1622 results about "Groundwater" patented technology

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 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 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 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 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 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 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 relates to the field of underground water pollution monitoring, in particular to a dynamic intelligent monitoring method and system for underground water pollution. The method comprises the following steps: constructing and updating an underground water solute transport model; generating a comprehensive pollution feature vector by using the obtained multi-source data which is related to the groundwater pollution and comprises a plurality of pollution indexes; respectively constructing a pollution source positioning model and a pollution diffusion model; triggering a pollution alarm according to the comprehensive pollution feature vector; according to the multi-source data and the current hydrogeological data, utilizing the pollution source positioning model to obtain a pollution source position; respectively utilizing the pollution diffusion model and the groundwater solute transport model to carry out prediction simulation to obtain first pollution distribution changing along with time and second pollution distribution changing along with time; and carrying out weighted fusion on the first pollution distribution and the second pollution distribution to generate predicted pollution distribution changing along with time. The problem that underground water pollution monitoring is not timely and accurate enough in the prior art is solved.

The invention relates to the technical field of underground engineering and pipe jacking construction, in particular to a large-diameter long-distance reservoir crossing rock pipe jacking design method. The method comprises the following steps: collecting parameters of a hard rock sample, and carrying out rock mass-underground water coupling stress field modeling to obtain a rock mass-underground water stress field distribution diagram; calculating a rock-water stress field density coefficient according to the rock mass-groundwater stress field distribution diagram; performing multi-parameter crossing path planning according to the rock-water stress field density coefficient to obtain a crossing path scheme set; calculating a path crossing resistance index according to the crossing path scheme set; determining an optimized crossing path scheme according to the path crossing resistance index; and performing segmented jacking force dynamic analysis according to the optimized crossing path scheme to obtain segmented resistance characteristics and a jacking configuration parameter scheme. According to the method, safe and efficient implementation of large-diameter long-distance reservoir crossing rock pipe jacking engineering is achieved by combining rock mass characteristic analysis, path optimization planning and jacking force dynamic control.

The invention discloses a tunnel or mine water gushing space-time prediction method and system coupled with a hydrodynamic numerical model, and the method comprises the steps: outputting multi-source data based on an identified and verified underground water numerical model, complementing the missing of measured data, quantifying the difference between the permeability characteristics of a fault and a normal stratum, and coupling the difference to a data system, and tunnel or mine excavation space data are merged. And constructing an LSTM-isolated forest-K neighbor regression coupling model, and configuring a multifunctional module to realize multi-scene data co-training. The preprocessed multivariate time series data is divided into a training set and a test set, hidden features are extracted through a coupling model, anomaly detection results are fused, a residual error correction model is synchronously trained, and hyper-parameters and weights are adaptively optimized according to multi-engineering prediction error feedback. And based on the trained coupling model, carrying out synchronous water gushing space-time prediction by adopting a window rolling strategy, and outputting prediction data meeting engineering precision in combination with residual correction. And reliable technical support is provided for safety prevention and control of engineering construction.

The invention provides a karst collapse early warning method and device, electronic equipment and a storage medium. The method provided by the invention comprises the steps of determining a first time sequence feature of surface displacement data, a second time sequence feature of groundwater dynamic data, a spatial feature of geological radar image data and a vibration feature of microseismic signal data, and generating a multi-modal fusion feature vector according to the first time sequence feature, the second time sequence feature, the spatial feature and the vibration feature; according to the multi-modal fusion feature vector and an early warning model, an early warning signal is obtained, and the early warning model is obtained by updating an early warning threshold value through a historical multi-modal fusion feature vector and a Transform-LSTM hybrid network by using a time sequence difference learning strategy; and performing validity judgment on the early warning signal according to the surface displacement data, the groundwater dynamic data and the micro-seismic signal data, and determining whether to perform early warning according to a judgment result. According to the method, the accuracy of karst collapse early warning can be improved.

The invention particularly relates to a hydrogeological analysis system and method based on big data, and relates to the technical field of hydrogeological analysis, and the method comprises the steps: placing a new model and an old model in an A / B test stage, and carrying out the parallel processing of real-time data; performing automatic judgment according to a preset performance index, and deciding whether to upgrade the candidate model to a new production model; and applying the model selected after decision making to hydrogeological analysis to solve the problem of long-term prediction precision under dynamic change of the hydrogeological system. According to the method, dynamic threshold monitoring, K-S outlier sample examination, sub-model optimization and A / B test smooth iteration processes are constructed, and a mechanism and machine learning coupling model and parallel calculation are combined, so that the model drift identification delay is reduced, the prediction precision is improved, scenes such as underground water over-mining prevention and control and pollution emergency are effectively supported, and the prediction accuracy is improved. And an accurate and efficient scientific decision basis is provided for water resource management.

