157 results about "Agricultural nonpoint source pollution" patented technology

The invention relates to the technical field of agricultural traceability, and discloses an agricultural non-point source pollution intelligent traceability method and system based on a knowledge graph, and the method comprises the steps: achieving the system integration of pollution source features through constructing the knowledge graph fusing multi-dimensional data, and building a sky-ground integrated monitoring network to obtain multi-scale dynamic data. An intelligent traceability mechanism is formed based on deep coupling of a knowledge graph and monitoring data, a high-precision pollution identification model is trained in combination with historical data, and real-time response and dynamic traceability of an over-standard pollution area are achieved. And verifying a traceability result through feature matching and semantic reasoning, quantitatively calculating a pollution contribution rate, and finally generating a reliable traceability conclusion containing the position, the type and the contribution rate. According to the scheme, the bottlenecks of data fragmentation, monitoring simplification, extensive analysis and the like of a traditional method are broken through, and the accuracy, timeliness and credibility of pollution traceability are remarkably improved through a series of full-chain technical systems of traceability identification, analysis and positioning.

The present application relates to the field of environmental monitoring and governance, and discloses a supervision system and method for agricultural non-point source pollution scenarios. The system includes a perception module, a data management module, an intelligent analysis module, and an application service module. The perception module collects pollutant concentration, hydrological characteristics, and abnormal behavior data through water quality sensors, high-position video monitoring equipment, and drones; the data management module dynamically integrates, stores, and standardizes the data collected by the perception module; the intelligent analysis module predicts the diffusion path of pollutants in the water body based on the pollution diffusion model, and inverts the spatial location and intensity of the pollution source by combining the video monitoring abnormal behavior records with the diffusion model; the application service module displays the analysis results, triggers warnings, and supports remote governance operations through an intelligent early warning system, a GIS visualization platform, and mobile devices. The present invention can accurately monitor agricultural non-point source pollution, improve the efficiency of pollution source positioning and supervision, and provide technical support for the governance of agricultural non-point source pollution.

The invention provides a plateau lake agricultural non-point source pollution treatment method which comprises the following steps: acquiring vegetation indexes and surface temperature field data by using a remote sensing satellite, and generating a pollution source space thermodynamic diagram in combination with water quality and soil parameters of ground sampling points; performing space-time alignment and data fusion on the thermodynamic diagram and real-time runoff and soil permeability data acquired by the hydrological sensor network, and constructing a structured pollution migration database; on the basis of the database, a hybrid neural network model embedded with physical constraints is utilized to predict pollutant concentration distribution within 72 hours in the future; inputting the predicted value into a multi-stage optimization controller, and generating a control parameter set comprising treatment intensity, engineering parameters and a fertilization ratio; generating a treatment strategy map covering the drainage basin through a GIS; and deploying an Internet of Things monitoring node to collect the treated water quality data to form a closed-loop control link. The treatment efficiency and effect can be improved, the treatment cost is reduced, and the negative influence on the ecological environment is reduced.

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 relates to the field of agricultural environment monitoring, and provides an agricultural non-point source pollution early warning method and system and electronic equipment, and the method comprises the steps: obtaining a first pollution monitoring parameter of a to-be-monitored region; predicting a second pollution monitoring parameter of the to-be-monitored area in a set time period; when the second pollution monitoring parameter meets the first early warning condition, first-level early warning is carried out, and when the second pollution monitoring parameter does not meet the first early warning condition but meets the second early warning condition, second-level early warning is carried out; and calculating the pollution contribution rate of the to-be-monitored area to the downstream area through the graph neural network, and if the pollution contribution rate meets a third early warning condition, performing third-level early warning. The invention discloses an agricultural non-point source pollution monitoring method and device, aims to overcome the defects that pollution monitoring means in the prior art are difficult to accurately identify and early warn pollution and cannot position pollution sources, can perform different levels of early warning on agricultural non-point source pollution through a graded early warning mechanism, and can realize real-time monitoring, dynamic early warning and accurate treatment of regional pollution.

