146 results about "Groundwater resources" patented technology

The invention provides an underground water dynamic evolution prediction method, and belongs to the technical field of underground water prediction based on deep learning. Hydrological parameters and geographic position data of monitoring points are collected, and a regional hydrogeological input tensor is constructed; then establishing an initial finite element model to carry out space extrapolation and flow field completion on underground water level distribution; based on an initial finite element model structure, designing a global optimization algorithm based on target decomposition, carrying out real-time structure optimization on the finite element model, then simulating underground water evolution of a non-monitoring area through a finite element numerical solution, and generating multi-node physical consistency hydrological time series data after resolution is improved; and inputting the generated hydrological time series data into a designed perceptual water level prediction model, and outputting underground water level prediction results at multiple moments and multiple positions in the future and corresponding underground water level thermodynamic diagrams. According to the method, more accurate, continuous and interpretable high-precision prediction of the underground water system is realized, and reliable support is provided for scientific management of underground water resources.

The invention discloses a three-dimensional visual management system and method for groundwater resources, and relates to the field of groundwater resource management and pollution control, and the system comprises a groundwater data obtaining module which is used for obtaining groundwater dynamic monitoring data of a target area in real time; the underground water environment digital twinborn model construction module is used for constructing an underground water environment digital twinborn model based on the underground water dynamic monitoring data; the underground water change and pollution control simulation module is used for carrying out numerical simulation on underground water resource and pollutant migration based on the underground water environment digital twinborn model, carrying out pollution control area division and formulating a corresponding underground water remediation scheme; and the decision support and knowledge management module is used for integrating groundwater dynamic monitoring data, the groundwater environment digital twinborn model, the divided pollution control area and the corresponding groundwater remediation scheme, and realizing data storage, three-dimensional display, data evaluation and user interaction. According to the invention, efficient management and pollution control of underground water resources can be realized.

The invention discloses a multivariable underground water level time sequence prediction method and device, equipment and a medium, and relates to the technical field of artificial intelligence. Performing feature variable contribution proportion calculation, feature screening and normalization processing on the processed data based on a random forest regression model by using an average impurity reduction method to obtain target data; constructing a prediction model based on a convolutional neural network and a long-short term memory network, and performing structure setting, cross validation, parameter setting and model training on the prediction model to obtain a target prediction model; the method comprises the following steps: inputting target data into a target prediction model to obtain a predicted value, generating an evaluation index based on the predicted value and an actual measured value, optimizing the target prediction model by using the evaluation index, improving the applicability, generalization ability and training speed of the model, optimizing the convergence of the model, and improving the accuracy and stability of multivariable groundwater level time sequence prediction. And the sustainable utilization efficiency of underground water resources is improved.

The invention discloses an underground water exploitable quantity evaluation method and system based on coupling of a physical mechanism and a neural network, and relates to the technical field of water resource management, meteorological data, surface water hydrological monitoring data, geological survey data, underground water resource development and utilization data and hydrogeological parameter data are integrated and preprocessed, and a basic data set is obtained; a three-dimensional geological model of a heterogeneous structure is constructed by utilizing a digital twin physical engine and combining drilling geological data. By introducing a digital twin technology and a numerical model, the underground water flowing process can be simulated more accurately, a digital twin physical engine is utilized to construct a heterogeneous aquifer digital model, a dynamic interaction process of surface water and underground water is embedded, and the model is enhanced through a graph neural network and a physical information neural network, so that the underground water flowing process is simulated more accurately. Errors caused by hypothesis of aquifer homogeneity, neglecting of surface water-underground water coupling process and the like of a traditional model are effectively reduced, and the accuracy of underground water exploitable quantity evaluation is improved.

The invention discloses a water quality detection system and detection method for groundwater resource assessment, and relates to the technical field of environmental monitoring, the method comprises the following steps: obtaining multi-source data of groundwater in a target area through a sensor network, and combining environmental parameters to carry out data fusion to generate a comprehensive result; performing water quality scoring based on the fused data, constructing a water quality spatial distribution diagram, and predicting a water quality change trend; and determining a pollution source according to trend data tracing, formulating a pollution control scheme in combination with multi-source data, and generating a treatment suggestion. The technical problem of insufficient water quality detection precision in existing groundwater resource evaluation is solved, and the technical effect of performing high-precision detection and comprehensive evaluation on groundwater quality data is achieved.

