630 results about "Ground water level" patented technology

The invention provides a mine water disaster monitoring and early warning method and system based on multi-source heterogeneous data fusion, and the method comprises the steps: collecting multi-source data of a mining area, carrying out the time-space alignment of the multi-source data, and generating a data set, the multi-source data comprising remote sensing data; preprocessing the data, inputting the preprocessed data into a multi-modal fusion network, and extracting surface water body distribution, lithologic permeability, underground water level and structural fracture characteristics to obtain a three-dimensional hydrogeological static model; the hydrological numerical model based on physical driving is coupled with the static model, and the dynamic model is used for simulating the dynamic change of an underground water flow field and a pollutant diffusion path; based on the dynamic model updated in real time, multi-target collaborative evaluation is carried out to evaluate the mining area water resource, ecological and social collaborative effect; and calling an unmanned aerial vehicle to inspect a leakage position or a settlement position in the hydrogeological risk map based on a multi-target collaborative evaluation result. According to the method, the prediction accuracy is improved through the multi-source data.

The invention discloses a mine reclamation effect evaluation method based on a multi-temporal remote sensing image, and belongs to the field of mine reclamation effect evaluation, and the method comprises the steps: obtaining and preprocessing multi-source remote sensing data, and obtaining a standardized multi-temporal data set; performing image registration and radiation correction on the standardized multi-temporal data set to obtain a correction data set with consistent space and consistent radiation; constructing a multi-dimensional feature data set based on the correction data set, wherein the multi-dimensional feature data set comprises surface morphological features, vegetation health features, soil temperature features and underground water level change features; extracting a surface form feature vector according to the multi-dimensional feature data set, and generating a vegetation health distribution map, a soil temperature feature map and an underground water level change distribution map; and fusing the surface form feature vector, the vegetation health distribution map, the soil temperature feature map and the underground water level change distribution map, constructing a comprehensive index system, and outputting a mine reclamation effect evaluation result. According to the method, the accuracy and comprehensiveness of reclamation effect evaluation are remarkably improved.

The invention provides a shield tunnel dynamic settlement compensation construction method based on an adaptive optimization algorithm, and the method comprises the steps: collecting the ground surface settlement, soil stress and underground water level data in real time through an Internet of Things sensor, achieving the data preprocessing and feature extraction in combination with an edge calculation node, constructing a three-dimensional geologic model, integrating the historical engineering data through transfer learning, and achieving the dynamic settlement compensation of a shield tunnel. The method comprises the following steps: identifying a high-risk area by using a clustering algorithm, designing a hybrid adaptive optimization framework with fusion of random forest and incremental learning, dynamically adjusting shield tunneling speed and soil bin pressure construction parameters, introducing an adaptive step length mechanism to cope with geological complexity change, and identifying a settlement abnormal mode through Fourier transform. Precise compensation is achieved in combination with a layered grouting strategy, the pressure of a soil bin is dynamically adjusted based on a hydraulic system, a closed-loop feedback mechanism is established, the predicted deviation rate is compared with an actual monitoring value, model parameters and the compensation strategy are continuously optimized, the settlement control precision is improved, and the construction risk is reduced.

The invention provides a mine slope risk assessment method and system based on multi-source data space-time fusion, and relates to the technical field of mine monitoring, and the method comprises the steps: obtaining geological and engineering data, and constructing a basic model representing a slope three-dimensional space structure; collecting multi-source heterogeneous monitoring data on a mine slope field, and aligning and fusing the multi-source heterogeneous monitoring data with the basic model in a space-time dimension to generate a continuous dynamic parameter field; and setting a data fusion model, and taking the basic model and the dynamic parameter field as input to obtain a four-dimensional space-time fusion risk field. According to the method, the basic model representing the three-dimensional space structure of the slope is constructed, and a unified space-time bearing base is provided for all heterogeneous monitoring data, so that originally isolated data such as GNSS displacement, deep displacement, blasting vibration and underground water level can be fused in a unified coordinate system; the problem of data splitting in the prior art is fundamentally solved, and integral and integrated expression of slope engineering and geological conditions is formed.