The invention provides an agricultural non-point source load simulation calculation method, and relates to the field of agricultural non-point source pollution calculation, and the method comprises the steps: constructing an agricultural non-point source load calculation model, reading surface runoff time sequence data of each hydrological response unit in a drainage basin, and setting corresponding model parameters; setting a time step length, sequentially calculating the thickness of soil capable of being scoured in the current time step length, the amount of pollutants capable of being scoured in unit area and the amount of pollutants actually scoured in unit area by utilizing surface runoff time sequence data and model parameters, and finally obtaining the updating amount of the concentration of the soil pollutants in the current time step length. All hydrological response units are respectively subjected to the above calculation in the simulation time period to obtain a time sequence of the soil pollutant concentration updating amount, and the agricultural non-point source load of the drainage basin in the simulation time period is calculated in combination with the surface runoff time sequence data. According to the method, the natural process in the agricultural non-point source scouring process is fused into the model, and the obtained agricultural non-point source load is more accurate and more interpretable.

The invention discloses a high temporal-spatial resolution risk assessment method for agricultural non-point source pollution in a plain river network region. The method comprises the following steps: selecting an assessment region; dividing evaluation units; selecting an evaluation time period; basic data collection and necessary supplementary monitoring of an evaluation area; agricultural non-point source pollution in-river load accounting; evaluating the bearing capacity of the riverway on non-point source pollution; calculating evaluation indexes; carrying out risk grade delimiting; compiling a priority treatment area list; agricultural non-point source pollution control measures are implemented; and evaluating agricultural non-point source pollution prevention and control performance. The polder area and the irrigation and drainage area are used as agricultural non-point source pollution risk last-stage evaluation units, so that the spatial resolution of agricultural non-point source pollution risk evaluation is greatly improved; a monthly risk assessment method is provided, and the time resolution of agricultural non-point source pollution risk assessment is greatly improved; a land and water linkage evaluation index system is adopted, excessive adoption of weights is avoided, the index meaning is clear, and targeted accurate recognition of a key source area is achieved through mutual verification of different indexes.

The invention provides an intelligent river water quality monitoring system based on a remote sensing technology, belongs to the technical field of river monitoring, and solves the technical problem that the current intelligent river water quality monitoring cannot realize full-space-time river water quality monitoring from large scale to microcosmic scale and point-surface combination. A river water quality intelligent monitoring system based on a remote sensing technology comprises a satellite remote sensing module, an unmanned aerial vehicle remote sensing module, a high-altitude holder module and a ground water quality detection module. According to the invention, through the arrangement of the satellite remote sensing module, the unmanned aerial vehicle remote sensing module, the high-altitude holder module and the ground water quality detection module, the air-space-tower-ground multi-source cooperative monitoring of the river water quality is realized, and under the action of the fixed-ship flow measurement assembly of the unmanned ship, moving and fixed-point monitoring can be carried out in the river; and meanwhile, satellite remote sensing and an unmanned aerial vehicle are utilized, and agricultural non-point source pollution satellite remote sensing and ground automatic monitoring advanced mature technologies are integrated, so that water quality monitoring is changed from large-scale monitoring to microscopic detection.

The invention discloses a regulation and control method for preventing nitrogen and phosphorus loss of saline-alkali farmland drainage, and particularly relates to the technical field of agricultural environment protection and water and fertilizer management. Establishing a three-dimensional drainage path initial model, and calculating a drainage easy flow intensity coefficient according to the gradient and sodium saturation joint index of each micro-unit; further monitoring the change rate of nitrogen and phosphorus concentration in different areas through experimental nitrogen and phosphorus tracking irrigation to obtain a nitrogen and phosphorus migration sensitivity parameter; and performing weighted combination on the drainage easy flow intensity coefficient and the nitrogen and phosphorus migration sensitivity parameter, constructing a nitrogen and phosphorus loss risk index, forming a saline-alkali farmland nitrogen and phosphorus loss risk hot area distribution map, taking an area with the identified risk index exceeding a preset threshold value as a target area needing regulation and control, and implementing differential regulation and control measures in the target area to obtain a saline-alkali farmland nitrogen and phosphorus loss risk hot area distribution map. The method can realize accurate identification and dynamic regulation and control of the nitrogen and phosphorus loss of the saline-alkali farmland, improves the utilization efficiency of the fertilizer, reduces the risk of agricultural non-point source pollution, and has relatively strong popularization significance.

