quantitative environmental risk assessment result for the risk of track bed voiding. As a result, the construction plan is not targeted enough and there are potential safety hazards. Summary of the Invention

[0005] The purpose of this invention is to provide a method for environmental risk assessment of groundwater-rich areas in subway construction zones through geophysical mapping, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for environmental risk assessment of groundwater-rich areas in subway construction zones, comprising the following steps:

[0007] S1. Data Acquisition and Fusion Steps: Collect geological radar exploration data, surveying data and engineering geological information of the subway construction area, spatially register the geological radar exploration data and surveying data in a unified coordinate system, and establish a comprehensive dataset that includes the reflection characteristics of underground media and the spatial location of surface and underground structures.

[0008] S2. Three-dimensional geological and structural model construction steps: Based on the comprehensive dataset, identify the geophysical response characteristics of the groundwater-rich area and determine its three-dimensional spatial distribution. Combine the stratigraphic information in the engineering geological information with the track bed structure design parameters to construct a three-dimensional geological and structural model that reflects the spatial relationship between the groundwater-rich area, the stratigraphic interface and the track bed structure.

[0009] S3. Coupled assessment steps for water inrush and voiding risks: Based on the three-dimensional geological and structural model, analyze the spatial relationship between the groundwater-rich area and the track bed structure, as well as the geological medium conditions, couple the water inrush potential with the track bed structure stability requirements, and generate environmental risk assessment results for the risk of track bed voiding.

[0010] As a preferred embodiment of the present invention, the geophysical response characteristics of the groundwater-rich area identified in step S1 include:

[0011] Preprocessing of ground-penetrating radar exploration data to extract the amplitude, frequency, and phase characteristics of reflected waves;

[0012] Based on the characteristics of reflected waves, regions that meet at least two of the following characteristics are identified as water-rich anomaly zones: enhanced reflected wave amplitude, reduced reflected wave frequency, and the reflected wave phase axis exhibiting a continuous or hyperbolic shape.

[0013] The identified water-rich anomaly areas are compared and verified with known aquifers in the engineering geological information to determine the final three-dimensional spatial distribution of groundwater-rich areas.

[0014] As a preferred embodiment of the present invention, the construction of a three-dimensional geological and structural model reflecting the spatial relationship between the groundwater enrichment zone, the stratigraphic interface, and the roadbed structure in step S2 includes:

[0015] Based on the track bed structure design outline coordinates in the survey data, a three-dimensional surface model of the track bed structure is established.

[0016] Based on borehole data and stratigraphic information in engineering geological information, a three-dimensional model of key stratigraphic interfaces is constructed. Specifically, the spatial coordinates of control points of each stratigraphic interface revealed in the borehole data are used as known data. Between adjacent control points, a continuous and smooth surface is generated according to the stratigraphic attitude trend to form a three-dimensional model of key stratigraphic interfaces.

[0017] The three-dimensional spatial distribution of groundwater-rich areas, the three-dimensional surface model of the track bed structure, and the three-dimensional model of key strata interfaces are integrated and visualized in a unified three-dimensional scene.

[0018] As a preferred embodiment of the present invention, step S3, analyzing the spatial relationship between the groundwater enrichment zone and the roadbed structure, as well as the geological conditions, includes:

[0019] From the three-dimensional geological and structural model, extract at least two sets of spatial relationship parameters: the minimum horizontal distance between the groundwater enrichment area and the roadbed base, the thickness of the vertical interlayer, and the spatial orientation of the line connecting the two.

[0020] Extract lithological and permeability classification information of the strata below the track bed base.

[0021] As a preferred embodiment of the present invention, the step S3, which considers both the potential for water inflow and the stability requirements of the track bed structure, includes:

[0022] Based on spatial relationship parameters and permeability classification information, according to the spatial distance between the groundwater enrichment area and the roadbed base, the thickness of the interlayer and the permeability of the stratum, combined with the type and intensity of construction disturbance, the trend and main direction of groundwater migration to the roadbed base are determined, and the water inrush potential is classified into three levels: high, medium and low.