The invention relates to the technical field of environment monitoring, in particular to an underground water monitoring and early warning method and system based on multi-source data fusion, and the method comprises the following steps: obtaining water quality, flow velocity, temperature and pH value data, adjusting the collection frequency, verifying the state of a sensor, forming a water quality and geologic feature data set, analyzing rainfall, air temperature, permeability and water flow dynamic state, and obtaining a water quality and geologic feature data set. And generating a seepage trend, identifying a pollutant diffusion path, range and main path, evaluating a diffusion rate and influence, and generating a pollution diffusion early warning level in combination with permeability and risk standards. According to the invention, through fusion analysis of multi-source data, determination of the correlation between an underground water flowing mode and water quality change, timely capturing of the influence of meteorological change on underground water, accurate evaluation of pollutant diffusion path, rate and influence range, improvement of timeliness and accuracy of pollution early warning, and improvement of monitoring response speed through automatic data processing. And timely and accurate decision support is provided for groundwater resource management and pollution control.

The invention relates to the technical field of underground water monitoring, in particular to an underground water dynamic monitoring multi-element early warning system based on data analysis, which comprises a data fusion acquisition module, a dynamic geological modeling module, a deep learning prediction module, a multi-level intelligent early warning module and an intelligent response decision module. Wherein the data fusion acquisition module is used for acquiring multi-dimensional data; the dynamic geologic modeling module is used for constructing a three-dimensional dynamic model of an underground water aquifer; the deep learning prediction module predicts the future change trend of the underground water level and the water quality; the multilevel intelligent early warning module is used for establishing a multilevel early warning mechanism; and the intelligent response decision module formulates corresponding underground water management and emergency response strategies. According to the invention, through real-time integration of multi-source data and combination of intelligent early warning and automatic management, the accuracy and response speed of underground water monitoring are significantly improved, and sustainable management and protection of underground water resources are effectively supported.

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 discloses a novel simulation method for representing underground water level space-time evolution, and belongs to the technical field of computer machine learning. A novel simulation method for representing underground water level space-time evolution comprises the following steps: acquiring long-time sequence underground water level data based on an underground water long-term observation hole; according to the underground water level information, multiple hydrogeological parameter information is superposed, a two-dimensional underground water seepage equation is used as a physical mechanism, a neural network model with the physical mechanism in a region is constructed, and then time and space evolution of the underground water level in the region is simulated; reasonable use of groundwater resources can be enhanced, scientific and effective supervision is implemented, and a scientific basis is provided for protecting the safety of regional groundwater and promoting sustainable development of the groundwater resources.

The invention discloses a gravity satellite groundwater storage variable vertical signal separation method based on a physical model, and the method comprises the steps: S1, building a physical response model of ground surface deformation and gravity change and groundwater storage variables, and enabling the physical response model to comprise a ground surface deformation response model and a gravity change response model; the method specifically comprises the following steps: step S2, constructing a gravity satellite and InSAR data joint inversion framework, and establishing an observation equation set; s3, regularization constraint conditions are introduced, and a weighted least square method is adopted for solving; and S4, carrying out groundwater reserve vertical separation and verification based on a mass conservation principle. The method overcomes the defect that an existing method depends on dense well observation data, fine monitoring of groundwater storage variables is achieved through physical model constraints, and the method can be widely applied to regional groundwater resource monitoring and management.

The invention belongs to the field of environmental protection, and discloses an underground water resource comprehensive evaluation method and system based on big data, electronic equipment and a storage medium. The method comprises the following steps: collecting and processing underground water resource data of a to-be-evaluated region to obtain processed data; based on the processed data, extracting long-term trend information related to the groundwater resources; constructing an underground water system model based on the long-term trend information; and completing groundwater resource assessment based on the groundwater system model. According to the method, the multi-source data is collected and processed, the long-term trend information is extracted, the groundwater system model is constructed, and denoising processing is performed, so that high-precision evaluation of groundwater resources is realized. According to the method, the problems of insufficient data coverage, low time resolution and low model precision in a traditional evaluation method can be effectively solved, and the reliability and the accuracy of an evaluation result are improved.

