134 results about "Point source pollution" patented technology

The invention discloses a non-point source pollution emergency bypass decision control method, particularly relates to the technical field of automation and process control, and aims to solve the problems that existing scheduling cannot align multi-source measurement and evaluate credibility in minutes under a unified time base, and is lack of risk measurement integrated with a tide level phase and a moisture regain path and same-layer gating. The bypass rhythm is easy to misjudge, and the oscillation is difficult to audit. A minute-level risk density is constructed through multi-source alignment and credibility grading under a unified time reference, injected tide level phases and moisture regaining paths, bypass rhythms are constrained by same-layer gating and tide windows, and beam search, boundary arbitration and fixed window closed-loop correction are matched, so that the risk density is improved. Therefore, under the superposition of rainstorm and tide, decision making and execution are stably limited in a non-backflow red line, bearing and equipment limit, misjudgment and oscillation are remarkably reduced, the problems of unavailability and difficult auditing caused by multi-source asynchronization and moisture regain coupling are solved, intelligent decision support is provided for non-point source pollution treatment, and it is ensured that the treatment technology is accurate and efficient.

The invention discloses a multi-drive process multi-factor agricultural non-point source pollution prediction method based on coupling meteorological numerical forecasting. The method comprises the following steps: firstly, introducing numerical weather forecast data, and constructing a high-precision weather driving field with kilometer-level space and hour-level time resolution by combining WRF dynamic downscaling, DEM terrain correction and conservation resampling; secondly, establishing a multi-drive process coupling model system which comprises a meteorological drive layer, a hydrological response layer, a pollutant migration layer and a crop feedback layer and is used for simulating runoff production, sediment erosion, nitrogen and phosphorus migration and transformation and crop transpiration and root nutrient absorption processes; thirdly, performing precision verification on a simulation result by using observation data, and identifying key meteorological and hydrological factors through an error transfer matrix and a sensitivity analysis method; and finally, realizing parameter adaptive correction by adopting a long short-term memory network, finishing parameter optimization in combination with a multi-target genetic algorithm, packaging the model chain through a containerization technology, and realizing cross-platform deployment and visual output of a pollution load result. The method can be used for agricultural non-point source pollution prediction and management.

The invention discloses a pond multi-objective optimization management method oriented to agricultural watershed non-point source pollution regulation and control, and relates to the technical field of agricultural watershed non-point source pollution abatement. Multi-dimensional attributes such as pond application types, morphological characteristics and sediment nutrient states are integrated into a unified quantitative framework for the first time, and a generalized additive model is constructed to obtain a multi-objective optimization model; nonlinearity and interaction of pond attributes on river water quality influence can be accurately captured, and the accuracy of river nitrogen and phosphorus concentration prediction is improved. According to the method, pond management measures are quantified into controllable decision variables, a multi-target dynamic optimization model for balancing environmental benefits and economic benefits is established, a Pareto optimal solution is used for replacing a traditional experience decision, a scientific, efficient and quantitatively-implemented pond management scheme is provided, the one-sidedness of a single target is avoided, and the method is suitable for large-scale popularization and application. The cost minimization is realized while the non-point source pollution reduction is maximized, and the accurate configuration and scientific quantitative decision of pond management resources are realized.

The invention discloses a key index screening method and system for investigation and monitoring of watershed agricultural non-point source pollution, and relates to the technical field of watershed agricultural non-point source pollution prevention and control. The method comprises the following steps: acquiring multi-source spatio-temporal data of a target area about watershed agricultural non-point source pollution; the multi-source spatio-temporal data comprises water quality monitoring data, geographic spatial data, yearbook statistical data and meteorological data; constructing a feature variable set and a target variable set by using a source-migration-sink theory based on the multi-source spatio-temporal data; inputting the feature variables in the feature variable set and the target variables in the target variable set into a pre-trained machine learning model to obtain a feature importance value of the contribution degree of each feature variable to each target variable; and screening out key indexes in the feature variable set according to the feature importance value. According to the method, a scientific and unified index system can be established, the monitoring cost is remarkably reduced, and the objectivity and comparability of evaluation are improved.

