2352 results about "Groundwater" patented technology

The invention provides an underground water pollution source tracing and evaluation method for a riverside water source in a karst area, and the method comprises the following steps: collecting and preprocessing multi-source information, and obtaining a multi-source data set; a water quality sample is collected and analyzed, the surface water-underground water interaction process and pollution characteristics are comprehensively analyzed, and a pollution source type is obtained; performing space-time analysis on the multi-source data set to obtain a pollution activity time period and a potential pollution source area; constructing a karst area hydrological model, simulating the hydrological characteristics of the karst area, constructing a pollutant migration model, and simulating the migration process of pollutants; and constructing a traceability algorithm, tracking pollutants, confirming a pollution source, carrying out risk partitioning and risk assessment, and carrying out visual display of a result. According to the invention, interaction between surface water and underground water can be effectively assessed, accurate traceability of pollutants and multi-angle accurate identification of pollution sources can be realized, and management efficiency can be optimized through reliable risk assessment prediction.

The invention relates to a groundwater safety assessment method under an extreme climate event, which comprises the following steps: collecting multi-source heterogeneous data such as meteorological data, geological data, hydrological data and remote sensing data, and constructing a unified groundwater safety knowledge graph through standardized cleaning, semantic alignment and deletion completion; monitoring an extreme climate event in real time, and updating a node relation weight and sparsifying a transmission path based on knowledge graph dynamic evolution and a time sequence attention mechanism; performing risk propagation path reasoning on the dynamic knowledge graph in combination with an improved graph neural network, identifying key pollution nodes, and outputting a structured risk level and a coping suggestion; the system continuously optimizes atlas and model parameters based on evolution feedback, and high adaptability and reasoning precision of emergency response are achieved. According to the method, the intelligence, the real-time performance and the accuracy of underground water risk assessment are improved. The problems that the underground water pollution propagation path is difficult to dynamically identify and the decision adaptability is insufficient under extreme climate events are solved.

The invention discloses an underground water infiltration replenishment evaluation method and equipment based on digital twinning, and relates to the technical field of underground water digital twinning evaluation, and the method comprises the steps: traversing a target area to carry out multi-source sensing collection; performing underground water infiltration simulation to generate an infiltration full-process data set, and obtaining an infiltration coupling model; geologic structure parameters of the target area are extracted, and a three-dimensional geologic structure model is constructed; performing association mapping on the infiltration coupling model and the three-dimensional geological structure model to obtain a dynamic simulation result; deviation analysis is carried out, automatic correction optimization is carried out, and an underground water infiltration supply evaluation report is generated. According to the method, the technical problems of insufficient multi-source data fusion, low space-time simulation precision and weak model dynamic correction capability in underground water infiltration supply evaluation in the prior art are solved, and underground water infiltration supply dynamic simulation and digital twinborn automatic correction of multi-source data coupling are realized; and the technical effect of improving the space-time precision of groundwater infiltration supply evaluation is achieved.

The invention provides a method for evaluating the grouting water control effect of an underground water-sealed cave depot project. The method comprises the steps that firstly, grouting and geological parameters and hydrological monitoring data of a project area are obtained; establishing a three-dimensional seepage-grouting coupling model, and simulating the dynamic state of a seepage field by using a finite element analysis algorithm; then calculating the equivalent permeability change rate of the grouting affected zone based on a simulation result; constructing an evaluation index system, and performing quantitative evaluation by using a fuzzy comprehensive evaluation algorithm; and finally, generating a grouting parameter dynamic adjustment scheme according to an evaluation result. According to the method, scientific and accurate evaluation and engineering optimization of the grouting water control effect can be achieved, and the safety and economical efficiency of engineering are improved.

