108 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 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 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 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 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.

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 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.

The utility model discloses an agricultural non-point source pollutant intercepting device, which belongs to the technical field of pollutant intercepting and particularly comprises a stabilizing component, a driving component arranged in the stabilizing component and a supporting component arranged at the bottom of the stabilizing component, and the driving component further comprises an intercepting net. The blocking net at the tail end of the driving rope is pulled, so that the blocking net entering the sewage can intercept solid pollutants, and the pollutant treatment of an agricultural non-point source is ensured; the multiple degradation assemblies serve as balancing weights, and meanwhile, a biodegradation layer is arranged in a degradation bin in each degradation assembly, so that agricultural non-point source pollution in a polluted water source can be sterilized and purified, and pesticide residues are reduced; the oppositely-arranged stabilizing assemblies can be matched with a motor to hoist and fall the blocking net, and in the outdoor area with the uneven ground, the purpose that the blocking net is kept horizontal can be achieved by adjusting the supporting rods in the supporting assemblies to ascend and descend.

The invention discloses a pixel scale water environment safety assessment method based on a non-point source water body pollution risk, and belongs to the technical field of environmental protection. According to the method, through an agricultural non-point source pollution direct evaluation method, the pollution risk of terrestrial agricultural non-point source output to surface water is accurately quantified, a DPeRS model is introduced, quantitative evaluation of the remote sensing pixel scale agricultural non-point source river entering amount is achieved, and the pixel scale agricultural non-point source river entering concentration is quantified as a non-point source pollution risk evaluation index in combination with an SWAT model. With surface water environment quality improvement as a target, an agricultural non-point source pollution in-water risk grade threshold value is determined based on a nitrogen and phosphorus concentration limit value in a surface water environment quality standard and a national secondary pollution general survey agricultural non-point source proportion, and a pixel scale agricultural non-point source in-water pollution risk prominent area is rapidly screened. High-precision target positioning of remote sensing pixel scale agricultural non-point source pollution is realized, and source-targeted agricultural non-point source pollution precise prevention and control and agricultural non-point source pollution treatment effect evaluation are facilitated.

The invention discloses a pollution risk identification and early warning method based on a multi-level scale. The method comprises the following steps: dividing county level grids, town level grids, village level grids and extensive plot grids; selecting a pressure index, a state index and a response index as risk identification indexes, collecting corresponding remote sensing data, ground sensor network data and agricultural data, and then performing space-time matching by adopting a Bayesian fusion model to obtain a standardized data set of each level of grid unit; a Delphi method is adopted to carry out multiple times of assignment to determine the weights of the three indexes, then a risk identification model is constructed, then a risk value is calculated, and a total quantity Quantile grading method is adopted to divide risk levels to identify the risk of each grid unit; a quantile and exponential smoothing method is adopted to dynamically adjust a threshold value, then early warning grades are divided according to the threshold value, and finally early warning is carried out according to the early warning grades. The agricultural non-point source pollution multi-level scale high-precision identification and real-time early warning are realized, and the precision and timeliness of pollution management are improved.

The invention relates to the technical field of environment monitoring, and discloses a plateau lake basin cultivated land soil pollution multi-index synchronous monitoring method. The method is suitable for plateau lake basin cultivated land, and under the condition that plateau lake basin cultivated land soil measured data is high in acquisition cost and difficult to acquire in quantity, a spatial distribution diagram of cultivated land soil non-point source pollution source load indexes is acquired in a large-scale, low-cost and high-efficiency manner by assisting limited field monitoring data through a satellite remote sensing means. Through long-term soil pollution index content and variable quantity monitoring and risk level evaluation, visualization, quantifiability, traceability and prevention and control of non-point source pollution are realized, the limitation of replacing surface by point in traditional point location measurement is overcome, and the method is the most efficient method for evaluating the potential risk of agricultural non-point source pollution.

The invention discloses a method for carrying out modeling simulation analysis on regional pesticide residue diffusion by utilizing a network density matrix. The invention provides a novel food safety modeling theory by utilizing the latest progress of statistical physics and machine learning in the field of network flow. Entropy and free energy concepts in statistical physics are introduced, path diversity and signal speed in the network are quantitatively represented by constructing a network density matrix, and deep analysis is performed on an established dynamic weighted network model. According to the method, the diffusion path, speed and concentration change after pesticide residue leakage can be accurately simulated, and then the influence of pesticide residue leakage and diffusion on the region is analyzed. By providing a scientific quantitative analysis theory for food safety prediction, the risk supervision capability is effectively improved, and powerful support is provided for agricultural non-point source pollution treatment.