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 relates to an agricultural non-point source polluted soil nitrate nitrogen in-situ monitoring system and method, and aims to solve the technical problem that accurate in-situ monitoring of soil leaching nitrate nitrogen and a migration rule is difficult to realize. Wherein the soil leaching solution extraction device comprises moisture sensors buried in different soil depths, a leaching solution extraction probe, a solution storage container and a negative pressure source, and the detection device comprises at least two groups of micro-flow pool channels connected in parallel and a photoelectric detection path corresponding to nitrate nitrogen ultraviolet light absorption and non-absorption wavebands; the liquid pumping pipeline is respectively communicated with the liquid storage container and the micro-flow pool channel; the control module receives information collected by the moisture sensor and determines whether to send a negative pressure source starting instruction or not after comparing the information with a set value, a negative pressure cavity is formed in the leaching solution extraction probe, and soil leaching solution collection is achieved. The in-situ monitoring of the leaching nitrate nitrogen can be realized without disturbing the soil structure; the result is continuous, accurate and reliable, and a reliable way is provided for obtaining accurate data information related to agricultural non-point source pollution distribution, migration, development trend and the like.

The invention relates to the technical field of agricultural pollution treatment, in particular to an agricultural non-point source pollution treatment device which comprises a multi-stage treatment tank, and a water inlet is formed in the top end of the multi-stage treatment tank; the first-stage separation mechanism comprises a separation cylinder used for separating large impurities in sewage, and the separation cylinder is composed of a separation frame and a fine-mesh filter screen; and the secondary separation mechanism comprises a self-adaptive adding assembly used for adding a medicament, the self-adaptive adding assembly comprises a rotating ball which rotates passively, and a plurality of medicament adding grooves which are arranged in a circumferential array mode are formed in the outer wall of the rotating ball. After agricultural sewage is discharged into the multi-stage treatment tank through the water inlet, solid and liquid are primarily separated through high-speed rotation of the centrifugal cylinder in the first-stage separation mechanism; separated liquid enters a conical water collecting cover, part of sewage enters a detection shell to detect the content of suspended particles, and a proper amount of flocculating agent is added into the sewage through a self-adaptive adding assembly according to a detection result.

The utility model relates to the technical field of cultivation, in particular to a land-based circulating rice and fish comprehensive planting and breeding device. The system comprises a rice planting field, a reservoir and a culture pond, a water pumping pipe is arranged between the rice planting field and the outer wall of the reservoir, a water pump is installed on the side face of a water pumping pipe shaft close to the rice planting field, a water inlet pipe is connected between the outer wall of the reservoir and the upper portion of the outer wall of the culture pond, and a water drainage pipe is connected between the upper portion of the outer wall of the culture pond and the rice planting field. Tail water generated by the culture pond enters the rice field circular ditch through the drainage pipe, the water suction pump is started after the tail water is treated to reach the standard, the tail water flows back and is collected to the water storage pond through the water suction pipe, then water in the water storage pond enters the culture pond through the water inlet pipe, repeated circulation is achieved, water and land are saved, and meanwhile the economic benefit of a unit rice field is improved. Agricultural non-point source pollution is reduced, the problems of facility fishery tail water discharge and treatment are effectively solved, environmental protection and ecological breeding are achieved, and green and healthy development of aquatic products is achieved.

The invention discloses an ecological rural ditch nitrogen and phosphorus interception system and method, belongs to the technical field of agricultural non-point source pollution control and water environment treatment, and provides an innovative'buffer-purification-interception 'composite ecological rural ditch nitrogen and phosphorus interception technology. By optimizing the ditch design and the ecological structure, the ecological function of the ditch is enhanced, and pollutants such as nitrogen and phosphorus in farmland drainage are efficiently intercepted and purified by removing nitrogen and phosphorus in a multi-level manner.

