549 results about "Groundwater pollution" patented technology

The invention relates to the technical field of environment monitoring, in particular to an underground water pollution source traceability identification method and system, and the method comprises the following steps: S1, collecting the flow velocity, flow direction and water level change data of underground water in a polluted region in real time; s2, constructing a preliminary underground water flow model; s3, simulating a migration path of pollutants in underground water, and predicting a potential pollution source position; s4, processing the collected underground water flow velocity and pollutant diffusion path data, and removing abnormal data interference; s5, generating a spatial distribution map of the potential pollution source in combination with a geographic information system; and S6, verifying pollutant components and concentration distribution thereof, and confirming the accuracy of a traceability result. According to the invention, by combining a multi-pollutant traceability algorithm, an underground water flow model and a geographic information system technology, a pollutant migration path is accurately simulated and a pollution source spatial distribution map is generated, so that the precision and reliability of underground water pollution source traceability are greatly improved.

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 the technical field of environment monitoring, in particular to an underground water pollution real-time monitoring method and system, and the method comprises the following steps: analyzing the underground water flow direction and original pollution records in geographic information, combining the geologic structure and hydrological characteristics of a monitoring area, and through the water flow propagation characteristics; and marking the position of the pollution source and matching the pollution range to generate a matching result of the pollution source and the range. According to the invention, the underground water flow direction, the pollution record and the geological and hydrological characteristics are analyzed, the position and the range of a pollution source are accurately marked, the identification precision and the monitoring pertinence are improved, monitoring points are deployed at key positions, diffusion information is extracted in real time, an early warning threshold value is dynamically generated, early warning is issued in time, and emergency response is started, so that the pollution control efficiency is improved; rapid development of isolation and water quality treatment is ensured, closed-loop adjustment and optimization of monitoring parameters are realized, so that the method dynamically adapts to environmental changes, and comprehensive control of groundwater pollution is realized.

The invention relates to the technical field of water quality monitoring, in particular to a mining area groundwater environment monitoring system and method, and the system comprises a mining area groundwater partition recognition module, a groundwater pollution risk assessment module, a groundwater monitoring point optimization module, a groundwater pollution path analysis module and a groundwater dynamic monitoring planning module. According to the invention, through data-driven zoning and risk assessment processes, fine and dynamic management is realized in underground water environment monitoring, functional zone zoning boundaries are accurately calibrated, understanding of an underground water flowing mode is enhanced, pollution source control is more targeted, diffusion risk intensity is assessed in combination with flow velocity and pollutant release intensity, and the risk assessment accuracy is improved. The risk management strategy is optimized, the pollution diffusion range is predicted and identified more efficiently, the emergency response accuracy is improved, monitoring point arrangement is optimized through risk data, reasonable monitoring resource allocation is ensured, the sampling task weight and the time interval are dynamically adjusted, and resource optimization and monitoring efficiency improvement are achieved.

The invention discloses an intelligent underground water quality supervision method and system. The method comprises heterogeneous sensing acquisition, water quality benchmark modeling, sewage traceability enhancement, water quality prediction and early warning and underground water quality supervision. The invention relates to the technical field of water quality supervision, in particular to an intelligent underground water quality supervision method and system, and adopts an underground water quality comprehensive supervision method combining water quality benchmark modeling, pollution traceability enhancement and dynamic threshold water quality prediction and early warning. The perception capability, the identification capability and the response capability of the underground water pollution event are effectively improved, and the supervision conversion from passive response to active pre-judgment is realized; carrying out water quality benchmark modeling by adopting an improved space-time diagram convolutional network method combined with a space-time dynamic baseline algorithm; pollution traceability enhancement is carried out by adopting an improved adversarial generative network method of virtual and real traceability modeling.

