452 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 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 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 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 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 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 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.

The invention discloses an early warning grade evaluation method based on an urban pollution industrial site, relates to the technical field of industrial site early warning evaluation, and solves the technical problems of incomplete overall evaluation and lack of systematic analysis process and data processing correction caused by analysis of a single evaluation index. According to the method, pollution factor indexes are integrated in a three-dimensional mode through the pollutant standard exceeding multiple mean value, the specific pollutant toxicity coefficient and the pollution plume diffusion area proportion, the pollution intensity is reflected, toxicity hazards and spatial diffusion risks are considered, the soil pollution area is calculated through the Kriging interpolation method, the groundwater pollution plume area is predicted through the MODFLOW model, and the groundwater pollution plume area is predicted through the MODFLOW model. The overlapping area is processed through a maximum area method, repeated statistics is avoided, the accuracy of pollution range data is improved, different threshold values are set, standardized matching of comprehensive indexes and early warning levels is achieved, corresponding management and control measures are defined for all the early warning levels, abstract comprehensive indexes are converted into specific practical operation guidance, and hierarchical management and control can be conveniently carried out.

The invention relates to the technical field of underground water detection, in particular to an online monitoring method and device for underground water pollution. Establishing a quantization environment model of the underground water system based on the multi-source heterogeneous environment data of the target area; mapping the time sequence monitoring data of each monitoring point into a quantum state sequence in a high-dimensional Hilbert space to obtain environment observation input of each monitoring point; inputting the environment observation of each monitoring point into the quantization environment model, and generating quantum action modal data by using quantum gate operation; and integrating the monitored quantum action modal data of each target area, constructing a cross-regional groundwater pollution knowledge graph, and transmitting the knowledge graph to a preset terminal for display. According to the invention, comprehensive and visual decision support is provided for global pollution monitoring and treatment, efficient and accurate online monitoring and early warning are realized, and powerful technical support is provided for groundwater pollution prevention and control.

The invention discloses an underground water pollution dynamic monitoring and risk early warning system, and relates to the technical field of underground water pollution monitoring and early warning. Comprising a data monitoring module used for collecting pollution index data of underground water in real time and sending the collected data to a data transmission module; the data transmission module is used for transmitting the received data to the data processing module; the data processing module is used for preprocessing and analyzing the received data and sending the processed data to the risk assessment module; the risk assessment module is used for carrying out pollution risk assessment based on the processed data and sending an assessment result to the early warning module; and the early warning module is used for sending out corresponding early warning information according to the evaluation result. According to the invention, the dynamic and real-time monitoring of groundwater pollution is realized, the accuracy of data processing is improved, the timeliness of early warning is ensured, and the loss caused by groundwater pollution is reduced.

The invention discloses a water pollution treatment method which comprises the following steps: pretreating a polluted water body, and removing larger particle pollutants from the source; biological treatment, wherein organic pollutants and heavy metal pollutants are removed through the combined action of a biological composite microbial agent and an adsorbent; ecological restoration: through the configuration of aquatic plants and organisms, heavy metal pollution and the like are further removed, and the ecological environment is improved for a long time; underground water treatment: underground water pollution is prevented from entering the downstream through interception and adsorption of an underground water permeation wall, and a three-dimensional treatment effect is achieved; and circular treatment, wherein the treatment effect is further improved through a circular treatment method of reflux dilution. According to special geological and hydrological conditions of the karst region in Guizhou, efficient removal of heavy metal and agricultural non-point source pollutants is achieved through a multi-means synergistic effect, the method has the advantages of being high in adaptability, low in cost, environmentally friendly and the like, guidance is provided for water pollution treatment in similar regions, and the method has high practical application value.