The invention discloses a flexible load multi-target collaborative scheduling system and method, and relates to the technical field of collaborative optimization of power systems. The method is used for solving the problem of lack of accurate prediction and multi-target coordination of agricultural electricity and water utilization regulation and control. Firstly, based on meteorological data, soil moisture content and crop growth characteristics, an irrigation demand prediction model is constructed, irrigation water demand is predicted, and a water pump load power baseline is generated; then, a dynamic baseline constraint condition is generated in combination with historical behavior data and water pump start-stop logic; establishing a power grid side objective function, a user side objective function and a water affair side objective function, and introducing an underground water and carbon emission punishment mechanism; thirdly, dividing the power distribution network into sub-regions, adopting an alternating direction multiplier method to solve a region regulation and control strategy in parallel, coordinating water resource distribution conflicts through virtual interactive variables, and outputting a global scheduling instruction; and finally, collecting real-time response data and correcting the prediction model on line to realize closed-loop adaptive optimization.

The invention relates to the technical field of coupling simulation, in particular to a river and underground water coupling simulation parameter generation method and system. The method comprises the following steps: collecting remote sensing and ground sensing monitoring data, and generating a multi-source space-time initial data set through time mark calibration, space resampling and signal-to-noise ratio weighted fusion; extracting features between the water level of the river and the water level of the underground water based on the data set, constructing a river-underground water space-time topological structure and identifying an interaction mode, and forming a space-time coupling feature map through significance screening and periodic enhancement; performing parameter inversion by adopting a hydrodynamic equation, and generating a physical inversion parameter set in combination with sensitivity analysis and local optimization; a parallelization hydrological simulation framework is constructed, error-driven optimization is executed, and dynamic optimization parameters are obtained; river and underground water exchange simulation is executed, and finally, coupling simulation parameter set updating is achieved through sliding window deviation evaluation and incremental parameter correction. Therefore, the precision and operability of a coupling simulation result are improved.

The invention provides an underground water source water supply safety assessment method and system, and relates to the technical field of water supply safety assessment. The method comprises the steps of obtaining a permeability distribution diagram, dividing grids and analyzing direction changes, constructing an edge set to extract a closed form to generate a partition layer, setting measuring points to collect water level data, evaluating a change consistency screening path, matching a boundary to judge a crossing condition, marking a sudden change position, recording an interference path and establishing a recognition list. According to the method, by comparing the consistency of the water level direction in unit time and the response fluctuation, the path line segment with the hydraulic coherence characteristic is identified, the depicting ability of the actual underground water flowing path in the non-uniform supply environment is improved, the path trend sudden change and boundary overlapping position is analyzed, the response identification of the structure interference action area is enhanced, and the accuracy of the structure interference action area is improved. A key section with water supply interruption or supply abnormity is positioned, and the response capability of actual hydrological and geological changes and the spatial fineness of evaluation and judgment are improved.

The invention relates to the technical field of environmental pollution monitoring, and discloses an intelligent monitoring and tracing method and system for groundwater pollution, and the method comprises the steps: arranging a first monitoring well at the periphery of a target pollution source, obtaining data, calculating a comprehensive pollution index, dividing a risk area, and obtaining second monitoring data based on the optimized point distribution of the risk area, a four-dimensional space-time distribution model and a three-dimensional dynamic migration diffusion model are constructed, and pollution traceability analysis is carried out by combining the two models; according to the method, accurate monitoring of groundwater pollution is realized through a risk classification-driven differentiated point distribution strategy, and the temporal-spatial resolution and traceability precision of pollution plume migration simulation are remarkably improved through fusion of monitoring data and dynamic traceability analysis of a geologic model.

The invention provides an industrial park soil and groundwater pollution early warning grade evaluation method and system.The method comprises the steps that production raw material components of pollution source enterprises, waste discharge data and soil heavy metal concentration evolution data in historical pollution events are integrated, optical sensing data of earth surface and underground monitoring points are combined, and the early warning grade of soil and groundwater pollution is evaluated; constructing a dynamic characteristic factor library reflecting pollution source characteristics; carrying out spatial concentration gradient calculation on the optical sensing data based on the characteristic factor library, and generating a dynamic heat map containing heavy metal distribution and migration trends at the same time; performing cross-modal analysis on the pollution source characteristics and the dynamic heat map, and establishing a spatio-temporal evolution trajectory of a pollution diffusion path; according to the diffusion rate and direction in the track, differentiated pollution risk early warning intervals are divided, and a targeted grading prevention and control strategy is generated. According to the invention, the timeliness of pollution early warning and the targeting of prevention and control measures are improved.