The invention discloses an integrated intelligent management and control method and system for underground water pumping and injection based on the Internet of Things, and the method comprises the steps: carrying out the geological investigation of a target region, constructing a three-dimensional geological model, and planning the layout of a pumping and injection well group and a sensor network according to the three-dimensional geological model; deploying a monitoring network and collecting data based on the layout scheme, and fusing a three-dimensional geologic model to construct a polluted site digital twinborn body; groundwater situation data are extracted through the digital twinborn body, a pollutant migration path and a water level dynamic state are predicted by using an LSTM model, and pollution scene simulation information corrected by geologic features is output; by taking the simulation information as input and coupling geological parameters as constraints, generating a pumping and injection well group cooperative control strategy set by adopting a BLMFO double-layer multi-objective optimization algorithm; and finally, a control instruction is executed, the real-time situation is monitored in the repairing process, strategy change suggestions including the flow adjustment amplitude, the agent optimization scheme and equipment operation parameter correction are judged and pushed, the repairing efficiency is improved, and the method adapts to the complex geological environment.

The invention provides a saline-alkali soil underground water regulation and control method and device, electronic equipment and a storage medium, and relates to the technical field of land governance. Inputting the first historical monitoring information into a pre-constructed prediction model to obtain a predicted value of soil salinity in a future time period; the predicted value of the soil salinity is input into the analysis model, and the target water level of underground water in the future time period is obtained; wherein the target water level of the underground water is used for restraining the target value of the soil salinity to be smaller than a preset salinity threshold value and the target value of the soil humidity to be larger than a preset humidity threshold value; generating a water level adjusting strategy based on the target water level of the underground water, and controlling the opening or closing of the water pump based on the water level adjusting strategy. According to the method, the soil salinity in the future time period is predicted by acquiring the saline-alkali soil monitoring information, so that the target water level of the underground water is obtained, the water level regulation strategy is generated, and the perspectiveness, dynamic nature and stability of underground water level regulation are ensured.

The invention discloses an ecological flow guarantee method based on runoff prediction and supply. Meteorological, hydrological and other data of the Tongkeng river basin are collected, an SWAT model is constructed and verified to simulate runoff, and extended rainfall is analyzed based on an R / S method and a wavelet method. And constructing a surface water and underground water coupling model, and predicting underground water volume, water level and water quality. And ecological flow safeguard measures are formulated after water resource supply and demand balance analysis, wherein the ecological flow safeguard measures comprise optimal allocation of water resources, enhanced management, ecological water supplementation, water environment treatment, ecological restoration project development and the like. The method has the advantages that measure implementation subjects and progresses are defined, monitoring system evaluation effects are established, adjustment and optimization are performed according to results, ecological flow is guaranteed, sustainable utilization of drainage basin water resources and ecological environment protection are realized, remarkable social, economic and environmental benefits are achieved, and a scientific and effective method is provided for water resource management.

The invention relates to the field of intelligent monitoring, and particularly discloses an underground water environment monitoring method and system based on big data, and the method comprises the steps: firstly, decomposing complex water quality time sequence data into three components, namely a trend component, a season component and a residual error component through an STL decomposition technology, thereby effectively separating an inherent periodic rule of an underground water system from random disturbance; on this basis, trend and seasonal components are innovatively used as dynamic macroscopic backgrounds for interpreting the real meaning of residual components, then a normal disturbance mode under a specific background is deeply learned in combination with an LSTM auto-encoder, and finally early warning judgment is made by an SVM model. Through the mode, the method can effectively adapt to the periodic change of the groundwater environment, and accurately recognize the normal water quality fluctuation caused by natural factors, thereby remarkably reducing the false alarm rate, improving the monitoring sensitivity of real pollution events, and finally realizing the accurate dynamic evaluation and reliable early warning of the groundwater environment state.