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

The invention relates to the technical field of resource evaluation, in particular to a precise evaluation system and method for the water resource quantity of an inland river basin, and the method comprises the following steps: laying a multi-modal sensor network in the inland river basin, collecting the hydrological characteristic data of the inland river and surrounding wetlands, extracting the inland river-wetland recessive water exchange characteristic indexes, and calculating the water resource quantity of the inland river basin; comprising the wetland groundwater supply amount, the inland river boundary seepage rate and the seasonal water exchange amplitude; based on the inland river-wetland recessive moisture exchange characteristic indexes, establishing an inland river-wetland recessive moisture exchange dynamic model; and embedding the inland river-wetland recessive water exchange dynamic model into an inland river basin water circulation system, and comprehensively calculating the surface water resource quantity and the underground water resource quantity in the basin. According to the method, the wetland consumption part is removed through the recessive moisture exchange between the wetland and the inland river, so that the water resource quantity calculation is more accurate.

The present application relates to the technical field of resource assessment, and particularly relates to a system and method for accurately assessing water resource quantity in an inland river basin, comprising the following steps: arranging a multi-modal sensor network in the inland river basin, collecting hydrological characteristic data of the inland river and surrounding wetlands, extracting implicit water exchange characteristic indexes between the inland river and the wetlands, including wetland groundwater recharge, inland river boundary seepage rate and seasonal water exchange amplitude; based on the implicit water exchange characteristic indexes between the inland river and the wetlands, establishing an inland river-wetland implicit water exchange dynamic model; embedding the inland river-wetland implicit water exchange dynamic model into the water cycle system of the inland river basin, and comprehensively calculating the surface water resource quantity and the groundwater resource quantity in the basin. Through the implicit water exchange between the wetlands and the inland river, the present application eliminates the wetland consumption part, so that the water resource quantity calculation is more accurate.

The invention relates to the field of groundwater resource management and protection, and discloses an AI intelligent groundwater level dynamic prediction system based on multi-source data fusion, which comprises a data acquisition module used for acquiring multi-source data to break through the limitation of a single data source and cover various factors influencing the change of the groundwater level; and the data fusion module adopts a multi-criterion decision analysis method and a multi-agent decision mechanism, analyzes the influence weight of each factor on the underground water level under different scales through weighted linear combination, and determines a decisive factor of a specific area. Multi-source data of meteorology, hydrogeology, human activities, building construction and the like are integrated through the data acquisition module, the influence weights of different factors on the underground water level can be comprehensively quantified in combination with a multi-criterion decision analysis method and a multi-agent decision mechanism of the data fusion module, the limitation of a traditional single data source is changed, and the underground water level can be accurately measured. Driving factors of underground water level changes are comprehensively captured, and a foundation is laid for accurate prediction.

The invention discloses a near-loose aquifer water-preserved coal mining method. The method comprises the steps that S1, the position of a working face and coordinates of a ground area are determined; s2, determining overlying strata structure characteristics of the mining working face and the positions of all aquifers through hydrogeological exploration; s3, the height H1 of the working face mining water flowing fractured zone is calculated; s4, the thickness delta H needing water pumping and draining treatment is determined; s5, ground drainage drill holes are arranged, and water is pumped out of a bottom water-bearing stratum of the S6, ground recharge well arrangement and middle aquifer recharge are conducted, and the double functions of protecting water resources of the loose aquifer and liberating coal resources near the loose aquifer are achieved; underground water resources are prevented from being damaged, and water resources are effectively protected and reasonably utilized.

The invention discloses an irrigation area groundwater resource scheduling method and device. The method comprises the following steps: acquiring irrigation demand data of an irrigation demand side, and determining a first benefit demand of the irrigation demand side according to the irrigation demand data; obtaining water resource scheduling data of the water conservancy management party, and determining a second benefit demand of the water conservancy management party according to the water resource scheduling data; obtaining water resource sustainable index data of the environmental protection management party, and determining a third benefit demand of the environmental protection management party according to the water resource sustainable index data; constructing a game model according to the first benefit demand, the second benefit demand and the third benefit demand, and solving the game model to obtain a target water resource scheduling strategy which minimizes the overall benefit loss of the irrigation demand side, the water conservancy management side and the environmental protection management side; and scheduling the water resources according to the target water resource scheduling strategy. The technical problem that local water-soil balance is easily damaged due to the fact that only irrigation requirements are considered in related irrigation area water resource scheduling schemes is solved.