The invention discloses a slope early warning method and system based on a knowledge graph, and relates to the technical field of multi-source monitoring slope early warning, and the method comprises the steps: 1, unifying laser, radar, satellite remote sensing and underground water level monitoring flow into an index-structure-disaster situation graph containing traceability metadata; 2, generating an instability trigger coefficient by using a gradient lifting model driven by a coupling trend and credibility; step 3, automatically outputting short messages, broadcasts and social contact templates, and implanting abstract codes for publishing; 4, comparing the returned text in real time, marking deviation nodes according to graph consistency, and tracing a source link; and step 5, performing Hash solidification on the core early warning segment and spreading the performance to the alliance chain, and writing back the knowledge graph optimization template and channel. According to the scheme, multi-source data alignment is achieved, early warning is accurate and reliable, cross-medium semantic consistency and evidence chain traceability are achieved, and the requirement of the whole mountain disaster prevention process is met.

The invention discloses a surface water and underground water combined regulation and control method considering runoff and underground water level recovery, and belongs to the technical field of comprehensive regulation and control of water resources. According to drainage basin water resource supply and demand conditions and engineering characteristics, on the basis of fully considering multiple factors such as economy, society and ecology, organic combination of multiple regulation and control measures is implemented, and the method becomes an important way for achieving efficient combined utilization of water resources, restoring the underground water level, improving the regional ecological environment and guaranteeing food safety. Besides, in order to comprehensively evaluate the combined regulation and control effect of the surface water and the underground water, an evaluation index system of the system needs to be established and is used for evaluating the recovery conditions of the river runoff and the underground water level. By quantitatively evaluating actual effects of different regulation and control measures, a decision maker can be helped to judge whether water resource distribution and use are reasonable or not, the regulation and control measures are adjusted and optimized according to evaluation results, an appropriate surface water-underground water combined regulation and control scheme is selected, and reference can be provided for sustainable management of drainage basin water resources.

The utility model discloses an underground water level monitor for geotechnical engineering, which relates to the technical field of water level monitoring and comprises a probe rod body and a protective sleeve sleeved outside the probe rod body, and the top end of the probe rod body is provided with a traction rope penetrating out of an annular seat at the top of the protective sleeve; an overturning frame is rotationally installed on the side face of the bottom of the protective sleeve, a floating plate and a plugging frame are arranged at the two ends of the overturning frame respectively, and the plugging frame is arranged at the end, close to the protective sleeve, of the overturning frame; a floating plate is arranged at the upper part of the floating plate; by means of the torque change design of the floating plate, the overturning frame and the plugging frame, when the floating plate does not enter water, the plugging plate covers the open groove in the lower end of the protective sleeve, and rock soil and other sundries can be prevented from entering the protective sleeve to affect the probe rod; when the floating plate enters water, the blocking plate is moved away, so that the probe rod can be in contact with the water body in time to monitor the water level.

A simulation method for characterizing the spatiotemporal changes of groundwater levels, which belongs to the technical field of computer machine learning; includes the steps of: obtaining long-term groundwater level data based on long-term groundwater monitoring wells; superimposing multiple hydrogeological parameter information based on groundwater level data; and constructing a regional neural network model with physical mechanism by using a two-dimensional groundwater seepage equation serving as a physical mechanism, thereby simulating the temporal and spatial evolution of regional groundwater levels. The present invention can strengthen the rational use of groundwater resources, implement scientific and effective supervision, and provide a scientific basis for protecting regional groundwater safety and promoting the sustainable development of groundwater resources.

A knowledge graph-driven groundwater-oriented method for building risk warning includes: extracting a relationship quadruple between groundwater level change and building structure change based on collected groundwater level data and building data; creating a cross-domain knowledge graph based on the relationship quadruple, and associating two different fields; updating the cross-domain knowledge graph in real time to realize the building risk warning caused by groundwater level changes. The risk warning is based on the causal relationship reflected in the factual data, making the risk warning more accurate, which can effectively solve the problem of the lack of risk warning system for buildings due to groundwater level changes in the related art.