[0023] Based on the load requirements and lithological information in the design parameters of the track bed structure, and the corresponding geological mechanical parameters, by simulating the stress distribution and deformation characteristics of the strata under the influence of groundwater, the safety allowable value of the track bed structure is compared to determine whether the track bed base meets the stability requirements and whether the stability safety reserve is sufficient or insufficient.

[0024] Establish a correlation matrix between the inrush potential level and the stability safety reserve, and output the comprehensive risk level according to the preset correlation rules.

[0025] As a preferred embodiment of the present invention, the association rules in the correlation matrix establishing the correlation between inrush potential level and stability safety reserve include:

[0026] When the inrush potential level is high and the stability safety reserve is insufficient, the output is Level 1 High Risk.

[0027] When the inrush potential level is high but the stability safety reserve is sufficient, or when the inrush potential level is medium and the stability safety reserve is insufficient, the output is level two medium risk.

[0028] When the inrush potential level is low, or the inrush potential level is medium and the stability safety reserve is sufficient, the output is level three low risk.

[0029] As a preferred technical solution of the present invention, the method further includes step S4: spatial expression and dynamic updating of risk assessment results, which involves associating the environmental risk assessment results generated in step S3 with the spatial location in the three-dimensional geological and structural model to generate a thematic risk assessment map, and dynamically correcting the model and risk assessment results according to the actual on-site display during the construction process.

[0030] As a preferred embodiment of the present invention, the step of dynamically correcting the model and risk assessment results based on the actual on-site demonstration includes:

[0031] When construction and excavation reach high-risk areas, record the actual groundwater conditions, the lithology of the strata, and the comparison between the model prediction results;

[0032] If the comparison shows a significant discrepancy between the actual situation and the prediction, the water-rich area, stratigraphic interface morphology, or lithological zoning in the constructed three-dimensional geological and structural model is locally adjusted using the actual recorded groundwater distribution, stratigraphic lithology, and structural surface data, and step S3 is re-executed to update the environmental risk assessment results.

[0033] As a preferred technical solution of the present invention, the mapping data in step S1 also includes real-scene three-dimensional point cloud data of the construction face or tunnel initial support structure obtained by three-dimensional laser scanning, and spatial registration includes accurately matching the location of the geological radar survey line with the real-scene three-dimensional point cloud data.

[0034] As a preferred technical solution of the present invention, the environmental risk assessment results are integrated into the construction management platform in the form of a digital layer. The digital layer supports filtering and display by risk level, spatial query, and linkage analysis with the construction progress plan.

[0035] Compared with the prior art, the beneficial effects of the present invention are:

[0036] 1. By spatially registering and fusing ground-penetrating radar exploration data, surveying data, and engineering geological information in a unified coordinate system, a comprehensive dataset containing the reflection characteristics of underground media and the precise spatial location of surface and underground structures was established. This method overcomes the problem of the disconnect between traditional geophysical interpretation and engineering spatial location, and lays a reliable data foundation for subsequent accurate modeling and risk assessment.

[0037] 2. Based on a comprehensive dataset, this invention not only identifies the three-dimensional spatial distribution of groundwater-rich areas, but also integrates key stratigraphic interfaces and track bed structure design parameters to construct a three-dimensional geological and structural model that can clearly reflect the spatial relationship between groundwater-rich areas, stratigraphic interfaces, and track bed structures. This model realizes the integrated and visual expression of hydrogeological conditions and engineering structural morphology, providing an intuitive and accurate platform for spatial risk analysis.

[0038] 3. Based on the three-dimensional geological and structural model, the spatial relationship parameters and geological conditions between the groundwater enrichment area and the track bed structure are extracted. The water inrush potential level and the track bed foundation stability safety reserve are evaluated respectively. By establishing the correlation matrix and preset rules between the two, the coupled analysis and comprehensive quantitative classification of water inrush risk and structural stability risk are realized. The environmental risk assessment results for track bed voiding risk are output, so that the risk assessment can move from empirical qualitative to model quantitative.