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 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 discloses a river pollution tracing method and system based on underground water quality pollution monitoring, and relates to the technical field of river pollution tracing. According to the river pollution tracing method based on underground water quality pollution monitoring, the real-time concentration value of each pollutant in underground water is obtained in real time and analyzed to obtain the underground water pollution real-time evaluation index; according to the method, a plurality of abnormal measurement points with abnormal concentration in a set area are identified, and the traceability position coordinate of each pollutant with abnormal concentration in underground water in a river is analyzed, so that the real-time evaluation index of underground water pollution can be continuously calculated by acquiring the pollutant concentration data of each measurement point in real time; and whether the pollutant concentration exceeds the preset range or not is judged in time, so that the defects of hysteresis and untimely data updating of traditional water quality monitoring are overcome, dynamic monitoring of the pollutant concentration can be realized, and quick response when the pollutant is abnormally increased is ensured.

The invention relates to the technical field of water pollution traceability, and discloses an underground water pollution traceability system based on simulation data, and the system comprises a data collection module which collects real-time data of an underground water monitoring well, soil sampling points and underground water monitoring equipment, and forms a multi-source heterogeneous database; the three-dimensional modeling module is used for constructing a layered geologic body three-dimensional model based on the drilling data, the geological section and the remote sensing image; and the numerical simulation module is used for solving an underground water seepage equation and a pollutant migration equation by adopting a finite difference method of GPU parallel acceleration on the basis of the constructed layered geologic body three-dimensional model. Multi-source monitoring data are accessed in real time through the data acquisition module, online dynamic calculation of an underground water flow field and pollutant migration is achieved in combination with the GPU accelerated numerical simulation module, and the efficiency is effectively improved compared with traditional offline analysis.

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 is applied to the technical field of water pollution treatment, and discloses a soil groundwater pollutant migration simulation system which comprises a data acquisition module, a model construction module, a boundary condition setting module, a model solving module and a result verification module. According to the soil groundwater pollutant migration simulation system, by integrating soil physical properties, groundwater geology conditions, pollutant characteristics and the like and applying a scientific model construction and numerical calculation method, the concentration distribution mode of pollutants at different time and space positions is accurately predicted, the trend and range of pollution diffusion are mastered in advance, and the migration simulation of the soil groundwater pollutants is realized. Accurate data support is provided for formulating targeted pollution prevention and control and treatment strategies, and in an industrial pollution site repair project, the expansion direction and speed of pollution plume can be determined according to a simulation result, so that the range and key area of the repair project are reasonably planned, excessive treatment or insufficient treatment is avoided, and the repair efficiency is improved. The treatment efficiency is improved; the treatment cost is reduced.

The invention provides an underground water pollution traceability method and system based on deep learning and multi-source data fusion, and the method employs multi-source data fusion to accurately describe pollution source features, builds a pollution source multi-source data set, builds a pollution source recognition model based on a CNN convolutional neural network and an LSTM long-short-term memory network, and achieves the traceability of underground water pollution. The multi-source data set is used for training, and the features and potential relationships of the multi-source data are fully mined, so that the traceability model can accurately identify the features of the main pollution source and contributions thereof, the limitation of single-dimensional data traceability and the difficulty of multi-source data fusion are overcome, and the accuracy and efficiency of groundwater pollution traceability are improved.

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 discloses a hydraulic control simulation-optimization method for underground water pollution in an in-situ leaching uranium mining final mining area. The method comprises the following steps: constructing a three-dimensional unstable underground water flow and pollution component reaction migration simulation model of an ore-bearing water layer by utilizing MODFLOW and PHT3D simulation software; determining a management objective function and constraint conditions of hydraulic control of the underground water pollution range of the in-situ leaching uranium mining final mining area, and establishing an objective function of a hydraulic control optimization management model; the underground water level and the pollutant concentration of each grid are used as state variables, the water pumping flow of each well is used as a decision variable, and the state variables are continuously updated through an ore-bearing water layer three-dimensional unstable underground water flow and pollution component reaction migration simulation model. And selecting an optimal solution of the objective function of the hydraulic control optimization management model by using a particle swarm optimization algorithm. According to the method, the hydraulic control condition of the pollution plume of the ore-bearing and water-bearing stratum in the final mining area can be predicted, potential problems can be found in advance, and corresponding measures are taken for adjustment.