The invention provides a Yellow River water irrigation area non-point source pollution load space-time analysis method, and relates to the technical field of Yellow River water irrigation area non-point source pollution monitoring and analysis, and the method comprises the following steps: S1, collecting and preprocessing multi-source basic data; according to the Yellow River water irrigation area non-point source pollution load space-time analysis method, total nitrogen and ammonia nitrogen are accurately recognized as core pollutants through three-stage fuzzy comprehensive evaluation, the recognition accuracy is improved to 90% or above, and the problem that recognition is fuzzy in a traditional method is solved; by combining nitrogen and oxygen isotopes and a flora active chip, the manure sewage is determined as a main source of nitrogen for the first time, the traceability error is controlled within 10%, and the pollution source analysis blank is filled up; a core pollution area is defined through a gravity center migration model, the pollution load space-time distribution visualization degree is improved by 60%, and area differentiation treatment is achieved; a coupling migration model is constructed, the mechanism of reverse migration of pollutants caused by irrigation return water is clarified for the first time, and the interpretation precision reaches 85%.

The invention relates to an urban non-point source pollution identification method and system based on rainfall events. The method comprises the following steps: step S100, decomposing rainfall data of a continuous time sequence into independent rainfall events and snowfall events; step S200, dividing grid units, and performing runoff calculation in each unit so as to obtain runoff information of spatial distribution; wherein the rainfall event runoff is estimated by adopting a runoff curve hydrological model method; calculating snow melting runoff by adopting a temperature index snow melting model; s300, estimating the average event concentration of the rainfall event by adopting an accumulation and scouring formula, and estimating the average event concentration of the snow melting event by using average observation values in different land utilization types; and step S400, realizing refined identification and accurate estimation of urban non-point source pollution load by integrating urban functional area characteristics, surface runoff simulation and event average concentration simulation of pollutants. The method is suitable for estimating the rainfall runoff pollution load in a large-scale region with relatively limited water quality monitoring data.

The invention belongs to the technical field of regional soil pollution evaluation and risk management, and particularly relates to a pollution grading evaluation and point source pollution identification method based on a regional soil environment background. The method comprises the following steps: determining a target area range and soil target pollutants; obtaining a current-stage soil environment background concentration data set of the target area, and calculating a statistical index of the data set; arranging regional soil pollution monitoring points, and monitoring the target pollutant content of the soil sample; and finally, the constructed pollution index evaluation model based on the soil environment background is adopted to calculate the single or combined pollution index of the soil at each point, the regional soil pollution grade and the environment quality are quantitatively evaluated, and the soil pollution point source is further identified. According to the method provided by the invention, based on the soil environment background content, the uncertainty of overestimation of non-point source pollution in a traditional soil pollution evaluation method is optimized, and the point source pollution point location can be accurately positioned.

The application discloses a kind of unmanned aerial vehicle photogrammetry and depth learning's field-gully-pond extraction method, belong to remote sensing technology and agricultural informatization technical field, method includes: using unmanned aerial vehicle carries multispectral camera and optical lens, obtains original image data by tilt photogrammetry technique;The original image data obtained is preprocessed, generates multispectral image (DOM) and digital surface model (DSM);From the spectral, topography and texture features of small watershed field-gully-pond system, construct the multiple extraction framework of U-net algorithm with built-in attention mechanism, image segmentation model supporting zero sample learning, multi-scale segmentation technology and shape feature extraction algorithm, carry out image segmentation, classification and interpretation, realize the fine extraction of small watershed field-gully-pond system;The design can improve the extraction accuracy and efficiency under complex terrain, applicable to current small watershed agricultural non-point source pollution migration trajectory simulation and farmland fine management.

The invention relates to the technical field of pollution risk assessment, and particularly discloses a non-point source pollution risk assessment method based on machine learning, and the method comprises the steps: collecting the water quality monitoring data of a target drainage basin under various meteorological conditions in a historical period, and synchronously collecting the meteorological monitoring data of a corresponding period; the method comprises the steps that meteorological extreme events and water quality response characteristics corresponding to the meteorological extreme events are extracted, a meteorological-water quality associated data set is constructed, a prediction model between meteorological factors and pollution load peak values is trained through a machine learning method, and the short-term risk level of non-point source pollution is evaluated based on a prediction result; and generating a risk early warning signal according to the risk level obtained by evaluation, and through multi-source data fusion and machine learning modeling, providing high-timeliness and high-precision risk decision support for drainage basin management, significantly enhancing the ability to cope with sudden pollution events, and improving the risk early warning effect. And meanwhile, key technical guarantee is provided for optimizing and treating resource allocation and reducing water environment disaster risks.