The invention relates to an underground water level early warning method based on pore water pressure, and belongs to the technical field of computer deep learning. According to the method, long-time-sequence layered underground water level data and layered pore water pressure data are obtained based on a ground subsidence monitoring station; according to the principles of fluid statics and groundwater dynamics, the measured value of the pore water pressure is converted into the water level elevation. On the basis, information such as various hydrogeological parameters and source and sink items of a region is integrated, an underground water kinetic equation is used as a physical constraint, an LSTM-PINNs model with a physical mechanism is constructed, and underground water level early warning based on pore water pressure is achieved. Compared with a traditional numerical model, the method can more accurately capture single-point layered groundwater dynamic characteristics, has strong data missing complementation capability and long-time scale prediction capability, and meanwhile has the advantages of being easy to implement, efficient in operation and high in expansibility; the method can be widely applied to the fields of underground water resource management, environmental protection, geological disaster prevention and control and the like.

The invention relates to the technical field of intelligent early warning, in particular to a desert vegetation-underground water intelligent monitoring and early warning method based on artificial intelligence. The method comprises the following steps: obtaining a vegetation-groundwater multi-source monitoring interface corresponding to a target desert area, and carrying out vegetation growth and groundwater multi-source data acquisition and preprocessing to generate desert vegetation-groundwater standardized monitoring data; vegetation-groundwater ecological correlation characterization analysis processing is carried out through the desert vegetation-groundwater standardized monitoring data, desert ecological coupling analysis is carried out at the same time, and desert vegetation-groundwater ecological coupling relation data is generated; based on the desert vegetation-groundwater ecological coupling relation data, desert ecological vulnerable area identification analysis is carried out, an artificial intelligence coupling model is constructed to carry out ecological evolution trend deduction and early warning analysis, and desert vegetation-groundwater ecological early warning data are generated. According to the invention, cooperative monitoring and early warning of the vegetation growth state and underground water resources in the desert area can be realized.

The invention relates to the technical field of geological survey, and discloses a groundwater environment monitoring and early warning method, which comprises the following steps of: coupling a real-time early warning module and a prediction early warning module, and constructing a groundwater environment monitoring and early warning model; according to the national standard, the underground water quality current situation and the real-time and prediction early warning result, an early warning level is delimited, and different colors are given to represent color block warning levels; according to a simulation result, judging an early warning line of the underground water specific pollutants, and if a relatively high early warning level is displayed, carrying out pollutant inversion; possible pollutants speculated by the pollutant inversion module are identified; an early warning decision is made for possible pollutant types and enterprise types; and after the sudden pollution event is effectively disposed, early warning feedback is timely carried out. According to the groundwater environment monitoring and early warning method, the groundwater quality real-time early warning grade and the distribution range of pollutants in the groundwater in different time periods in the future are determined, and a scientific basis is provided for reasonably developing and utilizing groundwater resources.

The invention discloses a method for estimating the burial depth distribution of regional underground water based on Bayesian deep learning, and the method comprises the steps: employing discrete observation well position data, and combining the multi-source data, such as rainfall, evapotranspiration, temperature, gradient, distance to a nearest surface water body, soil type, land utilization type, and underground water reserve, as input factors; and establishing a nonlinear mapping relation between the underground water burial depth and the input factors through a Bayesian deep learning model. According to the method, the model is trained and verified by using the measured data at the observation points, and then the regional groundwater burial depth distribution is estimated based on the input factor data of the research area, so that the problem of insufficient coverage of a traditional groundwater monitoring network can be effectively solved, and the regional groundwater burial depth distribution characteristics can be described with relatively high spatial resolution; and scientific support is provided for sustainable utilization and ecological protection of regional underground water resources. The method has universality and is suitable for underground water burial depth prediction in different areas and under various data conditions.