The invention discloses an industrial park groundwater pollutant screening and identification method, which comprises the following steps: firstly, scoring the source strength, toxicity and path of pollutants through a comprehensive scoring method, and carrying out preliminary screening according to the scoring result to determine preliminarily concerned pollutants, thereby being beneficial to narrowing the screening range and reducing unnecessary evaluation work; the evaluation efficiency is improved. Meanwhile, the ITD index model constructed based on the three dimensions of source intensity, toxicity and path can more comprehensively consider the potential risk of the pollutants, and a scientific basis is provided for an evaluation result. The toxicity test result is introduced, so that the evaluation result is more accurate, and experimental data support is provided for the evaluation result. The method can provide scientific basis and technical support for underground water pollution prevention and control in industrial parks. According to the comprehensive evaluation result, corresponding risk prevention and control measures are provided for the optimal control pollutants in the list, the underground water pollution risk of the industrial park is reduced, and the environment and human health are protected.

The invention relates to the technical field of water pollution detection, in particular to a rapid traceability method and system for underground water pollution source tracking, and the method comprises the steps: constructing a preliminary prediction model of pollutant concentrations of different sampling points according to pollutant concentration sequences of samples of different sampling points; based on the water flow velocity sequence, analyzing the water flow velocity anomaly of each sampling point, and obtaining the weight correction necessity of each sampling point; according to the pollutant type number sequence, the accumulative variable quantity of the pollutant type number is analyzed, and the type constant quantity of each sampling point is obtained; and correcting the weight value of the preliminary prediction model according to the weight correction necessity and the type constant quantity in combination with the pollutant concentration sequence to obtain a corrected prediction model, predicting the pollutant concentrations of different areas of the water area to be traced, and identifying a pollution source. And the correction prediction model corrects a model prediction error caused by a confluence effect, so that the accuracy and efficiency of source tracing of the pollution source are improved.

The invention belongs to the technical field of underground water pollution source tracking, and particularly relates to an underground water pollution source analysis method based on multiple tracers and electronic equipment. The method comprises the following steps: setting a monitoring point; acquiring concentration information of various tracers in the underground water; drawing a plurality of tracer agent spatial distribution diagrams; determining an initial key pollution area and an initial migration diffusion area; simulating the historical pollution state of underground water according to the underground water fluid model; simulating a historical key pollution area and a historical migration diffusion area of underground water by combining the initial key pollution area and the initial migration diffusion area; and determining a pollution source and a migration and diffusion direction according to changes of the historical key pollution area and the historical migration and diffusion area. The underground water flow information is introduced, the determined pollution source position is accurate, a fluorescent tracer agent does not need to be put, and underground water is not affected.

The invention discloses a simulation-optimization method for a pollution site groundwater pumping-injection-treatment pollution remediation system based on a multiform evolution search normal form. The method comprises the following steps: constructing a groundwater flow model and a pollutant solute transport model; the method comprises the following steps: determining a management objective function and constraint conditions of hydraulic control of an underground water pollution range, establishing an underground water pollutant treatment model, optimizing underground water pumping and injection treatment of a pollution site by adopting BLMFO, solving the problem of interdependence between an upper-layer global target and a lower-layer local target through nested optimization, and constructing an auxiliary task by utilizing MFO; state variables are updated through the groundwater flow model and the pollutant solute transport model, a management objective function value of the groundwater pollutant treatment model is calculated, and whether constraint conditions are met or not is judged; meanwhile, decision variables are selected by optimizing the groundwater pollutant treatment model, and state variables are updated by returning to the groundwater flow model and the pollutant solute transport model.