[0039] 4. The assessment results are linked with the spatial location of the 3D model to generate a thematic risk assessment map, which is then integrated into the construction management platform. This supports risk visualization, querying, and progress linkage. More importantly, a mechanism for dynamically correcting the model and risk assessment results based on the actual construction situation is introduced, ensuring the timeliness and accuracy of the risk assessment and forming a closed-loop management process of prediction-construction-verification-correction.

[0040] 5. This invention provides a complete methodology system from data acquisition and fusion modeling to coupled evaluation and dynamic updating. This method closely integrates geological radar exploration, engineering surveying and mapping and environmental risk assessment, which can identify groundwater environmental risks in the construction area in advance and accurately, and provide direct technical support for the formulation of scientific and effective construction plans and risk control measures. This effectively ensures the safety of subway construction, prevents engineering disasters such as track bed delamination, and reduces construction delays and economic losses caused by environmental problems. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the overall process of the geophysical mapping and environmental risk assessment method for groundwater-rich areas in subway construction zones according to the present invention. Detailed Implementation

[0042] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0043] Example 1

[0044] Environmental risk assessment methods for geophysical mapping of groundwater-rich areas in subway construction zones include the following steps:

[0045] S1. Data Acquisition and Fusion Steps: Collect geological radar exploration data, surveying data and engineering geological information of the subway construction area, spatially register the geological radar exploration data and surveying data in a unified coordinate system, and establish a comprehensive dataset that includes the reflection characteristics of underground media and the spatial location of surface and underground structures.

[0046] S2. Three-dimensional geological and structural model construction steps: Based on the comprehensive dataset, identify the geophysical response characteristics of the groundwater-rich area and determine its three-dimensional spatial distribution. Combine the stratigraphic information in the engineering geological information with the track bed structure design parameters to construct a three-dimensional geological and structural model that reflects the spatial relationship between the groundwater-rich area, the stratigraphic interface and the track bed structure.

[0047] S3. Coupled assessment steps for water inrush and voiding risks: Based on the three-dimensional geological and structural model, analyze the spatial relationship between the groundwater-rich area and the track bed structure, as well as the geological medium conditions, couple the water inrush potential with the track bed structure stability requirements, and generate environmental risk assessment results for the risk of track bed voiding.

[0048] Furthermore, the geophysical response characteristics of groundwater-rich areas identified in step S1 include:

[0049] Preprocessing of ground-penetrating radar exploration data to extract the amplitude, frequency, and phase characteristics of reflected waves;

[0050] Based on the characteristics of reflected waves, regions that meet at least two of the following characteristics are identified as water-rich anomaly zones: enhanced reflected wave amplitude, reduced reflected wave frequency, and the reflected wave phase axis exhibiting a continuous or hyperbolic shape.

[0051] The identified water-rich anomaly areas are compared and verified with known aquifers in the engineering geological information to determine the final three-dimensional spatial distribution of groundwater-rich areas.

[0052] Furthermore, step S2 involves constructing a three-dimensional geological and structural model reflecting the spatial relationship between groundwater-rich areas, stratigraphic interfaces, and the roadbed structure, including:

[0053] Based on the track bed structure design outline coordinates in the survey data, a three-dimensional surface model of the track bed structure is established.

[0054] Based on borehole data and stratigraphic information in engineering geological information, a three-dimensional model of key stratigraphic interfaces is constructed. Specifically, the spatial coordinates of control points of each stratigraphic interface revealed in the borehole data are used as known data. Between adjacent control points, a continuous and smooth surface is generated according to the stratigraphic attitude trend to form a three-dimensional model of key stratigraphic interfaces.

[0055] The three-dimensional spatial distribution of groundwater-rich areas, the three-dimensional surface model of the track bed structure, and the three-dimensional model of key strata interfaces are integrated and visualized in a unified three-dimensional scene.

[0056] Furthermore, step S3 analyzes the spatial relationship between the groundwater enrichment zone and the roadbed structure, as well as the geological conditions, including:

[0057] From the three-dimensional geological and structural model, extract at least two sets of spatial relationship parameters: the minimum horizontal distance between the groundwater enrichment area and the roadbed base, the thickness of the vertical interlayer, and the spatial orientation of the line connecting the two.

[0058] Extract lithological and permeability classification information of the strata below the track bed base.