The invention discloses a flood plain shallow-buried unsymmetrical-pressure multi-arch tunnel excavation stability evaluation method, and relates to the technical field of tunnel stability evaluation, and the method comprises the following steps: obtaining the geological conditions of a tunnel excavation area through on-site survey and drilling, and evaluating the groundwater emission amount and the inrush probability in combination with historical data; and basic data support is provided for subsequent risk modeling. According to the method, through geological and hydrological survey and a numerical model, the high-risk inrush area and the water pressure distribution are accurately predicted, the risk identification and early warning precision is effectively improved, and a scientific basis is provided for support design. Optimized design of the supporting structure is combined with real-time monitoring and dynamic adjustment, construction safety is guaranteed, and meanwhile structural reliability and economical efficiency are both considered.

The invention relates to the technical field of water resource scheduling, and provides an urban inland river system intelligent resource scheduling management system and method based on dynamic data collaboration, and the method comprises the following steps: S1, collecting river hydrological data, water quality indexes, urban water demands and water transfer facility state data in real time, and carrying out the time-space alignment and abnormal value filtering; s2, a hydrodynamic force-water quality coupling model of multiple water sources is established, a multi-objective optimization model is established in combination with constraint conditions of ecological base flow and an engineering upper limit, and the multiple water sources include but not limited to river water, underground water, reservoir water, reclaimed water, rainwater and desalinated seawater; and S3, carrying out global dynamic optimization on the water transfer proportion and the water transfer facility parameters by adopting a model algorithm, and minimizing the water transfer cost and the ecological influence. By quantifying the maximum flow upper limit and the ecological base flow threshold value of each water source and optimizing the water transfer proportion and facility parameters, the water resource utilization efficiency is improved, and it is guaranteed that the water transfer cost and the ecological influence are balanced in the urban river water dispatching process.

The invention provides an underground water pollutant concentration prediction method and system based on machine learning, and relates to the technical field of underground water pollutant concentration prediction.The method comprises the steps that historical data, hydrogeological parameters, meteorological data, human activity data and geochemical parameters of underground water pollutant concentration of a target area are preprocessed; dividing a training set, a verification set and a test set; constructing a preset resolution feature set based on a geochemical mechanism; selecting an adaptive machine learning model according to data characteristics and coupling a physical mechanism; performing hyper-parameter tuning by adopting Bayesian optimization, and supplementing small sample data in combination with transfer learning to complete model training; predicting the underground water pollutant concentration of the target area by using the trained model, and outputting a pollutant concentration prediction result with an uncertainty interval; the invention provides a technical scheme for predicting the concentration of underground water pollutants, which is efficient, accurate and high in adaptability.

The invention relates to the technical field of coal mining safety monitoring, and discloses a coal mining subsidence space-time evolution intelligent prediction method, which comprises the following steps: acquiring multi-dimensional geological dynamic data such as surface displacement, underground water pressure and rock stratum stress of a coal mining area, extracting a space-time characteristic sequence by using a GCLSTM algorithm, and calculating a space-time fluctuation coefficient; extracting a principal component vector through spectral decomposition, mapping to obtain a space-time correlation weight, dynamically correcting an original prediction value to generate a fusion prediction value, and judging a subsidence space-time evolution trend; constructing a three-dimensional subsidence curved surface model to identify a high-risk area and generate graded early warning; and establishing a joint optimization model to solve an optimal mining path, and generating a subsidence risk minimization scheme. According to the method, intelligent analysis of multi-dimensional data fusion and spatial-temporal characteristics is realized, the prediction accuracy is improved, an effective means is provided for coal mining subsidence prevention and control and safe mining, and the method has a remarkable engineering application value.