The invention relates to the technical field of ridge construction, and discloses an ecological ridge construction method for slowing down lateral seepage and intercepting non-point source pollution, which comprises the following steps of: extracting soil texture, elevation and area information of a target area, and scientifically delimiting a ridge and a farmland boundary by combining a spatial analysis and function partitioning algorithm; dynamically determining the height of the buffer zone according to the height difference relation and the flood and drought stress characteristics of plants; hydraulics characteristics are obtained through hydrological simulation, the width of the buffer zone and the filler amount are calculated based on the length-width ratio and hydrodynamic force coupling mechanism, optimal design of water flow regulation and control and pollution interception is achieved, and the stability and purification efficiency of the ridge system in different environments are ensured. According to the invention, the ecological ridge system with strong adaptability is constructed through cooperative analysis of multi-source terrain environment and ecological parameters.

The invention discloses a non-point source pollution intensity evaluation method based on multi-source data fusion. The non-point source pollution intensity evaluation method comprises the following steps: S1, collecting multi-source environmental data of a target drainage basin through a space-air-ground collaborative network; s2, constructing an environmental resistance-pollution source intensity coupling model, and calculating a pollution migration index and a dynamic load; and S3, calculating a non-point source pollution intensity index, and carrying out non-point source pollution risk grading. Through air-space-ground multi-source data collaboration, the space-based satellite remote sensing system, the air-based unmanned aerial vehicle monitoring system and the foundation internet-of-things sensing system are used for collecting environment data of the target drainage basin, and the environment data are used for non-point source pollution intensity calculation and non-point source pollution risk evaluation of the target drainage basin.

The invention discloses a watershed agricultural non-point source pollution on-line monitoring method and system, and relates to the technical field of agricultural non-point source pollution monitoring, a plurality of monitoring nodes are arranged in a watershed to collect water quality parameters in real time and regularly collect water body samples to obtain a monitoring data set, data preprocessing is completed through two times of frame interpolation processing and maximum and minimum normalization, and the watershed agricultural non-point source pollution on-line monitoring system is obtained. And performing real-time early warning on agricultural non-point source pollution in the drainage basin according to the established drainage basin agricultural non-point source pollution monitoring model and a preset early warning threshold value. According to the invention, the limitations of low manual sampling efficiency, incapability of real-time monitoring and limited remote sensing monitoring precision are broken through, and global dynamic monitoring is realized through multi-node deployment and real-time monitoring; a real-time early warning mechanism can timely find pollution and trigger response, and technical support is provided for efficient treatment of drainage basin agricultural non-point source pollution.

The invention relates to the technical field of agricultural environmental engineering and control, and discloses an agricultural non-point source pollution multistage control planning system and method based on a discussion hall architecture, and the system comprises an organization-level module, an adaptation-level module, a coordination-level module, an operation control-level module, a controlled-level module, a comprehensive integration discussion hall module, and an open external interface module. The organization level uses deep learning and causal inference to generate a full-watershed strategy; the discussion hall module fuses expert experience conversion constraints and carries out case migration; the adaptation level utilizes a recursive algorithm to dynamically correct model parameters; the coordination level adopts a hybrid optimization algorithm to solve a multi-objective optimization problem; the operation control level is combined with a feedforward feedback mechanism to generate an instruction; the controlled level executes actions and collects feedback; and the interface module is responsible for security encryption and verification of data interaction. According to the method, the expert intelligence of the discussion hall and the five-level hierarchical architecture are fused, qualitative and quantitative combination and full-basin dynamic collaborative optimization are realized, and the management and control precision and the response speed are improved.

The invention discloses a simulation basin non-point source pollution priority control area identification method and system, and relates to the technical field of water environment monitoring and pollution abatement, and the method comprises the steps: collecting basin basic data, and carrying out the preprocessing of the basin basic data; key resistance factors are selected, the weight of each factor is determined, a minimum cumulative resistance model is established based on a source-sink landscape theory, a source landscape is set as a pollution starting point, and the cumulative resistance value of pollutants in the process of migrating from the starting point to a receiving water body is calculated through the minimum cumulative resistance model; according to the calculated accumulated resistance value, pollution risk levels in different periods are calculated; and based on the risk level, introducing a governance feasibility factor to determine a priority control region. According to the method, the source-sink landscape theory, the minimum accumulated resistance model and multi-factor dynamic analysis are integrated, so that the priority control area which is low in data dependence, high in precision and strong in dynamic property and meets the treatment requirement is recognized, and a scientific basis is provided for targeted treatment of drainage basin non-point source pollution.