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 an accurate prevention and control method for agricultural non-point source pollution based on a dissolved oxygen hysteresis effect. The invention relates to the technical field of agricultural non-point source pollution prevention and control, and solves the problem that an existing agricultural non-point source pollution treatment method is difficult to meet accurate prevention and control requirements. The method comprises the following steps: constructing an SWAT model, and simulating monthly-scale nutritive salt load of each crop planting area; establishing a drainage basin-lake coupling model, inputting the nutritive salt load simulated by the SWAT model into a lake hydrodynamic water quality model, and performing calibration; adopting dissolved oxygen data output by the calibrated lake water power water quality model as a training set to train a dissolved oxygen concentration prediction model; determining dominant lag time of different crop areas by adopting an SHAP value analysis method; the optimal fertilization time window of each crop area is calculated by applying a backward model, and a differentiated fertilization reduction scheme is formulated based on the contribution degree weight of the nutritive salt, so that accurate regulation and control of agricultural non-point source pollution are realized, and the lake water quality is effectively improved while the use of chemical fertilizer is reduced.

The invention relates to an agricultural non-point source pollution intelligent management system based on the Internet of Things, and the system comprises an agricultural basic information obtaining module which is used for collecting the agricultural basic data of a target region; the agricultural pollution data acquisition module is used for acquiring agricultural non-point source pollution data of a target area in real time by arranging a monitoring station; the agricultural pollution data analysis module is used for processing and analyzing the agricultural basic data and the agricultural non-point source pollution data to obtain a pollution change trend and a pollution abnormal value; and the pollution early warning module is used for sending early warning information based on the pollution change trend and the pollution abnormal value and providing a treatment decision. The agricultural non-point source pollution abnormal value and the abnormal reason can be rapidly judged, and effective decision support is provided for prevention and treatment of agricultural non-point source pollution.

The invention discloses a pollution reduction and carbon reduction type agricultural non-point source pollution purification method, and particularly relates to the field of environmental protection, and the method comprises the steps of monitoring area division, purification data acquisition, purification data analysis and comprehensive analysis. According to the invention, the four-dimensional monitoring system is constructed to synchronously quantify the pollutant removal and carbon interception processes, the material energy flow rule of the agricultural non-point source system is accurately analyzed, and the deficiency of carbon cycle monitoring in the traditional technology is made up; a multi-index coupling model is adopted to convert fragmented data into comprehensive evaluation values of microbial activity, carbon-nitrogen conversion efficiency, plant tolerance and carbon retention capacity, the limitation of single-dimensional evaluation is broken through, and a three-dimensional decision basis is formed; a dynamic threshold judgment mechanism is established, intelligent identification and efficient purification are performed according to real-time data, regulation and risk early warning modes need to be optimized, differentiated treatment measures are triggered to improve the self-adaptive capacity of the system, the problem of response lag in the traditional technology is solved, and the treatment mode is promoted to be upgraded to the pollution reduction and carbon reduction collaboration direction.

The present invention provides a method for simulating and calculating agricultural non-point source loads, which relates to the field of agricultural non-point source pollution calculation. The method comprises: constructing an agricultural non-point source load calculation model, reading surface runoff time series data of each hydrological response unit in a watershed, and setting corresponding model parameters; setting a time step, and using the surface runoff time series data and the model parameters, sequentially calculating the soil thickness that can be washed within the current time step, the amount of pollutants that can be washed per unit area, and the amount of pollutants actually washed per unit area, ultimately obtaining an updated amount of soil pollutant concentration for the current time step; performing the above calculations for all hydrological response units within a simulation period, obtaining a time series of the updated amount of soil pollutant concentration, and calculating the agricultural non-point source load of the watershed within the simulation period in combination with the surface runoff time series data. The present invention incorporates the natural processes of agricultural non-point source washout into the model, resulting in a more accurate and interpretable agricultural non-point source load.

The invention is suitable for the field of digital control, and discloses an energy recovery method and system for agricultural non-point source pollution treatment and a storage medium. The energy recovery method for agricultural non-point source pollution treatment comprises the steps that if to-be-treated pollutants are detected, component information of the to-be-treated pollutants is detected, the component information comprises the carbon nitrogen ratio, the water content and the organic matter content, and the to-be-treated pollutants comprise at least one of livestock and poultry breeding waste, crop straw, rural domestic sewage and agricultural production wastewater; according to the component information, a target energy conversion process is selected, and the target energy conversion process comprises at least one of an anaerobic fermentation biogas preparation process, a biomass pyrolysis fuel gas production process, a sewage anaerobic electricity production process and a straw solidification heat production process; according to the target energy conversion process, the recovered energy is output, collected and stored, and the energy comprises at least one of methane, combustible mixed gas, electric energy and heat energy. The conversion efficiency of energy recovery is improved.