The invention discloses a method for determining the suitable development area of a large-scale drip irrigation farmland in an underground water shallow-buried area, and the method comprises the following steps: coupling an MODFLOW model and an SWNCM-2D model based on programming software, and developing a coupling model suitable for water and salt migration and crop growth simulation of a saturated zone and an unsaturated zone of the large-scale drip irrigation farmland in the underground water shallow-buried area; according to lysimeter underground water burial depth control test data, calibrating and verifying key parameters of the coupling model, performing multi-scenario simulation of different underground water burial depths, and determining an appropriate underground water burial depth under a drip irrigation condition; setting scenes with different drip irrigation farmland area proportions, simulating by adopting a coupling model, and determining a suitable development area of the large-scale drip irrigation farmland in the underground water shallow buried area by taking a suitable underground water buried depth as a control standard; according to the scheme, through multi-model coupling, multi-process simulation and multi-scene analysis, technical support and quantitative basis are provided for development and field management of large-scale drip irrigation farmland.

The invention provides an underground water environment monitoring system and method, and the method comprises the steps: carrying out the three-dimensional fluorescence spectrum full-wave band scanning of a known type of pollution source reference sample in a target monitoring region, and obtaining a three-dimensional fluorescence spectrum data set; performing characteristic analysis on the three-dimensional fluorescence spectrum data set to obtain fluorescence characteristic components, and determining a characteristic excitation wavelength corresponding to each fluorescence characteristic component; the classification contribution degree of each characteristic excitation wavelength is evaluated, and a characteristic excitation wavelength combination during source tracing of the pollution source is obtained through screening; performing fixed wavelength scanning on the to-be-detected underground water sample in the target monitoring area according to the characteristic excitation wavelength combination, and determining the initial type of the pollution source; and determining the relative contribution degree of the type of the pollution source of the to-be-detected underground water sample, simulating the migration trend of the pollution plume according to the underground water migration and diffusion model, and generating the position of the pollution source of the to-be-detected underground water sample. By adopting the scheme of the application, the pollution source of the underground water can be quickly identified and positioned at low cost.

The invention relates to the technical field of computer simulation, and discloses a coal mine underground reservoir environment risk assessment method and system, and the method comprises the steps: constructing a digital twinborn body of a coal mine underground reservoir; establishing a risk assessment index system; collecting monitoring data corresponding to the index system in real time; calculating risk coupling factors among different dimension indexes; according to the risk coupling factor and the real-time numerical value of each index, dynamically adjusting the weight of the index system, and generating a dynamic weight set; calculating a current comprehensive risk level; and extracting physical field parameter values in the real-time monitoring data, inputting the physical field parameter values into a multi-physical field coupling simulation engine for simulation, and outputting a prediction report. According to the invention, dynamic assessment and advanced early warning of the environmental risk of the coal mine underground reservoir can be realized, the risk identification precision and the emergency response capability are improved, and the method is suitable for safety management and control of the whole life cycle of the underground reservoir under complex geological conditions.

The invention discloses a cross-medium transmission simulation device and method for pollutants between soil and underground water, and relates to the technical field of environmental governance, and the cross-medium transmission simulation device for pollutants between soil and underground water comprises a soil layer system and an underground water system. The soil layer system comprises a base and a soil box arranged on the base in the vertical direction, the soil box is used for containing test soil, and the base is provided with a first water permeable hole used for being communicated with the soil box. The underground water system comprises a water tank, a mounting opening is formed in the upper side of the water tank and used for allowing the base and the soil box to sequentially penetrate through, and the height of the inner side of the water tank is larger than that of the base so that water in the water tank can penetrate through the first water permeable holes and make contact with a soil layer in the soil box. By comparing the content of the pollutants at the same position, the blocking effect of the blocking agent on the pollutants can be evaluated, and the blocking effect of the blocking agent during cross-medium transmission of the pollutants between the soil and the underground water can be evaluated on the whole.

The invention relates to the technical field of collaborative traceability, in particular to a soil-groundwater multi-medium pollutant collaborative traceability method, which comprises the following steps: synchronously collecting a soil-groundwater conversion sample at an oxidation-reduction interface in a diving surface fluctuation zone of a polluted site, and recording three-dimensional coordinates of a sampling point and a groundwater dissolved oxygen threshold value; detecting valence state change of pollutants in the conversion sample, identifying a morphological transition marker caused by mutation of a medium environment, and generating an interface transition feature set comprising a marker concentration gradient; and based on the concentration gradient direction of the interface transition feature set, in combination with underground water flow velocity field data, reversely tracking a pollutant migration path, and outputting a pollution source position coordinate and a dominant conversion medium type. According to the method, the migration vector module value difference, the form transition amplitude response difference and the path distance attenuation effect are considered, the position of the pollution source is calculated through weighted reverse integral, and the adaptability of the traceability algorithm to a complex interface multi-source pollution scene is remarkably enhanced.