The application provides a kind of method for identifying key source area of non-point source pollution, comprising: S1, the band of remote sensing image is fused, the multispectral image of study basin is generated, and the multispectral image is preprocessed and classified, to obtain the land use spatial distribution map of study basin, the land use spatial distribution map includes land use spatial distribution data;S2, calculate the influence factor related to soil erosion;And calculate the soil erosion modulus of study basin, and divide soil erosion grade according to soil erosion modulus;S3, calculate the landscape space load ratio index;S4, the land use spatial distribution map, the landscape space load ratio index, the soil erosion grade is standardized and spatial superposition analysis, to identify the key source area of non-point source pollution.The application can improve the accuracy of identifying pollution key source area, thereby providing technical support for agricultural non-point source pollution control and environmental protection.

The invention belongs to the technical field of agricultural non-point source pollution treatment and water body environment restoration, and particularly relates to a carbon-nitrogen-phosphorus synergistic purification system for polder area farmland water recession ditches and application of the carbon-nitrogen-phosphorus synergistic purification system. The system comprises a floatable photocatalytic water purification net and a modular purification box, the water purification net is composed of a polylactic acid / graphite phase carbon nitride modified polyurethane porous fiber sponge, and primary purification of nitrogen, phosphorus and organic pollutants in a water body is achieved through an adsorption-photocatalysis synergistic effect; a plurality of reaction chambers connected in series are constructed in the purification box through slope type choked flow baffles, and each reaction chamber is filled with a light composite adsorption filler taking polyethyleneimine modified loofah sponge-zeolite as a core, so that deep removal of nitrogen, phosphorus and organic pollutants is realized. According to the invention, a floating and modular unit is constructed by using a light functional material, and efficient and synchronous removal of carbon, nitrogen and phosphorus is realized through the cooperation of photocatalytic oxidation and specific adsorption on the premise of ensuring the drainage safety of the ditch.

The present application relates to the technical field of agricultural environment monitoring, and discloses a livestock and poultry manure field returning excessive judgment system based on environmental safety, which firstly collects basic data such as farmland soil nutrients, soil structure, meteorological conditions, groundwater depth, terrain slope, crop demand and manure nutrients, and carries out spatial gridding modeling on the farmland area; on this basis, the soil nutrient carrying capacity of each grid unit, the manure nutrient input and the crop nutrient absorption capacity are evaluated, and the nutrient diffusion risk index is calculated in combination with environmental factors such as rainfall, slope and groundwater depth; further, the manure safe application threshold and the excessive index are calculated by comprehensively considering the above parameters, so as to judge whether the manure field returning exceeds the environmental safety range, and output the risk early warning and application control suggestion. The present application can realize fine monitoring and dynamic management of the livestock and poultry manure field returning process, improve the resource utilization efficiency of manure, and reduce the risk of agricultural non-point source pollution.

The invention belongs to the technical field of agricultural microorganism development and application industry, and particularly relates to a high-temperature-resistant cronobacter sakazakii strain with cellulose degradation capacity and application. According to the specific technical scheme, the high-temperature-resistant cronobacter sakazakii strain with the cellulose degradation capacity is named as cronobacter sakazakii, and the 16S rRNA nucleotide sequence of the cronobacter sakazakii strain is as shown in SEQ ID NO: 1; the strain is preserved in the China General Microbiological Culture Collection Center (CGMCC), the preservation number is CGMCC No.33826, and the preservation date is March 14, 2025. The Cronobacter sakazakii disclosed by the invention can be used for efficiently degrading cellulose, hemicellulose and acidic detergent lignin, and a new solution is provided for the feed pretreatment of straws and dregs, the solving of agricultural non-point source pollution caused by the straws and the acceleration of high-temperature composting. Moreover, the strain still keeps high enzymatic activity at a high temperature of 65 DEG C, so that the development of related products of a microbial agent of the strain is greatly facilitated, the application range of the strain is expanded, and the strain has a wide application prospect.

This invention belongs to the field of pollution control technology and discloses an intelligent natural recycling system for farmland irrigation, fertilization, drought prevention, and water-saving, comprising 15 core nodes. The connections between these 15 core nodes form a complete closed-loop system integrating biogas energy recycling, water and fertilizer purification recycling, and organic fertilizer preparation recycling. This invention realizes the resource utilization of organic waste, thoroughly controls agricultural non-point source pollution, fully recovers biogas for power generation, achieves clean energy self-sufficiency and grid connection, and converts biogas slurry and sludge into water-soluble fertilizer and organic fertilizer, replacing chemical fertilizers. The entire system operates in a closed loop, with no secondary pollution, saving water, increasing efficiency, and ensuring harvests and drought prevention.