The invention relates to the technical field of agricultural non-point source pollution load evaluation, and provides an agricultural non-point source pollution real-time simulation method, device and equipment for an event rainfall. The method comprises the following steps: acquiring preset basic data of a target area, corresponding forecast rainfall of each hydrological response unit under a time scale, and initial conditions of each hydrological response unit before a rainfall event occurs; according to the forecast rainfall capacity, preset basic data and initial conditions of the model, prediction is carried out in combination with an agricultural non-point source pollution model of the rainfall event, and the flow and nitrogen and phosphorus load simulation values at the hydrological monitoring node at the current time point are obtained; and real-time correction simulation of the session event process is carried out based on an ensemble Kalman filtering algorithm and real-time monitored and transmitted flow and nitrogen and phosphorus load observation values. According to the method, the precision of the initial condition of the agricultural non-point source pollution model of the session rainfall event can be effectively improved, and real-time simulation of the process of the agricultural non-point source pollution model of the session rainfall event is realized.

The invention relates to the technical field of agricultural non-point source pollution treatment, in particular to a method for predicting regional agricultural non-point source risks, which is used for predicting the pollution risks of regions possibly polluted by agricultural non-point sources by collecting existing environmental basic data and constructing a proper model. In an agricultural non-point source pollution-oriented region, the method can accurately predict the concentration of nutrient substances in water bodies in different time periods and different regions, can provide a scientific basis for optimizing agricultural management measures and reducing non-point source pollution risks, and also provides a reference for agricultural non-point source pollution assessment of other drainage basins.

This invention provides a composite ecological restoration system and method for agricultural non-point source pollution in lakes. The system includes several pre-treatment reservoirs located at the lake's edge, each including a sedimentation zone, a shallow water purification zone, and a deep water purification zone; several water quality improvement wetlands adjacent to the pre-treatment reservoirs; several ecological interception ditches located at the entry points of agricultural non-point source pollution into the lake; a shoreline ecological interception zone surrounding the lake and located along its shoreline; an ecological enclosure adjacent to the water quality improvement wetlands, within which a submerged plant restoration zone is arranged; several submerged plant restoration zones are located inside the ecological enclosure; and ecological floating islands are evenly distributed within the lake. This invention can effectively address the complex and variable nature of lake non-point source pollution, improve the treatment effect of lake non-point source pollution, and achieve the goal of treating different types of lakes.

The invention relates to the technical field of farmland non-point source pollution control, in particular to an agricultural non-point source pollution load calculation method based on trend pre-judgment. The invention discloses an agricultural non-point source pollution load calculation method based on trend pre-judgment. The method comprises the steps of S1, data collection and preprocessing; s2, trend modeling and future prediction; s3, future pollution load calculation; s4, calculating a future pollution load weight; s5, a preliminary integration formula of non-point source pollution load calculation; s6, performing iterative optimization and convergence judgment; and S7, result calculation. Through fusion of future trend prediction, entropy weight method weight distribution and a dynamic correction function, the problems of insufficient foresight, weight staticization and environmental response lag in the prior art are solved. According to the method, the current pollution load calculation result can be dynamically corrected, and a scientific basis is provided for agricultural non-point source pollution prevention and control.

The invention relates to the technical field of farmland available nutrient information online acquisition, and discloses an online farmland available nitrogen and phosphorus nutrient networking monitoring method which comprises the following steps: firstly, burying a plurality of sensor combined probes and sampling probes in different depths of farmland monitoring area soil; secondly, constructing a monitoring device at a farmland intersection to extract soil leaching solutions at different depths and monitor the content of available nitrogen and phosphorus nutrients on line; and finally, uploading a monitoring result to a cloud platform for storage, analysis and processing. According to the method, the dynamic change of available nitrogen and phosphorus nutrients in different depths of soil is monitored on line, so that farmland available nutrient information is obtained on line, accurate management of crop nutrients is realized, and the problems of hysteresis and data distortion of a traditional sampling detection method are solved; meanwhile, nutrient distribution of a monitoring area is managed in combination with an internet cloud platform, space nutrient information of a certain farming area is obtained, the fertilization mode is dynamically adjusted, the utilization rate of chemical fertilizer is effectively increased, and a scientific basis is provided for agricultural non-point source pollution prevention and control.