[0059] Furthermore, step S3, which couples the inrush potential with the track bed structure stability requirements, includes:

[0060] Based on spatial relationship parameters and permeability classification information, according to the spatial distance between the groundwater-rich area and the track bed base, the thickness of the interlayer and the permeability of the stratum, combined with the type and intensity of construction disturbance, the trend and main direction of groundwater migration to the track bed base are determined, and the water inflow potential is classified into three levels: high, medium and low. For example, when the water-rich area is close to the track bed base, the interlayer permeability is high and it is within the range of construction vibration, the water inflow potential is determined to be high.

[0061] Based on the load requirements in the track bed structure design parameters and the corresponding stratum mechanical parameters of lithology information, by simulating the stress distribution and deformation characteristics of the stratum under the influence of groundwater, the safety allowable value of the track bed structure is compared to determine whether the track bed base meets the stability requirements and whether the stability safety reserve is sufficient or insufficient. For example, a coupled model of the track bed and stratum including the action of groundwater is established using finite element software. The stress and deformation of key parts are obtained through simulation analysis and compared with the design safety standards to determine the safety reserve status.

[0062] Establish a correlation matrix between the inrush potential level and the stability safety reserve, and output the comprehensive risk level according to the preset correlation rules.

[0063] Furthermore, the correlation rules in the correlation matrix establishing the relationship between inrush potential level and stability safety reserve include:

[0064] When the inrush potential level is high and the stability safety reserve is insufficient, the output is Level 1 High Risk.

[0065] When the inrush potential level is high but the stability safety reserve is sufficient, or when the inrush potential level is medium and the stability safety reserve is insufficient, the output is level two medium risk.

[0066] When the inrush potential level is low, or the inrush potential level is medium and the stability safety reserve is sufficient, the output is level three low risk.

[0067] Furthermore, the method also includes step S4: spatial representation and dynamic updating of risk assessment results, which links the environmental risk assessment results generated in step S3 with the spatial location in the three-dimensional geological and structural model to generate a thematic risk assessment map, and dynamically corrects the model and risk assessment results based on the actual on-site display during construction.

[0068] Furthermore, the model and risk assessment results are dynamically revised based on the actual on-site demonstration, including:

[0069] When construction and excavation reach high-risk areas, record the actual groundwater conditions, the lithology of the strata, and the comparison between the model prediction results;

[0070] If the comparison shows a significant discrepancy between the actual situation and the prediction, the water-rich area, stratigraphic interface morphology, or lithological zoning in the constructed three-dimensional geological and structural model is locally adjusted using the actual recorded groundwater distribution, stratigraphic lithology, and structural surface data, and step S3 is re-executed to update the environmental risk assessment results.

[0071] Furthermore, the mapping data in step S1 also includes real-scene three-dimensional point cloud data of the construction face or the initial support structure of the tunnel obtained by three-dimensional laser scanning, and spatial registration includes accurately matching the location of the geological radar survey line with the real-scene three-dimensional point cloud data.

[0072] Furthermore, the environmental risk assessment results are integrated into the construction management platform in the form of a digital layer. The digital layer supports filtering and display by risk level, spatial querying, and linkage analysis with the construction schedule.

[0073] Example 2

[0074] This embodiment takes a subway tunnel construction section in Guangzhou as an example to illustrate the implementation process of the geophysical mapping environmental risk assessment method for groundwater-rich areas in subway construction zones according to the present invention.

[0075] S1. Data Acquisition and Fusion Steps

[0076] Ground-penetrating radar (GPR) data was collected from the subway construction area using an Italian RIS series GPR system with an antenna frequency of 100MHz. The total length of the survey line along the tunnel axis was approximately 2.5 kilometers. The mapping data was obtained by control measurement using a total station and GPS to acquire the tunnel design axis coordinates and elevation data. A FARO Focus S350 3D laser scanner was used to scan the construction face and the initial support structure of the tunnel to obtain real-scene 3D point cloud data. The engineering geological information included columnar sections of 30 boreholes in the area, stratigraphic information, and aquifer distribution maps.