The invention discloses a karst underground river system multi-source pollution comprehensive quantitative traceability method, which comprises the following steps: S1, multi-dimensional sample collection and new pollutant screening: carrying out multi-period sampling on a water body, measuring conventional water quality indexes and nitrogen and oxygen isotopes, screening new pollutants, and carrying out targeted quantification on characteristic new pollutants; s2, principal component analysis dimension reduction and pollution factor identification: carrying out principal component analysis on conventional indexes and new pollutant data, extracting principal components of which the cumulative contribution rate exceeds 85%, identifying composite pollution factors, and eliminating secondary interference factors; s3, nitrogen and oxygen isotope auxiliary verification and denitrification elimination: eliminating denitrification interference by utilizing the ratio of delta 15N-NO3 <-> to delta 18O-NO3 <-> in combination with underground water burial depth and runoff velocity, and distinguishing the nitrate source as a chemical fertilizer, soil nitrogen or sewage and wastewater; and S4, PMF model optimization and pollution source quantification: inputting the conventional indexes and the new pollutant concentration matrix into a PMF model, and analyzing the contribution rate of each pollution source.

The invention provides a highway tunnel decision-making maintenance system and a maintenance method thereof. The method comprises the steps of obtaining tunnel static and dynamic data and tunnel surrounding geological environment data; according to the geological environment data, carrying out geological risk analysis by adopting a geological statistical simulation algorithm and a time sequence decomposition algorithm to obtain a safety risk assessment result of the tunnel structure influenced by geological factors and an underground water dynamic change trend prediction result; according to the geological risk analysis result, fusing the tunnel technical condition data by adopting a heterogeneous integration model of a dynamic Bayesian network and an extreme gradient boosting tree, predicting the tunnel technical condition, and generating maintenance decision parameters; optimizing the maintenance decision parameters by adopting a cuckoo search algorithm so as to minimize the maintenance cost under the influence of the geological risk; and outputting decision results including the total maintenance cost distribution based on the geological risk, the technical condition improvement expectation, the rock stratum stability safety factor prediction value and the underground water seepage risk early warning level.

The invention provides an underground water environment automatic monitoring super station state supervision method and system. The method comprises the following steps: collecting a multi-source dynamic time sequence data set and carrying out time-space alignment; generating a dynamic characteristic index set by using a nonlinear dynamic characteristic extraction method; based on the index set, constructing a self-adaptive cooperative measurement network to perform anomaly monitoring, and generating an anomaly detection result and a cooperative control instruction; generating real-time monitoring and early warning information by using a dynamic threshold adjustment algorithm; and generating an adaptive control instruction and a dynamic resource allocation scheme by using a neural network adaptive control strategy and a resource scheduling optimization algorithm. According to the method, a dynamic characteristic index set is generated, a C-C method is adopted to reconstruct a high-dimensional phase space, a Wolf algorithm and a G-P algorithm are combined to calculate related indexes and dimensions, and a multi-scale fractal mode is analyzed through an R / S analysis method and wavelet transform. The methods capture complex dynamic behaviors of the underground water system, and solve the problem that the traditional method is insufficient in non-linear feature extraction capability.

The invention discloses a land-sea system nitrogen and phosphorus pollutant collaborative source analysis method, and particularly relates to the field of environmental governance and water pollution traceability, which comprises a comprehensive method based on a multi-isotope tracer technology, an isotope mixed model and nitrogen and phosphorus molar ratio verification, and comprises the following steps: acquiring isotope characteristics of nitrogen sources and phosphorus sources in various forms of a land-sea system; in combination with hydrology and water quality monitoring data, the polymorphic contribution of river water, underground water, coastal terrestrial sources and estuary endogenesis to estuary nitrogen and phosphorus pollutants is quantitatively analyzed; through accurate calibration of underground water input, dynamic quantification of pollution flux and cooperative analysis of nitrogen and phosphorus pollutant sources, the problem of insufficient systematicness and accuracy in tracing of complex multi-source pollutants in the prior art is solved, and a basis is provided for drainage basin-estuary-bay integrated treatment.