The invention relates to a sample collection auxiliary device for groundwater resource investigation, which belongs to the technical field of groundwater sample collection, is configured and connected to the bottom of a sampler, and comprises a tank body vertically arranged at the bottom of the sampler, and a conical balancing weight arranged right below the bottom of the tank body, the plurality of impact columns vertically penetrate through the bottom of the tank body in a surrounding manner at equal intervals by taking the center line of the tank body as the center, the connecting plate is horizontally arranged in the tank body, the lower side of the connecting plate is fixedly connected with the tops of the impact columns, and the linear displacement mechanism is arranged on the tank body. The linear displacement mechanism is used for driving the impact column to impact the top of the conical balancing weight from top to bottom, so that the conical balancing weight obtains larger potential energy, a rope between the sampler and a wellhead is straightened in an auxiliary manner, and a distance mark on the rope conforms to the actual depth of the sampler; the specific depth of the monitoring sampling well is accurately sampled, so that a sample of a specific layer of underground water is obtained.

The invention discloses an intelligent territorial space planning system and method based on space-time big data, particularly relates to the technical field of space planning, and can timely discover the problem of excessive utilization possibly occurring in water resource exploitation by analyzing and monitoring the change speed of underground water resources. Therefore, unsustainable use of water resources and damage to the ecological environment are prevented. Secondly, by evaluating the water utilization efficiency of the land, the opportunity of improving agricultural and industrial water utilization methods can be identified, in addition, by comprehensively evaluating the water resource dependence degree and supply and demand fluctuation of the region, the dynamic change of the water resource can be better understood, and a scientific basis is provided for implementing an effective water resource management strategy and space planning. Finally, the method not only enhances the sustainable management capability of regional water resources, but also helps to guarantee the stable development of social and economic activities, improve the living quality of residents, ensure the long-term safety and ecological balance of the water resources, and support the realization of the sustainable development goal.

The invention discloses a coal-uranium collaborative mining circulation supply mining system and an application method, and particularly relates to the technical field of coal-uranium mining and a geological institution.The geological institution comprises a surface layer, a uranium layer, a coal seam and underground runoff, the surface layer is located above the uranium layer, the uranium layer is located above the coal seam, and the underground runoff is located above the coal seam. The underground runoff is located between the surface layer and the uranium layer; and the ground mining mechanism comprises an injection well, an extraction well, a leaching solution preparation tank, a uranium comprehensive treatment bin, a liquid injection pump, a liquid extraction pump, a liquid injection pipe and a liquid extraction pipe. According to the method, partition isolation and staged collaborative proceeding of uranium mine in-situ leaching mining and coal mining are achieved by planning the barrier infiltration reduction mechanism, the overall recovery efficiency of uranium and coal resources is improved, the pollution risk of uranium-containing leachate discharge to the environment is reduced, underground water resources are fully recycled, and the method has the advantages of being environmentally friendly, efficient and safe.

The embodiment of the invention discloses a water resource quality detection method and device applied to a water diversion project and electronic equipment. A specific implementation mode of the method comprises the following steps: performing water quality detection on a water area where a water diversion project is located to obtain an earth surface water quality data set and an underground water quality data set; constructing an earth surface data structure network according to a pre-constructed water area simulation model and an earth surface water quality data set; constructing an underground data structure network; performing water pollution detection on the water area to generate an earth surface water quality detection result set and an underground water quality detection result set; performing correlation analysis on the surface water resources and the underground water resources of the water area to generate water pollution correlation characteristics; determining a surface water pollution area and an underground water pollution area of the water area; and determining the surface water quality detection result set, the underground water quality detection result set, the surface water pollution area, the underground water pollution area and the water pollution correlation characteristics as water resource quality detection results. According to the embodiment, the accuracy of the water area overall quality detection result can be improved.