The invention discloses piezoelectric catalysis-Fenton self-coupling staged underground water treatment equipment, and relates to the technical field of underground water pollution abatement, the piezoelectric catalysis-Fenton self-coupling staged underground water treatment equipment comprises a reactor main body, a piezoelectric-aeration water treatment module and a PVDF-HFP piezoelectric film array, the piezoelectric-aeration water treatment module is fixedly arranged in a piezoelectric-aeration catalysis reaction zone, and the PVDF-HFP piezoelectric film array is fixedly arranged in the reactor main body; the PVDF-HFP piezoelectric film array is fixedly arranged in the Fenton-piezoelectric catalysis enhanced reaction zone; the piezoelectric-aeration water treatment module comprises a micro-nano bubble generator, a micro-nano diaphragm and a piezoelectric composite filler, a filler containing cavity is formed between the micro-nano bubble generator and the micro-nano diaphragm, and the piezoelectric composite filler is filled in the filler containing cavity; the micro-nano bubble generator is connected with the dissolved air pump through a first air inlet pipe; and a Fenton filler is loaded on the surface of the PVDF-HFP piezoelectric film array. According to the invention, high-efficiency and low-consumption remediation and treatment of the water body can be realized in an underground water environment.

The invention discloses a pollution risk assessment method, a pollution risk assessment device, pollution risk assessment equipment and a computer readable storage medium for an underground water environment, and the method can accurately simulate the migration and diffusion of pollutants in underground water through a constructed underground water pollutant migration model. And calculating exposure by combining sensitive receptor distribution, calculating risk indexes and probabilities according to toxicological parameters, and finally determining risk levels. Through application of the series of models, the accuracy and scientificity of risk assessment are greatly improved, a reliable basis is provided for groundwater pollution prevention, control and treatment, and potential environmental risks are effectively reduced.

The invention discloses an intelligent agricultural greenhouse for modern agriculture, and the greenhouse comprises a greenhouse frame which is internally provided with an intelligent inspection mechanism. The mechanism is mainly composed of a pair of sliding rails, an electric sliding block capable of moving on the sliding rails, a first transverse plate connected with the electric sliding block and a loader installed at the lower end of the first transverse plate. And a visual detection mechanism and a targeted spraying mechanism are arranged on the loader. The visual detection mechanism is responsible for collecting image information of crops in the greenhouse, and the targeted spraying mechanism is used for executing precise pesticide application work. The device has the remarkable beneficial effects that precise positioning and local pesticide application can be achieved, and the problems of resource waste and environmental pollution caused by a traditional wide pesticide spraying method are fundamentally avoided. The system can effectively protect the natural control ability of beneficial organisms and ecological systems and reduce the risk of soil hardening and underground water pollution, thereby being beneficial to improving the soil productivity and environmental bearing capacity and finally ensuring the safety and quality of agricultural products.

The invention relates to the technical field of data processing, in particular to a chemical industry park groundwater pollution diffusion prediction method based on artificial intelligence. The method comprises the following steps: acquiring pollutant concentration information data and geological exploration parameter data in underground water in a chemical industry park, and preprocessing to obtain preprocessed data; based on the preprocessed data, a self-shaping function embedding mechanism is introduced, a pollution action function is constructed, and a pollution potential energy field embedding tensor is generated; introducing a geological disturbance function generator, constructing a spatial disturbance tensor, and generating a spatial correction tensor of pollution transmission in combination with the pollution potential energy field embedded tensor; and based on the pollution potential energy field embedded tensor and the pollution transmission space correction tensor, pollution propagation modeling is carried out, and underground water pollution diffusion prediction is realized. The technical problem that the groundwater pollution diffusion prediction result is seriously deviated from the actual diffusion track due to the fact that a traditional groundwater pollution diffusion prediction method is inaccurate and incomplete in data processing and analysis is solved.

The invention relates to an organic combined polluted underground water in-situ remediation method based on a micro-nano iron-based material. The method comprises the following steps: acquiring underground water pollution information; establishing a composite reaction zone at a preset position, and constructing a reduction-oxidation chain reaction system; and operating the composite reaction zone, collecting monitoring data, and optimizing the composite reaction zone until the composite pollution is degraded and removed to a preset value. Through series reaction of powerful reduction of the micro-nano iron-based material and advanced oxidation of the iron-based activated persulfate, the performance of the micro-nano iron-based material serving as a strong reduction material and an active agent is fully played, pollutants such as halogenated hydrocarbon in underground water are sequentially subjected to reduction degradation, pollutants such as benzene series and volatile phenol are sequentially subjected to oxidative degradation, and the pollution to the underground water is reduced. Effective management and control of underground water combined pollution of medical and chemical parks and enterprises are realized; a monitoring well is configured based on a composite reaction zone, and remediation materials are discontinuously added in combination with management and control conditions, or other management and control materials are flexibly selected, so that long-term management and control of groundwater pollution risks are realized.