The invention provides an underground water overdraft area water level early warning method and system, and relates to the technical field of water quality dynamic monitoring, and the method comprises the steps: building an underground water overdraft area water level early warning model based on the corrected overdraft area range and overdraft degree; inputting the water level change data monitored in real time into the underground water overdraft area water level early warning model, and performing water level early warning to obtain a preliminary early warning result; water level change data of the underground water overdraft area are monitored in real time, related dynamic influence factor data are recorded, and the dynamic influence factor data comprise the rainfall capacity, the evaporation capacity and the man-made mining quantity; calculating a dynamic factor according to the dynamic influence factor data; and correcting the preliminary early warning result through the dynamic factor to obtain a final early warning result. According to the final early warning result, when it is judged that the groundwater level is about to drop to an early warning threshold value, an early warning signal is sent out. According to the invention, the accuracy and timeliness of early warning are improved.

The invention discloses a road foundation bearing characteristic analysis method and system, relates to the technical field of road foundation analysis, and realizes a fundamental breakthrough for the problems of high misjudgment rate, poor climate adaptability and the like caused by a traditional fixed threshold by constructing a dynamic self-adaptive risk judgment threshold mechanism. According to the mechanism, when a dynamic threshold value Tdy is calculated, spatial statistical characteristics of current foundation response strength are fully fused, and a comprehensive environment disturbance characteristic, namely a collapsible environment index, is combined, so that a dynamic judgment standard with environment sensitivity adjustment capability is formed. The system can automatically adjust the risk identification threshold value according to the actual rainwater infiltration intensity and the underground water dynamic jump condition, so that the system can actively reduce the risk tolerance boundary and identify and respond to an abnormal area in advance under the extreme working conditions of heavy rainfall, rapid underground water rising and the like, and moderately relaxes in a dry or stable period, so that the risk identification accuracy is improved. And the real-time performance and adaptability of risk identification are obviously improved.

The invention discloses a self-adaptive grid dynamic encryption method for underground water pollution migration simulation, which belongs to the technical field of underground water pollution migration simulation, and comprises the following steps of: forming 0.05-meter super-resolution grids at the periphery of a dispersed pollution source through a local grid dynamic encryption technology triggered by a pollution source intensity gradient threshold; the pollutant frontal surface tracking error is greatly reduced, and the high-precision pollutant migration simulation capability is realized. Moreover, based on an intelligent grid reconstruction algorithm of a flux threshold, the number of calculation units is reduced by 62%, the time consumed by single simulation is shortened to 3.3 hours, and the overall mass conservation error is kept to be smaller than 1% while the calculation efficiency is improved. Meanwhile, for a heterogeneous aquifer, through a pollution flux and stratum permeability coefficient dual-drive encryption strategy, the solute transport prediction precision of the model at the boundary of a clay lenticular body is greatly improved, and the problems that in the prior art, the simulation precision of the periphery of a pollution source is insufficient, and the calculation efficiency is low due to global encryption are effectively solved.

The invention relates to the technical field of mining, in particular to a mine disaster prediction method and system. The method comprises the following steps: acquiring geologic structure data corresponding to a mine, wherein the geologic structure data comprises rock stratum distribution, fault occurrence and underground water occurrence state; constructing a coupling model corresponding to the mine based on the rock stratum distribution, the fault occurrence and the underground water occurrence state, and determining a rock mass constitutive relation and coupling parameters in the coupling model; determining a prediction boundary condition of the coupling model based on the rock constitutive relation and the coupling parameters; and acquiring field monitoring data of the mine, correcting the coupling model based on the field monitoring data and the prediction boundary condition so as to determine a potential disaster point based on the corrected coupling model, and generating a risk early warning strategy and a risk recovery strategy corresponding to the potential disaster point. According to the embodiment of the invention, a full-chain prevention and control system from disaster prediction to emergency disposal is constructed, and the safety management level and disaster prevention and control capability of mine engineering are remarkably improved.