[0077] Spatial registration was performed between the geoground radar survey line coordinates and the 3D laser scanning point cloud data. The seven-parameter transformation method was used to unify the two into the Guangzhou urban coordinate system, and a comprehensive dataset including underground medium reflection characteristics, surface topography, tunnel structure and initial support surface morphology was established.

[0078] S2, Steps for constructing a three-dimensional geological and structural model

[0079] The ground-penetrating radar data was preprocessed, including zero-point correction, background removal, and gain adjustment. The amplitude, frequency, and phase characteristics of the reflected waves were extracted, and three water-rich anomaly zones were identified. These anomaly zones were characterized by an increase in reflected wave amplitude of about 40%, a decrease in frequency to about 60MHz, and a continuous hyperbolic shape in the phase axis. These anomaly zones were compared and verified with known sand aquifers in borehole information to confirm that they were groundwater-rich areas and to determine their three-dimensional spatial distribution range.

[0080] Based on the track bed structure design outline coordinates in the survey data, a three-dimensional surface model of the track bed structure was established in AutoCAD Civil 3D software. Based on the borehole data and stratigraphic information in the engineering geological information, a three-dimensional model of the key stratigraphic interface was constructed. The specific process is as follows: using the spatial coordinates of the control points of each stratigraphic interface revealed in the borehole data as known data, a continuous and smooth surface was generated between adjacent control points by linear interpolation and smooth connection according to the stratigraphic attitude trend, so as to form a three-dimensional model of the key stratigraphic interface. Finally, the three-dimensional distribution of groundwater-rich areas, the track bed structure model and the stratigraphic interface model were imported into the same three-dimensional scene and integrated and visualized in the ArcGIS Pro platform.

[0081] S3, Risk Coupling Assessment Steps for Water Inrush and Voiding

[0082] Spatial relationship parameters were extracted from the three-dimensional geological and structural model, including the minimum horizontal distance between the groundwater enrichment area and the roadbed base, the thickness of the vertical interlayer, and the azimuth of the line connecting the two. The lithological information of the strata below the roadbed base was extracted, which mainly consisted of silty clay and medium-coarse sand, with permeability classified as low permeability and high permeability.

[0083] Based on spatial relationship parameters and permeability classification, and considering the distance between the water-rich area and the track bed base, the thickness of the interlayer, and permeability, combined with the shield tunneling method used in this section and the potential disturbance to the surrounding strata, the trend and main direction of groundwater migration towards the track bed base are determined. For example, in one water-rich area, the vertical interlayer thickness between the water-rich area and the track bed base is only 2.1 meters, and the stratum is a highly permeable sand layer. It is determined that under the disturbance of shield tunneling, groundwater is likely to migrate along this sand layer towards the track bed base, and the inrush potential level is rated as high. In another water-rich area, the interlayer thickness reaches 8.5 meters, and the stratum is low-permeability clay. It is determined that the groundwater migration trend is weak, and the inrush potential level is rated as low.

[0084] Based on the design load requirements of the track bed structure and the stratum mechanical parameters, a coupled model of the track bed and stratum was established using finite element software. The stress and deformation distribution of the track bed base and surrounding strata under the influence of groundwater were simulated. The simulation results were compared with the design safety allowable value to evaluate the stability safety reserve of the track bed base under the influence of groundwater. The results showed that the deformation of the sand layer area in the simulation was close to the allowable limit, with a safety factor of 1.8, indicating that the stability safety reserve was sufficient. The deformation of the clay layer area was much smaller than the allowable value, with a safety factor of 2.3, also indicating that the safety reserve was sufficient.

[0085] A correlation matrix was established between the potential level of water inrush and the stability safety reserve. Based on the correlation rules, the comprehensive risk level was output. The results were: the first water-rich area was classified as Level 1 high risk, and the second water-rich area was classified as Level 3 low risk.

[0086] S4. Spatial Representation and Dynamic Update Steps of Risk Assessment Results

[0087] The risk assessment results are linked to the spatial location in the 3D model to generate a thematic risk assessment map, which is then integrated into the BIM system of the construction management platform. This supports filtering and display by risk level, spatial querying, and analysis linked with the construction schedule.