The invention relates to a heterogeneous sensor-oriented agricultural non-point source pollution monitoring data fusion and quality control method. According to the method, firstly, heterogeneous monitoring data is subjected to standardization processing, a drainage basin agent model fusing a physical mechanism is constructed, and then a dynamic event graph describing a cross-domain causal relationship is established according to the drainage basin agent model; when it is detected that data is abnormal, the system performs reverse traceability through the atlas and drives the agent model to generate a theoretical expected value, and logic consistency verification is performed through comparison so as to distinguish a real pollution event from a sensor fault; for the data judged to be faulty, an optimization model fused with physical constraints is further established and solved, and a self-consistent repair value conforming to a pollution transmission rule is generated, so that quality control normal form transformation from isolated threshold judgment to cross-domain logic verification is realized; the accuracy of complex pollution event identification, the reliability of sensor fault diagnosis and the physical rationality of an abnormal data restoration result are remarkably improved.

This invention relates to a composite microbial agent for the remediation of hexavalent chromium pollution and its application, belonging to the field of environmental engineering technology. The composite microbial agent for hexavalent chromium pollution remediation includes anaerobic bacteria, aerobic bacteria, heavy metal bacteria, and a carbon source. This composite microbial agent can maintain high activity in the actual complex environment of groundwater with low temperature and low nutrients, rapidly reducing hexavalent chromium to low-toxicity, low-migration trivalent chromium, achieving efficient removal of hexavalent chromium. The in-situ remediation method for hexavalent chromium-contaminated groundwater of this invention can be widely applied in environmental engineering fields such as industrial site pollution remediation, mine wastewater treatment, and agricultural non-point source pollution remediation, and is particularly suitable for in-situ injection-enhanced natural attenuation groundwater remediation processes.

The invention relates to the technical field of watershed hydrology and water quality simulation and agricultural non-point source pollution control, and discloses a watershed fertilization management-oriented SWAT multi-scenario automatic construction and evaluation method, which comprises the following steps of: establishing an SWAT reference model for a target watershed, constructing multiple groups of fertilization scenarios for target crops in a parameter configuration table manner, and establishing an SWAT reference model for the target watershed; and respectively operating multiple groups of fertilization scenarios on the SWAT reference model to simulate fertilization to obtain simulation data of each group of fertilization scenarios, further analyzing to obtain evaluation index data of each group of fertilization scenarios, comprehensively evaluating the multiple groups of fertilization scenarios, and screening out an optimal fertilization scenario for a target crop. According to the method, automatic construction and batch simulation of a fertilization scene are realized in a parameterized and templated manner, a multi-index automatic evaluation system covering water quality, yield and fertilization input is established, and the efficiency and scientificity of watershed agricultural non-point source pollution control and fertilization management optimization research are remarkably improved.

The application discloses a light-controlled oxidation-reduction dual-mode biochar and application of the biochar in construction of a self-purification biological buffer zone, and belongs to the field of environmental functional materials and agricultural non-point source pollution control technology. The application takes biomass resource utilization as a channel, and prepares a light-controlled oxidation-reduction dual-mode biochar by co-pyrolysis of a semiconductor material precursor and biomass rich in nitrogen / sulfur through a one-step pyrolysis method. The prepared biochar utilizes photo-generated holes to oxidize and degrade organic pollutants and nitrate ammonia nitrogen into nitrate nitrogen under daytime light, and stores photo-generated electrons in doped sites of the biochar skeleton at the same time. The stored electrons are released to reduce nitrate nitrogen into nitrogen in situ at night. The dual-mode biochar is used as a core functional filler to construct a self-purification biological buffer zone, and efficient and synergistic removal of nitrogen and phosphorus pollutants and pesticides is realized by utilizing natural day and night alternation, and the buffer zone is endowed with continuous self-purification capacity, so that the risk of saturation of traditional fillers and secondary pollution is solved.

The application discloses a kind of agricultural non-point source pollution load evaluation method, device and medium based on water quality monitoring, and is related to agricultural non-point source detection field, wherein, method includes: according to hydrology water quality monitoring data, the sampling days of each target pollutant are estimated, the daily load data corresponding to the estimated minimum sampling days is posterior stratification, and the annual load of each target pollutant in each stratification is estimated by applying ratio method, and finally the annual total load of each target pollutant is obtained.In the application, the minimum sampling days is obtained by estimating the sampling days, which reduces the number of samples involved in pollution load calculation, improves the calculation efficiency, and uses ratio method to estimate pollution load, which ensures the accuracy of load estimation value under the premise of relatively high efficiency.