The invention relates to a pile foundation reinforcement method and system based on a karst area, and belongs to the technical field of foundation treatment and reinforcement. The pile foundation reinforcement method comprises the steps that a karst area pile foundation monitoring network is established, and karst cavity distribution characteristic parameters and underground water dynamic change parameters are obtained; constructing an adaptive evaluation model, and setting an initial real-time feedback correction parameter vector; based on a spatio-temporal evolution rule, generating a karst development comprehensive complexity index of dynamic evolution; a grading response mechanism is established, and pile foundation reinforcement early warning and response measures of corresponding grades are triggered; and constructing an intelligent decision-making system, and continuously optimizing an evaluation model and a reinforcement strategy through a feedback mechanism. According to the method, the karst development comprehensive complexity index is generated by introducing the underground water dynamic change parameters and combining the karst cavity distribution characteristic parameters, the evaluation of the geological environment is expanded from a static time point to a dynamic evolution process, and the comprehensiveness and accuracy of the evaluation are improved.

The invention relates to a mining damage control method for multi-medium carbon pollution cooperative reduction and control and resource application, and belongs to the technical field of full-waste resource treatment and utilization of a short-distance coal seam mining goaf. The mining damage control method comprises the following steps that filling liquid and filling materials are stirred and mixed while carbon dioxide gas is introduced to form filling slurry; then all-directional shower type spraying is conducted from the filling pipeline to the goaf; performing full grouting on the goaf in a sealed form until the goaf is full, introducing carbon dioxide into the goaf while performing full grouting, monitoring and analyzing underground behaviors, rock reaction and rock stratum stability of carbon dioxide in a backfilling area, and when underground water exists in a sealing and storing area, establishing an underground water monitoring system to monitor the water quality of the underground water; the power plant flue gas is treated and then injected into the goaf to be mixed with the filling material, so that the oxygen concentration of the goaf is effectively reduced, goaf fire disasters are prevented and treated, mining disasters in the goaf are effectively controlled, and the stability of rock strata is improved.

The invention discloses a dynamic blockage management system and method for an underground water recharge well. The system comprises a monitoring and acquisition module, a data processing and risk assessment module, a flow rate adjustment optimization and dynamic feedback module and a storage and remote management module. The method comprises the following steps: monitoring key parameters such as water flow rate, suspended particulate matter concentration, fluid density and temperature and the like in a well injection process in real time, and carrying out data preprocessing; deriving a comprehensive blockage risk index calculation formula based on the key parameters, and comparing with a set threshold to judge whether flow velocity adjustment is triggered or not; by analyzing the relationship among the blockage risk, the pressure loss and the injection amount in real time, an objective function is constructed to seek an optimal solution; the well injection flow velocity is dynamically adjusted based on the solved optimal flow velocity and is dynamically fed back; and carrying out data storage and remote management. The device can dynamically adjust the injection flow rate, remarkably improve the injection efficiency, reduce the maintenance cost, and effectively manage and reduce the physical blockage problem in the underground water recharge process.

The invention relates to the technical field of soil monitoring, and discloses a power transmission and transformation project soil pollutant monitoring method and system, and the method comprises the steps: collecting hyperspectral image data in a power transmission and transformation project region; processing the hyperspectral image data by adopting a multi-stage spectrum transformation mechanism to obtain a characteristic wave band representing the pollutant content; inputting the characteristic wave band into a preset spectrum inversion model to generate a concentration spatial distribution diagram of the soil pollutants; and constructing a soil and groundwater diffusion model according to the concentration spatial distribution map, and generating a migration path identification map of soil pollutants and an underground pollution risk area identification map based on the soil and groundwater diffusion model. The method has the beneficial effect of improving pollution identification precision and migration prediction accuracy.

The invention relates to an isotope-based underground water organic pollution traceability analysis method and system. The method comprises the following steps: collecting pollutant parameters of a monitoring point at a plurality of time intervals; constructing a target monitoring point set; the coverage area is called as a target area; discovering and analyzing pollutant parameters of each monitoring point in the target monitoring point set based on the typical time interval so as to obtain contour lines corresponding to pollutant parameter types; taking an area in the contour line corresponding to the high pollutant parameter of each pollutant type as a suspected area; and determining a target pollution source in the suspected area based on the isotope parameters. According to the method, big data monitoring resources are fully utilized in space and time, pollutant parameters are combined, isotope analysis resources are optimized and utilized, pollution sources are tracked and guided, and efficient multi-source burst differentiated pollutant traceability is provided.