The invention discloses a rice-wheat rotation area liquid manure efficient returning planting method, which comprises the following steps: step 1, precisely metering and applying liquid manure subjected to innocent treatment, step 2, precisely applying the liquid manure by stages according to the fertilizer requirement rules of rice and wheat in different growth periods, and step 3, performing returning operation by combining injection type deep application and movable sprinkling irrigation equipment. 4, carrying out matched management after the liquid manure is applied; 5, carrying out a dynamic management closed loop of measurement, calculation, determination, application, monitoring and regulation; through system implementation and dynamic closed-loop management of three precise dimensions of opportunity, method and proportioning, ammonia volatilization and nitrogen and phosphorus runoff loss are greatly reduced, agricultural non-point source pollution is effectively controlled, soil organic matter is stably increased, chemical fertilizer investment can be remarkably reduced through precise replacement, the production cost is reduced, and the economic benefit is increased. Meanwhile, fertilizer utilization rate is increased, annual yield of rice and wheat is increased, and income is increased.

The invention discloses an agricultural non-point source pollution monitoring data quality evaluation method, and relates to the field of agricultural environment monitoring, an agricultural non-point source pollution area to be monitored is divided into a plurality of grid areas to be monitored, and a fixed monitoring unit is arranged in the physical center of each grid area; and the server creates a double-track digital file for each grid area, the double-track digital file comprises a static attribute and a dynamic attribute, the double-track digital file is stored in a database and updated according to a preset period, and an updated version record is retained. According to the method, a three-dimensional multi-index comprehensive scoring and fixed mobile monitoring collaborative verification mode is adopted, the key dimension of data quality is comprehensively covered, misjudgment is reduced, and the evaluation accuracy is improved. An index calculation method, weight configuration and threshold standard are clear, the process is clear and operable, and actual popularization and application are facilitated. And targeted rectification suggestions are output, so that the quality optimization of the monitoring data can be directly guided, the reliability of the monitoring data is guaranteed, and powerful support is provided for agricultural non-point source pollution abatement decisions.

The utility model discloses a treatment device for preventing and treating agricultural non-point source pollution, which comprises a box body, one side of the box body is provided with a water inlet pipe, the other side of the box body is provided with a water drainage pipe, a filter plate is detachably connected between the inner walls of the two sides of the box body through bolts, one side of the box body is provided with an avoiding opening, and the avoiding opening is provided with a water outlet. And the avoiding opening is located between the water inlet pipe and the filter plate, a collecting box is slidably connected into the avoiding opening, one side of the collecting box makes contact with the inner wall of one side of the box body, a fixing assembly is arranged between the box body and the collecting box, and two handles are fixedly connected to one side of the collecting box. According to the sewage treatment device, polluted water entering the box body can be preliminarily filtered through the filter plate, and filtered garbage can be collected into the collection box through the collection box, so that treatment is facilitated.

The invention discloses a crop disease, pest and weed identification and pesticide application system and method based on multi-modal fusion, and the system comprises a multi-modal data collection unit, an edge calculation and intelligent identification unit, and a precise decision and targeted pesticide application unit. The multi-modal data acquisition unit is used for acquiring visible light information of crops, fine spectral information of canopies and geographical location information, and the edge calculation and intelligent identification unit is used for preprocessing the acquired multi-modal data, then performing cross-modal attention fusion, performing information feature comparison with a stored disease, pest and weed damage library, and obtaining a target object. The accurate decision-making and targeted pesticide application unit is used for completing accurate pesticide delivery according to the information of the diseases, the weeds and the pests of the crops. Through targeted pesticide application and on-demand pesticide preparation, it is predicted that the pesticide use amount can be reduced by 50% or above, the production cost is directly reduced, and the risk of agricultural non-point source pollution and agricultural product pesticide residue is relieved from the source.