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 belongs to the technical field of water pollution prevention and control, and particularly discloses a method for simulating and predicting underground water pollution of a karst area with multiple media. The method comprises the following steps: carrying out a water pumping experiment, geophysical exploration and a field tracing experiment, and determining the connectivity of a fault and a karst pipeline, the water flow velocity, the average water flow velocity of the pipeline, the connectivity of the pipeline and a branch structure; constructing a matrix three-dimensional unsteady-state groundwater flow equation, and determining the area and duration of a pollution source, a characteristic pollution factor and a leakage concentration; hydrogeological parameter calibration is carried out based on the groundwater unified measurement water level; taking the weighted variance of the monitored water level, the spring flow and the spring solute concentration as a calibration objective function; the fixed supply coefficient is converted into supply intensity, and the long observation hole water level fluctuation condition, spring flow and the concentration of pollution factors in spring water are predicted on the basis of unsteady flow simulation. The karst spring and water quality evolution can be accurately predicted, and a decision basis can be provided for protection and restoration of underground water resources in the karst area.

The invention relates to the technical field of data processing, in particular to a karst area mine groundwater pollution channel tracking method, which comprises the following steps of: acquiring groundwater flow data and pollutant concentration data of a plurality of monitoring points of a karst area mine; the water flow fluctuation degree of the monitoring point and the concentration trend change degree of various pollutants are obtained according to the underground water flow data and the pollutant concentration data, the overall pollutant concentration equilibrium proportion degree of the monitoring point is obtained according to the concentration difference between various pollutants and another matched pollutant, and the overall pollutant concentration equilibrium proportion degree of the monitoring point is calculated according to the water flow fluctuation degree. The characteristic distance between any two monitoring points can be obtained according to the concentration trend change degree of various pollutants in the current monitoring period and the previous monitoring period and the overall pollutant concentration equilibrium ratio degree, so that the monitoring points are clustered, the accuracy of the clustering result is improved, the tracking of the mine groundwater pollution channel is realized, and the monitoring efficiency is improved. And interference of actual mine operation activities on local monitoring points is avoided, so that the tracking accuracy of the pollution channel is enhanced.

The invention relates to the technical field of data processing, in particular to a chemical industry park groundwater pollution risk dynamic assessment method fusing multi-source heterogeneous data. The method comprises the steps that multi-source heterogeneous data of a chemical industry park is acquired and preprocessed, and preprocessed multi-source heterogeneous data is obtained; performing preliminary feature extraction on the preprocessed multi-source heterogeneous data, and performing fusion processing to obtain fused data; based on the fused data, constructing a bidirectional coupling groundwater pollution migration simulation model, calculating a groundwater flow rate and a pollutant concentration, and constructing pollutant three-dimensional concentration distribution; based on the three-dimensional concentration distribution of pollutants, a weighted heterogeneous graph is constructed, a pollution propagation path is identified, a path potential score is calculated, a pollution risk index is calculated, and the pollution risk is dynamically evaluated. The technical problems that a traditional groundwater pollution risk assessment method is not accurate enough in multi-source heterogeneous data processing, not comprehensive enough in analysis and poor in self-adaptability of a chemical industry park are solved.

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 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.

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 pollution tracing, in particular to an underground water pollution tracing method and system based on sewage pipeline data, and the method comprises the steps: obtaining the water flow and mineral dissolution content of a monitoring well; acquiring all suspected downstream monitoring wells of each monitoring well; analyzing the fluctuation similarity of the water flow and combining with the mineral dissolution content to obtain a plurality of monitoring wells contained in each underground river reach; the intersection condition of the underground river reach is analyzed to obtain a plurality of tide suspected communication points and a plurality of marked wells thereof; the high water flow date of each marked well of each tide suspected communication point is obtained; judging the independence of the trend of the mineral dissolution content to obtain a plurality of tidal well channels and communicated river reaches thereof; and connecting an underground river section for pollution tracing. The invention aims to solve the influence of unclear upstream and downstream of an underground river and well channels existing between different underground river reaches on traceability, and realizes accurate groundwater pollution traceability.