The invention provides grouting and filling equipment for water-preserved mining of a coal mine, and relates to the technical field of mining equipment, and the grouting and filling equipment comprises a base frame piece, a grouting guide pipe piece, a slurry post-processing assembly and a plugging driving assembly. A plurality of groups of outer ring parts with hole wall pressure sensors are arranged on the outer wall of the grouting guide pipe piece, and a pipe end micro sensor is arranged at the grout outlet end; the inserting and pulling driving assembly drives the stirring assembly to push the outer ring part through the motor, and inserting and pulling of the grouting guide pipe piece are controlled. During working, the guide pipe piece is inserted into a grouting hole to a goaf, the sensor monitors rock mass pressure, temperature and sound wave signals in real time, the grouting pressure is dynamically adjusted in combination with formation resistance, and grout fluid channeling or insufficient filling is avoided. Through precise pressure regulation and automatic insertion and extraction, the problems of material waste, underground water pollution and insufficient goaf filling in traditional grouting are solved, and the environmental protection property and the engineering efficiency of water-preserved mining are remarkably improved.

The invention discloses a method for analyzing the influence of railway tunnel construction on urban underground water, which belongs to the field of railway tunnel construction and comprises the following steps: S1, acquiring and preprocessing multi-source data; s2, constructing a geology-hydrology-construction-remote sensing multi-dimensional feature vector, and extracting an underground water disturbance index; s3, establishing a stress-seepage-heat conduction three-field coupling model; s4, analyzing a three-field coupling effect based on the three-field coupling model, and outputting a comprehensive risk level of the influence of tunnel construction on underground water; s5, fusing a comprehensive risk level by utilizing a GIS spatial analysis function, and combining real-time data to realize spatial visualization and graded early warning of underground water influence; and S6, geological parameters of the three-field coupling model are updated in real time, and an optimal construction parameter combination is searched. By adopting the method for analyzing the influence of the railway tunnel construction on the urban underground water, the scientificity and engineering practicability of analyzing the influence of the railway tunnel construction on the urban underground water are remarkably improved.

The invention provides a visual rock filling fracture seepage monitoring method. The visual rock filling fracture seepage monitoring method comprises the following steps: preparing a transparent rock filling fracture model based on real fracture morphology and filling treatment; a mixture which is used for simulating the underground water environment and contains tracer particles is injected into the filling fracture of the model, seepage is conducted, in the seepage process, an image I1 and an image I2 are continuously collected, the flow velocity field of the filling fracture is monitored for the image I1 through a PIV method, and the dissolution condition of filler and the corresponding filling fracture opening change condition are monitored for the image I2 through a DIC method; and identifying an eddy current area in the filling crack by the image I2, and calculating the overflowing capability of the filling crack according to the flow of the waste liquid discharged by the model. According to the method, disturbance to a natural structure in the fracture is avoided, dynamic monitoring of fluid in the fracture can be achieved, data support is provided for research on seepage field change in the dynamic fracture, and research on the relation between fracture geometric heterogeneity and seepage field characteristics is facilitated.

The invention discloses an underground water pollutant migration simulation method coupled with a physical mechanism and data driving, which comprises the following steps: establishing a statistical model through a machine learning method to correct the structural error of an underground water model, and expressing the output of the underground water model as the sum of a physical mechanism model, a structural error model and an observation error. According to the method, underground water pollutant migration simulation under complex conditions can be carried out, structural errors existing in the model are effectively corrected based on a data driving method, the defect that a traditional underground water model is poor in simulation precision under the complex conditions is overcome, and the application scene of underground water pollutant migration simulation is expanded; according to the method, underground water pollution migration simulation can be carried out aiming at novel and macromolecular organic pollutants such as polycyclic aromatic hydrocarbon, the defect that a traditional underground water model cannot accurately describe pollutant and colloid co-migration behaviors is overcome, the uncertainty of a model prediction result is remarkably reduced, the accuracy and reliability of the model prediction result are improved, and the method is suitable for popularization and application. And the model prediction performance is improved.