The invention relates to the technical field of soil and groundwater pollution remediation, in particular to a polluted groundwater source controlling and breaking system suitable for limited space of an industrial accumulation area, which comprises a main well, a gas stripping circulating unit and a groundwater circulating unit. A blocking device composed of a packing rubber structure and a driving device is arranged in the main well, the packing rubber structure is driven by the driving device to move and intermittently inject air to expand, and an air flow channel which is dynamically opened and closed is formed between the inner wall of the main well and the unsaturated area. The vacuum pump device builds negative pressure on the upper portion of the main well, so that purified clean gas enters an unsaturated area in an intermittent pulse mode through the peripheral injection well, and soil gas is induced to flow in an oscillating mode under cooperation of the dynamic gas flow channel. Groundwater extracted by the centrifugal pump is purified by the gas stripping area and the underground activated carbon filtering device and then is discharged into the top of the unsaturated area through the drainage device in an intermittent wave mode, the system is suitable for pollution treatment in the limited space of the industrial accumulation area, and targeted source control and long-acting reduction are achieved.

The invention discloses a sea-land interaction zone underground water pollution source tracing method based on multi-pollutant fingerprints, and the method comprises the steps: constructing a fingerprint feature library of eight key pollutants including cadmium, arsenic, nitrate nitrogen, ammonium nitrogen, phosphate, total petroleum hydrocarbon, sulfamethoxazole, pH value and the like; statistical characteristic models of four pollution sources of industrial emission, agricultural non-point sources, oil exploitation and aquaculture are established, Z-Score standardization and a similarity calculation method based on a standard normal distribution probability density function are adopted, comprehensive similarity evaluation is performed in combination with a risk weight distribution mechanism, a similarity threshold value of 0.7 is set to perform pollution source identification and sorting, and the pollution sources are identified and sorted according to the similarity threshold value. And correction is performed by considering environmental factors such as tide, season and geology of a sea-land interaction zone. The method can quickly and accurately recognize the groundwater pollution source of the sea-land interaction zone, the traceability accuracy rate reaches 80% or above, and scientific and technical support is provided for prevention and control of groundwater pollution of the sea-land interaction zone and formulation of an environmental protection policy.

The invention discloses a medium and long term remediation method for plant groundwater pollution, and relates to the technical field of water treatment.The medium and long term remediation method comprises the steps that S1, pollutant concentration data of plant soil and groundwater is obtained, and plant pollution areas are divided; s2, determining a remediation method based on the polluted area of the factory; s3, establishing an underground water migration-reaction coupling model for simulating pollutant diffusion and restoration; s4, based on the groundwater migration-reaction coupling model, simulating to obtain a predicted restoration period and predicted restoration parameters, and then adopting a restoration method and the predicted restoration parameters to restore the groundwater pollution of the factory area; according to the method, a systematic and scientific factory groundwater pollution remediation scheme is provided, the diffusion and remediation process of pollutants can be simulated by establishing the groundwater migration-reaction coupling model, the remediation cost can be reduced as much as possible while the environment remediation effect is guaranteed, and the balance of environmental benefits and economic benefits is achieved.

The invention belongs to the field of soil environment pollution simulation and prediction, and provides a prediction method based on a two-point chemical unbalanced model, which is used for quantitatively evaluating the effect of regulating and controlling the migration behavior of p-nitrophenol in acid red soil by straw stalk biochar. According to the method, a biochar-red soil composite medium system is constructed, a soil column leaching experiment is carried out to obtain penetration curve data, a two-point chemical unbalance model in CXTFIT software is utilized to carry out parameter inversion, and key parameters such as a retardation factor, a two-region distribution coefficient, a mass transfer coefficient and a liquid phase degradation coefficient are accurately identified. Model verification shows that the goodness of fit is high, and a parameter change rule reveals the inherent mechanism of enhancing the pollutant retention capacity, changing the proportion of fast and slow adsorption sites and influencing mass transfer kinetics by the biochar. Based on the verified model, the long-term migration behavior and pollution risk of p-nitrophenol under different environmental conditions can be simulated, and a scientific basis is provided for groundwater pollution control and remediation strategy optimization.