The invention discloses a rainstorm runoff flow limiting and overflowing impact resistance device and method, and belongs to the technical field of runoff non-point source pollution abatement. The device comprises a flow dividing well body and further comprises a water inlet, a flow limiting opening and an overflowing opening; by adopting a double-stage shunting mode of initial-stage interception and middle-later-stage overflow and combining the design of horizontal symmetrical distribution of the water inlet and the flow limiting port and vertical distribution of the overflow port and the water inlet, water flow can be guided to form a stable transverse flowing path, so that high-pollution rainwater is intercepted in the initial stage of rainfall by virtue of a gravity flow principle, and high-pollution rainwater is intercepted in the middle-later stage of rainfall. Clean rainwater is rapidly discharged through the flow limiting opening, so that the short-time heavy rainfall condition can be effectively handled, the flow dividing stability in different rainfall stages can be guaranteed, the impact load resistance of the device is greatly improved, the system overload risk caused by sudden flow change is reduced, and it is ensured that the efficient pollution treatment effect is always kept in long-term operation.

The invention provides a low-hill mountainous area non-point source pollution intelligent prevention and control and gradient utilization system, and relates to the technical field of low-hill mountainous area agricultural non-point source pollution prevention and control. The system comprises a drainage ditch, a water quality on-line monitoring module, an intelligent gate, a multi-stage ecological ditch pond, a direct drainage channel, an internet-of-things intelligent management and control platform and a stepped rice field. The system drives the intelligent gate to perform diversion according to a pollution index threshold value based on monitoring data, high-pollution water enters the multi-stage ecological ditch pond to be purified, low-pollution water is discharged through the direct discharge channel, and purified tail water is reused for the cascade rice field. Self-flow conveying is achieved by means of the regional height difference, a collaborative prevention and control mechanism of process interception, tail end purification and resource recycling is constructed, scientific prevention and control of pollution, intelligent management and efficient utilization of resources are achieved, the non-point source pollution treatment effect is remarkably improved, and continuous circulation of water and fertilizer resources is promoted.

The invention belongs to a non-point source pollution identification method and system for lake and reservoir water quality change, electronic equipment and a storage medium. The method comprises the steps of multi-source data acquisition, reservoir area water body mask identification, sensitive wave band analysis, hybrid inversion model architecture construction, inversion calculation, model correction and contribution quantification calculation. According to the invention, by constructing a hybrid inversion model architecture, automatic selection and optimization of different water body models are realized, and the precision and universality of the model are improved; multi-scale space-time simulation of lake and reservoir water quality changes is realized through DPeRS and SWAT in combination with the spatial resolution advantage of a remote sensing technology and the dynamic simulation capability of a hydrological model.

The invention discloses a multi-target cooperation-based drainage basin ecological restoration measure configuration optimization method. The method comprises the following steps: respectively calculating water storage benefits, ecological restoration measure corrosion reduction benefits and drainage basin different ecological restoration measure pollution reduction benefits of different drainage basin ecological restoration measures according to basic data; then constructing a multi-objective function and constraint conditions thereof; and solving and optimizing the multi-target constraint condition by using an NSGA-II optimization algorithm to obtain a Pareto leading edge of an optimized solution. According to the optimization method, the calculation stability of a mature optimization algorithm is reserved, the simulation efficiency and the result precision are remarkably improved, and the problems of large simulation deviation and low convergence speed in a traditional method can be effectively solved through verification of actual drainage basin data; meanwhile, the water storage capacity, the corrosion reduction capacity and the non-point source pollution reduction capacity serve as core optimization targets, the synergistic effect of different remediation measures can be accurately quantified, scientific optimization of the measure configuration mode is achieved, and high-precision numerical model support is provided for formulating a watershed ecological remediation scheme.

1. The name of the design product: modular phosphorus removal filter dam (PRFD). 2. The use of the design product: the design product is used for modular water treatment in aquaculture tail water, green circular breeding and non-point source pollution control research and development. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention discloses a water conservancy construction period water environment influence early warning method and system based on edge calculation, and relates to the technical field of water conservancy environment early warning, and the method comprises the steps: receiving a construction scheme of a water conservancy project, and building a point source risk network and a non-point source risk network; establishing a first edge water environment monitoring network; analyzing the monitoring effectiveness of the water environment influence, and generating a second edge water environment monitoring network; monitoring and early warning of point source pollution are carried out through the first edge water environment monitoring network, and monitoring and early warning of non-point source pollution are carried out through the second edge water environment monitoring network. The technical problems that in the prior art, water environment pollution risk points in the water conservancy construction period are not accurately recognized, and water environment influence early warning comprehensiveness and accuracy are insufficient are solved, and the technical effects that the water environment pollution risk points in the water conservancy construction period are accurately recognized, and the water environment influence early warning comprehensiveness and accuracy are improved are achieved.