The invention discloses an underground water seepage analysis and prediction method based on physical-data cooperative driving, and belongs to the field of underground water seepage, and the method comprises the following steps: establishing a hydrogeological numerical model, carrying out seepage simulation calculation, and carrying out comparison verification with field monitoring data to realize accurate mapping; meanwhile, a machine learning data set is constructed by utilizing a numerical simulation result, a prediction model based on a Stacking integrated learning structure is established in combination with field data of a construction roadway, a water curtain layer and an oil storage cavern layer, and the water seepage amount or the underground water level after excavation of a rock mass in front of a tunnel face is predicted by taking geological, hydrological and construction parameters as input. According to the method, a physical mechanism and data driving are fused, the prediction precision and interpretability are remarkably improved, and a scientific basis is provided for cave depot project grouting and excavation optimization.

The invention discloses an airport area underground water and surface water system coupling seepage regulation and control method and system, and the method comprises the steps: employing a multi-source data fusion investigation mode to find out regional stratum and structure characteristics, and determining an underground water occurrence migration rule and a surface water and underground water supplement and drainage relation; constructing a coupling seepage model of the underground water and the surface water system under the current condition by applying a numerical simulation method, and defining a dynamic association mechanism of the underground water and the surface water system in time and space; based on a simulation result, determining a transformation scheme that a main stream adopts a double-hole box culvert and a branch stream adopts a single-hole box culvert, and arranging an electric gate at the box culvert; arranging monitoring points of groundwater level, pore water pressure and surface water system flow in combination with field spring water and well distribution, and constructing a cooperative monitoring network; the coupling seepage law of underground water and surface water systems is analyzed based on monitoring data, and the opening degree of a box culvert electric gate is dynamically adjusted to control rising of the underground water level in the flood period. The stability of a water system in an airport area is ensured.

The invention discloses a multi-source geological disaster information intelligent processing method, and particularly relates to the technical field of geological disaster monitoring. The method comprises the following steps: collecting multi-source monitoring data such as remote sensing images, surface deformation, meteorology, underground water level and seismic micro-motion, and preprocessing to form a feature vector set; establishing a credibility weight matrix based on data continuity and consistency evaluation; main disaster-inducing factor combination features are extracted through an adaptive feature extraction model; constructing a disaster evolution graph in combination with historical disaster data; in the continuous monitoring process, when the node attribute variation rate in the atlas exceeds a threshold value and an abnormal path chain is formed, geological disaster early warning output is triggered; according to the method, heterogeneous data fusion and disaster factor dynamic modeling can be realized, and disaster prediction accuracy and response efficiency in a complex environment are improved.

The invention discloses an urban underground space water level risk dynamic assessment method and device, and relates to the technical field of water level risk assessment, and the method comprises the steps: collecting underground space utilization characteristics of a preset city; collecting underground space geologic structure information of the preset city; the method comprises the following steps: collecting underground water level and rainfall information in real time through a laid sensor network, performing risk grading evaluation, and generating a water level risk grade; and performing underground water level risk prediction according to the water level risk level. According to the method, the technical problem that the underground water level risk management scientificity is insufficient due to the lack of dynamics and accuracy in urban underground space water level risk assessment in the prior art is solved, and the dynamic assessment and prediction of the urban underground space water level risk are realized; and the scientificity and accuracy of underground water level risk management are improved.