[0088] When the construction excavation reached the first-level high-risk area, the actual groundwater seepage was relatively large, which was basically consistent with the model prediction. The actual data was recorded, the model was locally corrected, and the risk was reassessed. The result was still first-level high risk, which verified the reliability of the method.

[0089] Example 3

[0090] This embodiment takes a subway tunnel construction section in Shanghai as an example to further illustrate the applicability of the method of the present invention under different geological conditions.

[0091] S1. Data Acquisition and Fusion Steps

[0092] The ground-penetrating radar data was collected using the American GSSI SIR series radar with an antenna frequency of 80MHz and a survey line length of 3.0 kilometers. The mapping data was laid out with high precision using a Leica TS60 total station, and oblique photogrammetry was performed using a DJI drone to obtain a real-world 3D model of the construction area. The engineering geological information included data from 45 boreholes and a table of geological physical and mechanical parameters.

[0093] The data from the ground-penetrating radar (GPR) was registered with the oblique photogrammetry model. Specifically, the location of the GPR survey line was precisely matched with the real-world 3D point cloud data. By identifying ground feature lines in the point cloud data that correspond to the trajectory of the GPR survey line, such as road edge lines or obvious ground feature outlines, coordinate alignment was performed to ensure that the underground detection data and the spatial location of the surface and underground structures accurately correspond under the unified Shanghai local coordinate system.

[0094] S2, Steps for constructing a three-dimensional geological and structural model

[0095] After preprocessing the ground-penetrating radar data, two water-rich anomaly zones were identified. The amplitude of the reflected waves increased by about 35%, the frequency decreased to about 50MHz, and the phase axis showed a continuous shape. Compared with the borehole information, it was confirmed that they were silty sand aquifers.

[0096] Based on the track bed structure design outline coordinates in the survey data, a three-dimensional surface model of the track bed structure is established. Based on the borehole data and stratigraphic layering information in the engineering geological information, a three-dimensional model of the key stratigraphic interface is constructed. The specific process is as follows: using the spatial coordinates of the control points of each stratigraphic interface revealed in the borehole data as known data, between adjacent control points, according to the stratigraphic attitude trend, a continuous and smooth surface is generated by directly triangulating between the control points and smoothing the surface to form a three-dimensional model of the key stratigraphic interface.

[0097] The three-dimensional spatial distribution of groundwater-rich areas, the three-dimensional surface model of the track bed structure, and the three-dimensional model of key strata interfaces are integrated and visualized in a unified three-dimensional scene.

[0098] S3, Risk Coupling Assessment Steps for Water Inrush and Voiding

[0099] Spatial relationship parameters extracted from the three-dimensional geological and structural model show that the horizontal distance between one water-rich area and the roadbed base is only 3.5 meters, and the vertical interlayer is a silt layer with high permeability. The horizontal distance between the other water-rich area and the roadbed base is 12 meters, and the interlayer is a clay layer with low permeability.

[0100] The water inrush potential level was assessed, with the first location being high and the second low. Based on the load requirements in the track bed structure design parameters and the corresponding stratigraphic mechanical parameters of the lithology information, the stability safety reserve of the track bed base under the influence of groundwater was assessed. Using a simplified method similar to Example 2, the safety factor of the silt layer area was 1.5, which was determined to be insufficient stability safety reserve; the safety factor of the clay layer area was 2.1, which was determined to be sufficient.

[0101] Based on the correlation matrix, the risk level is output: the first point is level one high risk, and the second point is level three low risk.

[0102] S4. Spatial Representation and Dynamic Update Steps of Risk Assessment Results

[0103] The environmental risk assessment results are integrated into the construction management platform in the form of a digital layer. The digital layer supports filtering and display by risk level, spatial query, and linkage analysis with the construction schedule.

[0104] During construction, the model and risk assessment results were dynamically revised based on the actual site conditions. After excavating high-risk areas, it was found that the local strata lithology changed from the predicted silt to thin layers of silt, and the permeability changed. The comparison between the actual and the predicted results showed significant differences. Subsequently, the lithology zoning and permeability parameters in the three-dimensional geological and structural model constructed in step S2 were locally adjusted using the actual recorded strata lithology and structural surface data, and step S3 was re-executed. The updated risk assessment results showed that the risk level of this local area was adjusted from Level 1 high risk to Level 2 medium risk, which guided the subsequent adoption of more targeted control measures.