The invention provides a water environment non-point source pollution recognition method and device based on hyperspectral scanning, and belongs to the field of non-point source pollution recognized.The method comprises the steps that a target point location is obtained, and the target point location is the point location with the non-point source characteristic pollution index concentration exceeding the preset quality control concentration; the non-point source pollution confidence coefficient of the target point location is determined according to the hyperspectral information of the target point location, the multiple ground feature types and the weights corresponding to the ground feature types, the weight corresponding to each ground feature type is in positive correlation with the distance between the ground feature type and the target point location, and the multiple ground feature types include the agricultural land type and the non-agricultural land type; and if the non-point source pollution confidence exceeds the preset threshold, calculating the change rate of the water quality parameter of the target point location, and identifying whether the non-point source pollution occurs at the target point location according to the change rate. According to the water environment non-point source pollution identification method and device based on hyperspectral scanning, the non-point source pollution hot spot area can be automatically identified based on the hyperspectral scanning technology in combination with the ground feature type.

The invention relates to the technical field of pollution detection devices, in particular to a waterfront water and soil loss non-point source pollution detection device and method.The waterfront water and soil loss non-point source pollution detection device comprises a water and soil loss monitor, the water and soil loss monitor is installed on a supporting plate, the supporting plate is in lap joint with the top of a ditch supporting plate, and wire bunching arms are rotationally connected to the two sides of the supporting plate; the surface of the bunching arm is provided with a bunching groove, the connecting end of the water and soil loss monitor is connected with a wire, one end of the wire is provided with a sensor probe, and the wire and the sensor probe both extend into the bunching groove; the device has the advantages that the bunching arms rotationally connected to the two sides of the supporting plate are ingenious in design, the bunching arms can swing downwards to the bottom of the ditch supporting plate, and a sensor probe installed at one end of a wire can extend into a ditch to detect a flowing water source. Meanwhile, the bunching groove formed in the surface of the bunching arm provides an ordered placement space for the wire and the sensor probe, and the wire bunching arm is fixed through the cooperation of the bunching groove and the hand-twisted screw, so that the wire and the sensor probe are effectively prevented from swinging under the impact of water flow.

The invention discloses an artificial wetland space optimization arrangement method and system, a non-point source pollution model is constructed based on a hydrological response unit, target meteorological data, target pollution data and an SWAT model, and the simulation precision of the non-point source pollution process can be improved. Climate scene data is constructed through future climate data, a preset path rule and a simple quantile algorithm, and the influence of climate change on pollution load can be reflected. Furthermore, a wetland optimization model is constructed based on a non-point source pollution model and a target function, the scientificity of an optimization strategy is enhanced, candidate wetland areas are identified by a spatial analysis algorithm based on a complex terrain index CTI, and the maximum potential area of each candidate wetland area is counted, so that efficient identification of potential arrangement areas can be realized. The constructed wetland optimization regulation and control scheme is generated based on the preset genetic algorithm, and the constructed wetland space optimization arrangement is performed according to the scheme, so that the optimization and practicability of the constructed wetland layout can be realized.

The application provides a construction method of a natural river channel and overbank wetland, comprising the following steps: S1: constructing a natural river channel and three-stage overbank in a riverbed according to historical daily flow statistical characteristics, so as to adapt to river channel flow characteristics under different rainfall scenarios; and S2: constructing overbank wetlands with different characteristics according to selected overbank types. The application relies on overbank wetlands to comprehensively improve the ecological service function of the river channel; in a non-rainfall scenario, the service functions of landscape, soil conservation, wind prevention and sand fixation are realized; and in a rainfall scenario, the service functions of reducing non-point source pollution, storing flood, and improving water environmental quality are mainly played.

The present application belongs to the technical field of nitrogen and phosphorus non-point source pollution key source area identification, and relates to a nitrogen and phosphorus non-point source pollution key source area identification method based on weighted feature importance. Watershed water system, underlying surface conditions, meteorological, hydrological and water environment data are collected and arranged to establish a watershed nitrogen and phosphorus non-point source pollution tracing basic data set. A RF model, a GBRT model, an XGBoost model and a CatBoost model are used to construct a basic model for simulating total nitrogen and total phosphorus flux, and a Ridge model is used to construct a meta-model for simulating total nitrogen and total phosphorus flux. The basic model is applied to carry out sub-basin feature importance analysis, and the meta-model is applied to carry out basic model weight analysis. By analyzing the weighted feature importance of the sub-basin, the nitrogen and phosphorus non-point source pollution key source area is identified according to the importance from high to low. The present application makes up for the shortage of the existing non-point source pollution key source area identification method based on mechanism model, i.e. more parameters and difficult calibration.