The invention discloses a single-hole pressure adjusting method, device and equipment for a water curtain test of an underground water-sealed cave depot and a storage medium, and relates to the technical field of geological engineering.The method comprises the steps that firstly, a rock mass acoustic impedance spectrum is collected, intrinsic mode decomposition is carried out to extract geologic feature components, and the rock mass acoustic impedance spectrum is obtained; processing the target pressure value, the current pressure value and the geologic feature component by using a pressure-opening coupling model based on acoustic feature extraction, time sequence dynamic analysis and physical constraint decoding to obtain a reference valve opening; then, a water curtain hole valve is adjusted according to the reference valve opening degree, and the pressure change acceleration is monitored in real time; calculating an opening compensation increment and a damping attenuation coefficient based on the pressure change acceleration, and further generating a target valve opening; and finally, the valve is adjusted to the target opening degree, so that the water curtain hole reaches the target pressure value. According to the invention, high-precision self-adaptive adjustment of the pressure of a single water curtain hole can be realized in the water curtain test of the underground water-sealed cave depot.

The invention relates to the technical field of hydrological monitoring, and discloses a regional groundwater reserve change dynamic monitoring method based on gravity satellite time series data analysis. According to the method, the multi-source data scale effect and observation noise are effectively eliminated, the physical reliability and resolution of groundwater signal extraction are improved, and the recognition precision and early warning perspectiveness of the abnormal loss trend are enhanced. A full-chain monitoring closed loop of multi-source satellite observation, high-precision physical inversion and dynamic statistical benchmark is constructed, multi-dimensional environment data is aligned, a component separation strategy based on multi-element physical mechanism constraint is established based on a water balance principle, and anomaly diagnosis is performed in combination with a self-adaptively updated long-time-sequence historical database.

The invention provides an underground water monitoring method. The method comprises the following steps: acquiring underground water level monitoring data in real time; the corresponding water level monitoring data range in the first preset time period is compared with a water level amplitude variation abnormal threshold value, and the water level abnormal level of each point position is obtained; according to the fitting relation between the historical water level amplitude variation data and the land subsidence amplitude variation data, constructing a multi-stage early warning threshold model related to water level early warning and water level amplitude variation early warning; and comparing the groundwater level monitoring data of the point location with the highest water level abnormal level with various early warning thresholds in the multi-level early warning threshold model to obtain the groundwater early warning level of the corresponding point location. According to the method, the quantized multi-stage early warning threshold model is constructed through the fitting relation of settlement-water level, the invasion of the external water can be early warned more accurately, the risks of the invasion of the external water, land subsidence, ecological degradation and the like can be remarkably reduced, and sustainable management of water resources is facilitated.

The invention discloses an intelligent groundwater storage variable prediction system based on multi-source data fusion and parameter optimization, and relates to the technical field of groundwater storage change prediction, and the system comprises a data collection module, a hydrological sensor connected with the Internet of Things, a satellite remote sensing data interface and a meteorological data interface. According to the intelligent groundwater storage variable prediction system based on multi-source data fusion and parameter optimization, the problem of prediction time lag caused by data updating lag, data spatial-temporal scale inconsistency and parameter stiffness of a groundwater storage change evaluation system is solved by constructing a double-circulation collaborative architecture of a real-time assimilation ring and a parameter evolution ring. High-frequency assimilation is used for fusing multi-source real-time data, and it is ensured that model input is synchronous with a real environment state; the prediction system continuously tracks the transient process of an underground water system, and the timeliness and reliability of underground water storage volume change prediction under the scenes of extreme rainfall, extreme drought, high-intensity mining and the like are effectively improved.

The invention relates to the technical field of geological engineering and underground water simulation, and discloses a regional underground water simulation method and system based on a physical mechanism and deep learning, and the method comprises the steps: converting the static attributes of an observation well into the embedding of nodes and edges through a graph neural network, and obtaining spatial features; according to the dynamic input of the observation well, modeling time sequence response of the underground water system under external dynamic driving through a long short-term memory neural network; deep fusion of spatial features and time dynamics is realized through a feature interaction mechanism, and a groundwater level simulation value is generated; combining a water balance constraint with a relative water level consistency constraint between observation wells to jointly construct a composite loss function for quantifying a difference between an analog value and a real observation value, and guiding parameter updating; the time-space dynamic and physical mechanism can be sensed synchronously, and the method is more reliable and efficient.