[0105] Compare with Example 1 (traditional geophysical exploration method, without establishing a three-dimensional coupling model).

[0106] The same ground-penetrating radar data as in Example 2 was used, but the water-rich area was identified based solely on the single feature of enhanced reflected wave amplitude. Multi-feature fusion and three-dimensional spatial modeling were not performed. The risk assessment was based solely on experience and did not quantitatively analyze spatial relationships and stratum permeability. During construction, water inrush occurred in areas originally identified as low-risk, causing construction delays.

[0107] Compare with Example 2 (which was not dynamically updated).

[0108] The same data and model as in Example 3 were used, but the model was not corrected based on the actual data displayed during construction. The original model predicted that a certain area was low-risk, but after actual excavation, it showed local water abundance. However, because the model was not updated, construction continued according to the original plan, resulting in local track bed detachment.

[0109] Experimental data tables and analysis descriptions

[0110] The following table shows the comparison data between the risk assessment results and actual conditions of Examples 2 and 3, and Comparative Examples 1 and 2 during the actual construction process:

[0111]

[0112] As can be seen from the above experimental data, the method of the present invention exhibits high risk assessment accuracy in both Example 2 and Example 3. In Example 2, for the high-risk area of ​​a subway section in Guangzhou, the model accurately predicted the potential for water inrush, and the construction unit took support and drainage measures in advance, effectively controlling the construction risk; the construction in the low-risk area proceeded smoothly without any abnormalities. In Example 3, the high-risk area of ​​a subway section in Shanghai was also accurately identified, and timely responses were made during the construction process, without causing any substantial impact.

[0113] In contrast to Example 1, the traditional single geophysical feature identification method was used, but a three-dimensional coupled model was not established, which led to an error in risk assessment and an unexpected water inrush during construction, causing a delay in the construction period. In contrast to Example 2, although an initial model was established, it was not dynamically updated during construction, which caused the model to become out of touch with the actual situation and failed to provide timely warning of local water inrush risks, ultimately leading to the problem of track bed delamination.

[0114] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for environmental risk assessment of groundwater-rich areas in subway construction zones, characterized in that... Includes the following steps: S1. Data Acquisition and Fusion Steps: Collect geological radar exploration data, surveying data and engineering geological information of the subway construction area, spatially register the geological radar exploration data and surveying data in a unified coordinate system, and establish a comprehensive dataset that includes the reflection characteristics of underground media and the spatial location of surface and underground structures. S2. Three-dimensional geological and structural model construction steps: Based on the comprehensive dataset, identify the geophysical response characteristics of the groundwater-rich area and determine its three-dimensional spatial distribution. Combine the stratigraphic information in the engineering geological information with the track bed structure design parameters to construct a three-dimensional geological and structural model that reflects the spatial relationship between the groundwater-rich area, the stratigraphic interface and the track bed structure. S3. Coupled assessment steps for water inrush and voiding risks: Based on the three-dimensional geological and structural model, analyze the spatial relationship between the groundwater-rich area and the track bed structure, as well as the geological medium conditions, couple the water inrush potential with the track bed structure stability requirements, and generate environmental risk assessment results for the risk of track bed voiding.

2. The method according to claim 1, characterized in that, The geophysical response characteristics of groundwater-rich areas identified in step S1 include: Preprocessing of ground-penetrating radar exploration data to extract the amplitude, frequency, and phase characteristics of reflected waves; Based on the characteristics of reflected waves, regions that meet at least two of the following characteristics are identified as water-rich anomaly zones: enhanced reflected wave amplitude, reduced reflected wave frequency, and the reflected wave phase axis exhibiting a continuous or hyperbolic shape. The identified water-rich anomaly areas are compared and verified with known aquifers in the engineering geological information to determine the final three-dimensional spatial distribution of groundwater-rich areas.