The invention relates to the technical field of hydraulic engineering safety monitoring, and particularly discloses a reservoir dam safety assessment method based on strategy optimization, which comprises the following steps: collecting sediment accumulation rate and underground water level change rate data in real time through a distributed sensor network, and extracting multi-scale features by adopting variational mode decomposition and wavelet packet transformation; constructing a sedimentary anomaly characteristic value and a water level disturbance characteristic value in combination with the energy entropy and the fluctuation amplitude; fusing the two types of features into a dam body safety feature vector, inputting the dam body safety feature vector into a deep learning model for multi-dimensional risk assessment, and outputting a dam safety level; furthermore, a feedback control loop is constructed based on a digital twinning technology and a meta-learning framework, dynamic adjustment of monitoring frequency and an early warning threshold value and automatic generation of a reinforcement strategy set are realized, a closed-loop intelligent regulation and control mechanism is formed, and the real-time performance, the accuracy and the autonomous decision-making capability of dam safety management are improved.

The invention belongs to the technical field of coal mining, and discloses a coal mine collapse monitoring system and method, and the method comprises the steps: a deformation monitoring module carries out the deformation monitoring of a coal mine; the displacement stress monitoring module monitors rock mass displacement, stress state and strain change of a coal mine goaf or a potential collapse area; the underground water monitoring module measures the change of the underground water level in real time; the route planning module plans a cruise route of the unmanned aerial vehicle; the image acquisition module performs low-altitude flight shooting on a coal mine area; the image preprocessing module preprocesses the scanned image; the abnormity identification module performs feature extraction on the preprocessed image and identifies the abnormal condition of coal mine collapse; the comprehensive evaluation module performs multi-source data fusion and establishes a multi-parameter early warning model; when the monitoring data exceeds a preset threshold value, the alarm module triggers an early warning signal. Through multiple monitoring means, the functions of real-time continuous monitoring, intelligent analysis and evaluation and the like are achieved, and potential collapse risks can be found in time.

The invention belongs to the technical field of hydrogeology and intelligent control, particularly relates to an underground water level dynamic regulation and control method and system based on digital twinning, and aims to solve the problems of one-sided perception, static model, extensive decision and single feedback of traditional regulation and control. The method comprises the following steps: collecting multi-source monitoring data and constructing a data set through cross-scale calibration; constructing a multi-field dynamic coupling digital twinborn model, and introducing a dynamic coupling coefficient to deduce a risk evolution field; calculating a variable coefficient of the risk value of each physical field based on the risk evolution field, and generating a comprehensive risk value; and matching the risk threshold to generate a deep and shallow layered regulation and control instruction. The multi-field dynamic coupling breaks the static limitation of the model, the dynamic weight based on the variable coefficient ensures that the regulation and control decision can preferentially respond to the key physical field with high absolute risk level and large spatial fluctuation, and the full-region visual tracking and accurate management and control of the underground water level and the geological risk are realized.

The invention discloses a real-time dynamic monitoring and early warning system and method for house crack deformation, relates to the technical field of building safety monitoring, and aims at mastering the influence of underground water level fluctuation on a foundation in real time, ensuring the accuracy of crack propagation analysis, obtaining a crack risk index Lf and performing house safety assessment through underground water level related data acquisition. House safety abnormity is identified, a soil expansion factor Tr and a water level change influence factor psi are calculated, scientific support is provided for crack prediction, crack development trend is predicted, risk assessment is carried out, house maintenance initiative is improved, future crack change data are collected and fed back to a crack change prediction model, long-term monitoring accuracy is improved, and the method is suitable for popularization and application. Errors are reduced, the house maintenance cost is reduced, and the scientificity and reliability of safety early warning are improved.

The invention discloses a dynamic prediction method for a deformation joint of an underground comprehensive pipe gallery. The method comprises the following steps: S1, collecting and fusing multi-source monitoring data; s2, data preprocessing and feature engineering; s3, constructing a dynamic prediction model; s4, dynamic prediction and performance evaluation; s5, early warning and decision support are carried out, in the step S1, temperature field data including the air temperature in the pipe gallery, the concrete temperature (inner and outer surfaces) of the pipe gallery structure and the soil temperature outside the pipe gallery are acquired, and the measuring range ranges from-40 DEG C to 80 DEG C; according to the method, a multi-source monitoring data acquisition and dynamic prediction model system is established, continuous monitoring and trend prediction of the deformation joint of the underground comprehensive pipe gallery are achieved, multi-dimensional data such as the temperature field, the soil pressure and the underground water level are integrated, time sequence analysis is combined, and the deformation joint of the underground comprehensive pipe gallery is obtained. The development rule of the deformation joint can be accurately captured, and a prospective evaluation basis is provided for the safety of a pipe gallery structure.