The application relates to the technical field of automatic water quality monitoring, and discloses a water quality automatic monitoring device for high-frequency real-time monitoring of TN situation of non-point source pollution, which comprises a main box, a water and gas distribution module, the water and gas distribution module is composed of a measuring tank, a submersible pump, an air pump and an electric valve, the measuring tank is installed at the bottom of the main box and is used for storing water delivered by the submersible pump, a water inlet pipe and an air inlet pipe are installed on one side of the measuring tank, an overflow pipe is arranged on the other side of the measuring tank, a water outlet pipe is installed at the lower end of the measuring tank, and a water distribution assembly is obliquely installed in the measuring tank. The water quality automatic monitoring device for high-frequency real-time monitoring of TN situation of non-point source pollution can reduce the interval time of monitoring, continuously monitors nitrogen and phosphorus pollution in river water in a short time, and is not affected by sundries in the river water during work, so that the detection device can reflect the migration and transformation of non-point source pollution, and the monitoring, early warning and research of non-point source pollution can be prevented from being delayed and uncertain.

The invention relates to a water environment pollution source reasoning and tracing method, system and equipment and a medium. The method comprises the following steps: constructing a pollution source characteristic database containing spectrum fingerprints and spatio-temporal information; performing time sequence enhancement on the mixed spectral signal of the monitoring point to extract stable features; a hydrological model is coupled to dynamically simulate pollutant transport paths and probabilities, and a potential contribution source set with weights is generated; analyzing the mixed signal by adopting a deep unmixing network embedded with space-time constraint, and separating and quantifying known source contribution and unknown pollution components; and finally, generating a visual pollution contribution degree spatial distribution diagram and a quantitative traceability report through geographic information mapping. The method solves the problems that complex mixed signals are difficult to accurately analyze, multi-source contribution is difficult to dynamically quantify and unknown pollution components are difficult to effectively recognize in the prior art, and intelligent and accurate traceability of municipal water environment non-point source pollution is achieved.

The invention provides an urban area non-point source pollution key risk area identification method based on a PCSWMM model. The method comprises the following steps: constructing a PCSWMM model of a research area; selecting a plurality of non-point source pollution influence factors of the research area as non-point source pollution risk indexes; based on a PCSWMM model, an evaluation index system is constructed through non-point source pollution risk indexes; determining a risk index weight in the evaluation index system through a variable coefficient method; based on the risk index weight, determining a risk evaluation result through fuzzy comprehensive evaluation; and drawing a non-point source pollution risk result graph according to the risk evaluation result. According to the method, the PCSWMM model and the multi-factor statistical analysis are combined, so that the problems of incomplete consideration of influence factors, strong data dependence and high operation cost are solved, and the identification precision of the non-point source pollution key region is improved.

The invention relates to the technical field of ecological environment data processing, in particular to a river non-point source pollution source identification method, device and equipment. The method comprises the following steps: calculating a first pollutant influence factor of a target drainage basin grid based on acquired hydrological information; according to the first pollutant influence factor and the hydrological information, utilizing the constructed conditional distribution function to calculate a second pollutant influence factor of the target drainage basin grid; determining residual pollutant influence factors according to the target drainage basin grids and the target river; according to the first pollutant influence factor, the second pollutant influence factor and the residual pollutant influence factor, calculating to obtain a pollutant accessibility index of the target drainage basin grid relative to the target river; the potential non-point source pollution source degree of the target river basin grid to the target river is evaluated based on the pollutant accessibility index, and the problem that in an existing non-point source pollutant identification method, the non-point source pollutant identification accuracy is low can be effectively solved.

The application discloses a water quality pollution event tracing method and a terminal. When a pollution event is monitored, a monitoring site is determined as a target water quality section. A pollution curve of the target water quality section is obtained, and a pollution path pollution curve, a non-point source pollution curve and an internal source pollution curve corresponding to the target water quality section are calculated. The pollution dominant probability of each pollution path in the pollution event is calculated. The pollution source is determined based on the pollution dominant probability. The pollution source is simply and effectively positioned considering the multi-source water quality pollution, so that the pollution event source is accurately and quickly positioned.