The invention relates to the field of groundwater pollution tracing methods, in particular to a method for rapidly tracing groundwater pollution in a chemical industrial park, and solves the problems of high cost and technical threshold, poor operability and long tracing time of groundwater pollution tracing in the prior art. The method comprises the following steps: S1, collecting basic data; s2, defining a monitoring area; s3, data matching is carried out; obtaining a preliminary judgment result according to a data matching result; s4, secondary judgment is carried out, and the park groundwater pollution source is determined. Data acquisition can be carried out through the existing underground water environment monitoring well in the park, the cost is low, and the operation is simple and convenient; performing data analysis and matching on enterprise basic data and environment monitoring data to obtain a suspected pollution source enterprise list of the park; on the basis, the park pollution source is further locked, and park underground water pollution traceability work is completed.

An intelligent early warning method for soil and groundwater pollution in an industrial gathering area belongs to the technical field of early warning of soil and groundwater pollution, and comprises the following steps: constructing an early warning index system for soil and groundwater pollution in the industrial gathering area and formulating a scoring rule; constructing an industrial accumulation area soil and groundwater pollution risk assessment model; constructing a pollutant migration prediction model; and carrying out early warning grade division by applying a density-based clustering algorithm. According to the method, a whole-process multi-level index system covering pollution generation, migration and action is constructed, factors such as enterprise emission behaviors, pollution characteristics, anti-seepage and hardening conditions and receptor sensitivity are systematically integrated, and panoramic quantitative characterization of industrial gathering area pollution is achieved. According to the method, the pollution risk index and the pollutant migration simulation prediction result are combined, the automatic division of the pollution early warning grade is realized by using the density clustering algorithm, a static division mode depending on a fixed threshold value is eliminated, and the scientificity and rationality of the early warning result are remarkably improved.

The invention relates to the technical field of agricultural environmental protection and groundwater pollution remediation, in particular to an agricultural non-point source groundwater pollution remediation technology screening system and method, and the system comprises a barrier technology screening module, a degradation technology screening module, a removal technology screening module and a cost accounting module; the method comprises the following steps: quantitatively evaluating the pollutant blocking capability of a blocking technology to farmland infiltration through a soil hydraulics equation, screening an aeration zone efficient degradation technology by utilizing a Fick law and a Monod kinetic model, and verifying the economic feasibility of an aquifer removal technology based on a shadow engineering method and a full life cycle cost model; the method comprises the following steps: determining optimal technologies of farmland infiltration, an aeration zone and an aquifer in sequence through each module, and generating a feasible scheme in combination with cost accounting. The problems that a traditional technology is poor in adaptability and high in cost in an agricultural scene are solved, and full-chain precise screening from a pollution source to a tail end and economic and feasible repairing technology combination are achieved.

The invention discloses a soil and groundwater pollution diffusion prediction method and system based on a time-space diagram neural network, and relates to the crossing field of environmental information modeling and artificial intelligence, and the prediction method comprises the following steps: S1, obtaining multi-source soil and groundwater monitoring data and external driving data; s2, generating a static hydraulic communication matrix and a dynamic convection dominant matrix, and constructing a multi-relation dynamic graph structure; s3, performing parallel processing on graph convolution operation of the static hydraulic connection matrix and the dynamic convection dominant adjacency matrix, capturing time dynamic characteristics, and obtaining a pollutant concentration prediction result; and S4, outputting structured prediction data and a visual product. By constructing a multi-relation dynamic graph structure fusing a hydrogeological physical mechanism and a dynamic flow field response, distortion of a pollution plume leading edge deduction trajectory caused by misjudgment of a spatial dependency relation can be avoided, so that the prediction precision of a non-uniform anisotropic pollution diffusion path is improved.