The invention is applicable to the technical field of underground water level monitoring and sampling, and provides an underground water level monitoring and sampling device for hydraulic engineering, which comprises a base, the base is rotatably connected with a plurality of adjustable supporting assemblies for supporting and limiting, the upper end face of the base is provided with a winding mechanism, and the winding mechanism is wound with a pull rope. A sampling barrel is fixedly arranged at one end of the pull rope, the winding mechanism is connected with a movable limiting assembly, and the movable limiting assembly can limit the pull rope in the horizontal direction; the device further comprises a falling speed optimization system which can regulate and control the falling speed of the sampling barrel. Under the interference of multiple factors such as wind speed sudden change, underground water flow velocity fluctuation and pull rope elasticity mismatching, the rotating speed of the winding mechanism can be dynamically adjusted, sampling barrel swinging and track deviation are restrained, meanwhile, mechanical damage caused by sudden change of the rotating speed is avoided, and the sampling efficiency and data reliability are improved.

The invention relates to the field of hydrogeology and environmental engineering, and discloses an underground water anomaly identification and early warning method based on a multi-time-sequence spatial-temporal change rate field, which comprises the following steps: acquiring underground water monitoring data, constructing a multi-time-sequence underground water level burial depth space field, constructing a spatial-temporal change rate field, acquiring a comprehensive saliency map, intelligently identifying a dynamic descending area of underground water, and performing early warning. Identifying and classifying the dynamic descending area, quantifying the dynamic index of the dynamic descending area, and performing graded early warning; historical data of known groundwater abnormal events are obtained, and adaptive adjustment is carried out on the corresponding adaptive threshold parameters in the previous steps. According to the scheme, a static water level field is converted into a dynamic space-time change rate field, the form change trend of the water level field of the whole area can be obtained, and the problem that only single-point water level change can be obtained in a traditional monitoring method is solved; graded early warning based on different development modes of the dynamic descending area is realized; the method does not depend on geological parameters difficult to obtain, and is simple and easy to implement and low in cost.

The invention discloses a powder spraying pile composite roadbed deformation prediction method, and particularly relates to the field of roadbed settlement prediction, comprising the following steps: in an edge calculation node, respectively constructing an underground water level change event, a construction stage event, a soil consolidation stage event and a traffic load cycle event into independent event time chains; the event time chain is recorded by taking the occurrence moment of the event, the duration of the event and the interval duration between the events as a time step unit; and performing splitting operation on the time step units of each event time chain, and forming a time granularity matrix according to the duration difference between the time step units. A plurality of types of discrete events such as water level, construction, consolidation, traffic load and the like are uniformly disassembled into time step length units, and a time granularity matrix and a time dislocation vector are constructed, so that the rhythm difference and dislocation relationship of the events on different time scales can be quantitatively expressed; and solving the transition of the settlement stage by taking the result as the observation input of the variational Markov model.

The invention relates to the technical field of slope disaster monitoring, in particular to a high and steep slope geological disaster monitoring method and system based on multi-source data fusion. The method comprises the following steps: tracking surface deformation through PS-InSAR time sequence analysis and atmospheric phase correction to obtain surface deformation characteristics; identifying the apparent diseases of the slope, and extracting spatial and temporal distribution characteristics of the apparent diseases of the slope; analyzing spatio-temporal evolution characteristics under geologic structure constraints by utilizing slope rock mass structure characteristics and the earth surface deformation characteristics; according to underground water level dynamic and potential sliding surface weakening features and the slope apparent disease spatial and temporal distribution features, extracting disaster-causing key factor features after cooperative correction; and combining the disaster-causing key factor characteristics, the true three-dimensional geological environment background characteristics and the spatio-temporal evolution characteristics to analyze the comprehensive early warning grade and the potential instability mode of the landslide. Scientific support is provided for high and steep slope geological disaster prevention and control, and engineering construction and operation safety can be guaranteed.