3. The method according to claim 1, characterized in that, The construction of a three-dimensional geological and structural model reflecting the spatial relationship between groundwater-rich areas, stratigraphic interfaces, and the roadbed structure in step S2 includes: Based on the track bed structure design outline coordinates in the survey data, a three-dimensional surface model of the track bed structure is established. Based on borehole data and stratigraphic information in engineering geological information, a three-dimensional model of key stratigraphic interfaces is constructed. Specifically, the spatial coordinates of control points of each stratigraphic interface revealed in the borehole data are used as known data. Between adjacent control points, a continuous and smooth surface is generated according to the stratigraphic attitude trend to form a three-dimensional model of key stratigraphic interfaces. The three-dimensional spatial distribution of groundwater-rich areas, the three-dimensional surface model of the track bed structure, and the three-dimensional model of key strata interfaces are integrated and visualized in a unified three-dimensional scene.

4. The method according to claim 1, characterized in that, The analysis of the spatial relationship between the groundwater enrichment zone and the roadbed structure, as well as the geological conditions, in step S3 includes: From the three-dimensional geological and structural model, extract at least two sets of spatial relationship parameters: the minimum horizontal distance between the groundwater enrichment area and the roadbed base, the thickness of the vertical interlayer, and the spatial orientation of the line connecting the two. Extract lithological and permeability classification information of the strata below the track bed base.

5. The method according to claim 4, characterized in that, The coupling consideration of water inrush potential and track bed structure stability requirements in step S3 includes: Based on spatial relationship parameters and permeability classification information, according to the spatial distance between the groundwater enrichment area and the roadbed base, the thickness of the interlayer and the permeability of the stratum, combined with the type and intensity of construction disturbance, the trend and main direction of groundwater migration to the roadbed base are determined, and the water inrush potential is classified into three levels: high, medium and low. Based on the load requirements and lithological information in the design parameters of the track bed structure, and the corresponding geological mechanical parameters, by simulating the stress distribution and deformation characteristics of the strata under the influence of groundwater, the safety allowable value of the track bed structure is compared to determine whether the track bed base meets the stability requirements and whether the stability safety reserve is sufficient or insufficient. Establish a correlation matrix between the inrush potential level and the stability safety reserve, and output the comprehensive risk level according to the preset correlation rules.

6. The method according to claim 5, characterized in that, The association rules in the correlation matrix establishing the inrush potential level and the stability safety reserve include: When the inrush potential level is high and the stability safety reserve is insufficient, the output is Level 1 High Risk. When the inrush potential level is high but the stability safety reserve is sufficient, or when the inrush potential level is medium and the stability safety reserve is insufficient, the output is level two medium risk. When the inrush potential level is low, or the inrush potential level is medium and the stability safety reserve is sufficient, the output is level three low risk.

7. The method according to claim 1, characterized in that, The method also includes step S4: spatial expression and dynamic updating of risk assessment results, which involves associating the environmental risk assessment results generated in step S3 with the spatial location in the three-dimensional geological and structural model to generate a thematic risk assessment map, and dynamically correcting the model and risk assessment results based on the actual on-site display during construction.

8. The method according to claim 7, characterized in that, The dynamic correction of the model and risk assessment results based on the actual on-site demonstration includes: When construction and excavation reach high-risk areas, record the actual groundwater conditions, the lithology of the strata, and the comparison between the model prediction results; If the comparison shows a significant discrepancy between the actual situation and the prediction, the water-rich area, stratigraphic interface morphology, or lithological zoning in the constructed three-dimensional geological and structural model is locally adjusted using the actual recorded groundwater distribution, stratigraphic lithology, and structural surface data, and step S3 is re-executed to update the environmental risk assessment results.

9. The method according to claim 1, characterized in that, The mapping data in step S1 also includes real-scene three-dimensional point cloud data of the construction face or tunnel initial support structure obtained by three-dimensional laser scanning. Spatial registration includes accurately matching the location of the geological radar survey line with the real-scene three-dimensional point cloud data.

10. The method according to claim 1, characterized in that, The environmental risk assessment results are integrated into the construction management platform in the form of a digital layer. The digital layer supports filtering and display by risk level, spatial query, and linkage analysis with the construction schedule.

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