The invention relates to the technical field of water resource assessment, and discloses a regional water resource assessment system based on hydrological survey data, which collects the hydrological survey data in real time through a sensor, builds a convolutional neural network model based on a TensorFlow framework, and performs feature extraction on the hydrological survey data to obtain hydrological survey feature data; obtaining evaluation indexes including the average precipitation of many years, the surface water resource quantity, the underground water resource quantity, the total water resource quantity, the water quality standard reaching rate, the water resource development and utilization rate and the ecological water demand satisfaction rate; a penalty parameter and a kernel function parameter of a support vector machine are optimized by adopting a particle swarm optimization algorithm based on hydrological survey feature data, and a water resource evaluation model is constructed; inputting the real-time data into a water resource evaluation model, performing comprehensive evaluation on the water resource condition of the region based on evaluation indexes, and outputting each current water resource evaluation index value; the regional water resource is evaluated from multiple dimensions, and the regional water resource condition can be comprehensively reflected.

The invention discloses an underground water long-term correlation analysis method based on a geostatistics and fractal theory combined model, and the method comprises the steps: obtaining the initial underground water long-sequence burial depth monitoring data of a research region, and carrying out the processing of the underground water long-sequence burial depth monitoring data based on a space-time Kriging interpolation method, and obtaining the average burial depth data of underground water; and constructing a geostatistics and fractal theory combined model, inputting the initial groundwater long sequence burial depth monitoring data and the groundwater average burial depth data into the geostatistics and fractal theory combined model for processing to obtain an output result, and analyzing the long-term correlation of the groundwater burial depth of the research area through the output result. According to the method, a more accurate and reliable prediction result is provided, and a more scientific basis is provided for groundwater resource management and planning.

The invention provides an underground water resource remediation device, and belongs to the technical field of underground water treatment. According to the groundwater resource restoration device, the feeding channel between the floater and the drill rod enables restoration feed to enter the space below the floater, and meanwhile the space below the floater can contain groundwater entering the inner cavity of the drill rod through the flowing channel after the drill bit enters a groundwater layer; compared with an existing groundwater resource restoration device in which the groundwater in a flowing state is mixed with the restoration feed, the groundwater resource restoration device has the advantages that the groundwater resource restoration device is directly arranged near a groundwater layer, the restoration feed is mixed into the groundwater, and the groundwater resource restoration effect is improved. On one hand, along with the increase of the water quantity of underground water, the feeding efficiency of repairing feeding is improved; on the other hand, the feeding mode is changed into one-time feeding instead of successive feeding adopted by existing underground water remediation equipment, so that the mixing quality of remediation feeding is higher.

The present invention relates to the technical field of slope rainwater collection, and discloses a slope rainwater collection and irrigation system for landscaping projects, comprising a water collection end, a water storage tank, and an irrigation end. The water collection end comprises a water inlet assembly installed on the slope, the water inlet assembly being provided with a sediment filter, and a plurality of water inlet assemblies being connected to the water storage tank via a drainage channel. The irrigation end comprises a water pump, which is connected to the water storage tank via a water inlet pipe. A water spray pipe is connected to the water outlet of the water pump, the water spray pipe extends out of the slope, the water spray pipe is located at the upper end of the slope, and a water spray head is installed at the top of the water spray pipe. Rainwater in the present invention is an important source of water resources for hillside slopes and can replenish soil moisture and groundwater resources. By collecting rainwater left on the hillside during the rainy season, the collected rainwater is used to irrigate vegetation on the hillside during the dry season, thereby ensuring that the vegetation on the hillside can obtain sufficient water during the dry season to ensure growth, while reducing the use of municipal water supply or groundwater.

The present invention belongs to the technical field of hydrogeological evaluation, and specifically discloses a method and system for evaluating groundwater vulnerability based on a hydrogeological model. The method includes obtaining groundwater vulnerability evaluation parameters for the study area, including aquifer parameters, groundwater flow parameters, and pollutant characteristic parameters; constructing a three-dimensional anisotropic hydrogeological model based on the groundwater flow equation and the pollutant transport equation; calculating characteristic indicators of groundwater vulnerability, including pollutant arrival time index, pollutant concentration attenuation index, and system recovery ability index; constructing a kinetic coupling groundwater vulnerability index, calculating the time-varying contribution coefficients and non-linear coupling indices of each indicator and determining the dynamic threshold, so as to obtain a quantitative evaluation result of the groundwater vulnerability in the study area; this method improves the scientificity and accuracy of groundwater vulnerability evaluation and provides decision-making support for the protection and management of groundwater resources.