The invention belongs to the technical field of surface collapse group simulation, and discloses a split mounting type surface collapse group simulation experiment system. The system comprises a supporting steel frame, a rainfall simulator, a split mounting type surface collapse model test box, a water level control box, an overflow device, a split mounting type karst pipeline, a split mounting type karst water cavity simulation box, a water supply box, a peristaltic pump and various monitoring devices. Through the split mounting type structural design, the number of collapse points, the distance, the cavity shape, the karst pipeline connectivity, the underground water level, the rainfall intensity and other key parameters can be flexibly adjusted, and multi-working-condition simulation of a surface collapse group is achieved; meanwhile, through cooperative work of various monitoring devices such as a laser displacement sensor and a pore water pressure sensor, multi-physical-quantity data in the collapse process are collected in real time. According to the invention, the problems of lack of surface collapse group simulation capability and poor parameter adjustability in the prior art are solved, and experimental support can be provided for research and prediction of the development mechanism of the surface collapse group.

The invention discloses a self-calibration and drift compensation method for an automatic underground water monitoring station, and the method comprises the following steps: 1, transmitting a reference measurement starting instruction to an underground bubble method device by an edge calculation gateway, forming a reference data pair by a bubble method water level reference value and a reference acquisition moment, and writing the reference data pair into a reference data cache region; 2, the edge computing gateway creates a state storage structure and a covariance storage structure; and step 3, the edge computing gateway reads a drift amount estimation value from the state storage structure as a drift compensation amount, and when a drift estimation standard deviation exceeds a set threshold, bubble method hardware reference acquisition is triggered. According to the invention, the problems of high manual calibration cost and lack of independent reference support in pure software estimation in the prior art are solved, so that a monitoring station can stably operate for a long time under an unattended condition and continuously output high-precision underground water level monitoring data.

The invention relates to the technical field of soil treatment, in particular to an integrated saline grainfield soil improvement and remediation method. According to the method, precise irrigation, concealed pipe drainage, salt-tolerant crop planting and bioremediation technologies are comprehensively applied, and systematic treatment of the salinized soil is achieved. Precise irrigation dynamically regulates and controls the leaching depth and frequency on the basis of real-time soil salinity and moisture data, the underground water level is intelligently controlled in combination with an underground pipe drainage network, salt accumulation is effectively reduced, and water resource waste is avoided; according to the salt-tolerant crop and green manure rotation mode, salt damage is reduced through plant salt absorption and root system nitrogen fixation, soil organic matter accumulation and microbial community reconstruction are promoted through application of a microbial agent and biochar, and a sustainable soil improvement mechanism is formed. The intelligent monitoring system integrates multiple types of sensors, collects key indexes such as salinity, nutrients and pH values in real time, predicts the salinization trend and regulates and controls irrigation, fertilization and drainage equipment in a linkage mode, full-process automatic management is achieved, and the management precision and efficiency are remarkably improved.

The invention provides a large-scale agricultural irrigation area grid scale underground water level spatial and temporal distribution efficient prediction method, and belongs to the technical field of underground water prediction.The method comprises the steps that firstly, an SWAT model of a drainage basin where an irrigation area is located and an MODFLOW model covering the irrigation area are constructed respectively, the SWAT model and the MODFLOW model are coupled to obtain an SWAT-MODFLOW model, and parameter correction is conducted; secondly, an irrigation area underground water level data set is constructed through scene combination and model simulation and used for training and screening the LSTM model with the highest precision, the optimal control range of each LSTM model is determined through space compression and reconstruction, and a multi-LSTM model is obtained; and finally, carrying out parallel calculation on the multiple LSTM models to predict the spatial and temporal distribution of the grid scale underground water level of the irrigation area. According to the method, the optimal control range of each LSTM model is determined through space compression-reconstruction, the prediction of the underground water level spatial and temporal distribution of the grid scale of the large-scale agricultural irrigation area is finally realized through multi-LSTM model parallel calculation, and the prediction efficiency is improved on the premise of ensuring the prediction precision of the underground water level of the irrigation area.

The invention relates to the technical field of underground water state evaluation, and discloses an underground water level dynamic evaluation method based on multi-source data mapping and fluid model correction. The invention aims to solve the technical problems of insufficient underground water level monitoring precision and lack of space details caused by low spatial resolution of existing satellite gravity detection data and difficulty in accurately separating a deep underground water change signal from a land total water reserve signal. According to the method, through space-time reference unification of multi-source heterogeneous data, high-resolution surface texture features are utilized to guide a low-resolution gravitational field to carry out space downscaling reconstruction; surface water body and soil water reserve signals are removed layer by layer in combination with spectral characteristics and a thermal inertia principle; and introducing measured data to construct a spatial error correction curved surface of specific yield parameters, and identifying the underground water funnel by using an image connected domain analysis technology.

The invention relates to the field of foundation pit monitoring, and discloses a foundation pit monitoring method and system based on a regression prediction algorithm. Comprising the steps that displacement, stress, underground water level, environmental factors and acoustic emission signals are collected, monitoring data are subjected to missing measurement compensation and noise reduction processing, and a multi-dimensional feature sample is constructed; performing fusion modeling by using static regression, LSTM dynamic prediction and spatial correlation regression, introducing an adaptive weight module to realize dynamic weighting, and generating a multi-scenario prediction curve in combination with hysteresis effect correction and scenario simulation; the optimization function and dynamic threshold unit performs early warning judgment and outputs risk levels and disposal suggestions; and furthermore, abnormal data are identified and compensated through a sensor reliability evaluation module, so that the continuity and stability of prediction are improved. The system is composed of a data acquisition terminal, a preprocessing module, a feature extraction module, a regression prediction module, an adaptive weight fusion module, a dynamic threshold adjustment unit, a sensor reliability evaluation module, an early warning judgment module and a visual platform.

The invention discloses a regional groundwater spatio-temporal evolution modeling and prediction method based on a graph neural network. The method is specifically implemented according to the following steps: step 1, collecting research region data and performing preprocessing; step 2, constructing a static boundary structure under hydrogeological constraints; step 3, extracting multi-scale time sequence features based on the Fourier neural network; 4, constructing a spatial dependency integration model based on the graph attention network; 5, introducing a dynamic graph structure to learn a modeling cross-regional association relationship; and step 6, predicting the dynamic change of the underground water level based on the graph Fourier network. The method solves the key technical problems of insufficient spatial-temporal feature coupling, limited adaptive capacity to hydrogeological heterogeneity and limited cross-regional generalization ability of an existing groundwater prediction model under complex hydrogeological conditions.

The invention provides a coastal area foundation pit dewatering system and method, and belongs to the technical field of foundation pit dewatering, the coastal area foundation pit dewatering system comprises a foundation pit, a plurality of light well points, a deep tube well and an electroosmosis auxiliary module, and the light well points are annularly arranged in a shallow layer area on the periphery of the foundation pit; the deep tube well extends to a deep area from the ground; and a plurality of electro-osmosis auxiliary modules are arranged in the peripheral clay layer area of the foundation pit. The annularly-arranged light well points evenly intercept shallow underground water around the foundation pit, the deep pipe wells can rapidly reduce the deep underground water level, and the drainage problem of a low-permeability clay layer area is effectively solved through the synergistic effect of the arranged electro-osmosis auxiliary modules and the well points / pipe wells; the synchronous precipitation uniformity of the complex soil layer is improved, layered targeted precipitation design is adopted in a shallow area, a deep area and a clay layer area, and the overall precipitation efficiency is improved. According to the foundation pit dewatering system in the coastal area, the problem that in the prior art, in the environment with complex hydrogeological conditions, the dewatering efficiency of a single dewatering measure is low is solved.