38 results about "Agricultural pollution" patented technology

The invention provides a method for preventing and controlling nitrogen and phosphorus loss of sandy and dry cultivated land based on EICP root reinforcement and relates to the field of soil ecological protection and agricultural pollution prevention and control. According to the method, a three-dimensional prevention and control system is formed from the two dimensions of surface layer film covering protection and deep root system soil fixation through the synergistic effect of EICP film covering and local plant root system three-dimensional reinforcement, wind erosion and water erosion are effectively resisted, the soil nitrogen and phosphorus loss rate of the large-gradient sandy and dry cultivated land is remarkably reduced, and meanwhile the soil desertification process is slowed down; the EICP film covering layer has good water permeability and moisture retention, nitrogen and phosphorus loss can be prevented, rainfall infiltration and soil moisture conservation can be guaranteed, and the germination rate and the growth speed of crops are increased; according to the method, local crop root system reinforcement is selected, the original planting structure is not disturbed, the economic benefit of cultivated land yield per mu is guaranteed, a harmless means of combining microorganisms, geotechnical engineering and agricultural planting is adopted, external pollution sources are not introduced, original basic characteristics of soil are not damaged, and the requirement for ecological protection of the Yellow River basin is met.

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 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 application discloses an agricultural water quality and water quantity dual risk and cascade transmission evaluation method, belongs to the technical field of water resource management, and aims at solving the problem that traditional methods only stay in water quantity depletion caused water resource pressure accounting and ignore the risk caused by substandard water quality; the application comprises the following steps: based on a farmland soil nitrogen budget and hydrodynamics coupling model, quantifying the pollution emission list of subdivided sources in the growth process of specific crops, simulating agricultural pollution dilution water consumption; using a crop water requirement model to calculate the irrigation water consumption of specific crops in the whole growth period; using a source and sink corrected physical flow trade model to analyze the virtual water transfer path hidden in each agricultural product trade link; integrating the production end and the consumption end results to realize high-precision grid agricultural water resource supply and demand imbalance risk evaluation and cascade effect analysis; and the cascade transmission effect of the application in evaluating the water resource risk provides strong support for reasonable allocation of agricultural water resources and improvement of nitrogen fertilizer utilization efficiency.

The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification. The application discloses a CPN multi-pollutant efficient degradation agricultural sewage combined grid coordination purification system and belongs to the technical field of sewage purification.

The application discloses an adaptive method for relieving double risks of water quality and water quantity of agriculture, and belongs to the technical field of water resource management.The method is based on a farmland soil nitrogen balance and hydrodynamics coupling model, quantifies a pollution emission list of subdivided sources in the growth process of specific crops, and simulates agricultural pollution dilution water quantity; a crop water requirement model is used to calculate irrigation water consumption of the specific crops in the whole growth period; a water resource loss evaluation module is established to evaluate potential agricultural yield reduction and economic loss caused by water resource shortage; a scenario library of water and fertilizer coordination strategies is constructed to compare the relieving effects of different adaptive strategies on water quantity depletion type and water quality pollution type water resource risks.The application solves the technical problem that it is difficult to simultaneously cope with water quantity risks and water quality risks to develop targeted adaptive strategies, can effectively relieve water resource pressure, improve the sustainability of agricultural production, realize optimal allocation of water resources, and further guarantee the health of an ecological system.

The utility model provides an unpowered ecological wetland small-sized agricultural pollutant treatment device which comprises a base, an agricultural pollutant flowing structure is arranged at the top of the base, an agricultural pollutant filtering structure is arranged in the agricultural pollutant flowing structure, and a filler body is arranged in the agricultural pollutant flowing structure. The agricultural sewage filtering device is reasonable in design, the agricultural sewage filtering structure can be separated from the filtering bin through the arranged agricultural sewage filtering structure capable of being lifted, then different filtering layers are directly pushed towards one side, the filtering layers can be rapidly replaced, and the situation that the filtering layers needing to be replaced can be replaced only by taking out the different filtering layers layer by layer is not needed.

The invention provides a preparation method of a CoO / CoP-LIG heterojunction electrolyzed water catalyst, and belongs to the technical field of preparation methods of electrocatalytic materials. CoO and CoP in the obtained electro-catalysis material are of a heterostructure, a large number of active interfaces and defect sites are exposed between the two components, and the electro-catalysis reaction is facilitated. The laser induced graphene (LIG) has excellent conductivity and huge specific surface area, and an ideal platform is provided for loading of CoO / CoP heterojunction nanosheets and construction of electron / mass transfer channels. The water electrolysis catalyst is simple in preparation process, high in stability, low in raw material price, easy to realize industrial mass production, and beneficial to realizing industrial development of hydrogen production by water electrolysis. The electrolyzed water catalyst can also be applied to degradation of urea in industrial and agricultural pollutants, and is an environment-friendly electrolyzed water catalyst.

The utility model is applicable to the technical field of agriculture, and provides an agricultural polluted soil remediation device which comprises a mounting frame, the first telescopic rod is fixedly mounted below the mounting frame, and a placement frame is fixedly mounted on an output shaft of the first telescopic rod; the soil turning frame is rotationally mounted on the placement frame and used for turning over agricultural contaminated soil, and a soil turning mechanism used for driving the soil turning frame to rotate to turn over the contaminated soil is arranged on the placement frame and the soil turning frame; the placement box is fixedly mounted on the mounting frame, the placement box is used for placing crop straw materials used for contaminated soil remediation, and a discharging hopper is fixedly mounted at the bottom of the placement box. According to the agricultural contaminated soil remediation device provided by the scheme, agricultural contaminated soil can be remedied, straw materials used for remediation can be well and uniformly sprayed on the contaminated soil, and the remediation efficiency of the contaminated soil is effectively improved.

Agricultural non-point source pollution is caused by runoff of fertilizers and pesticides in farmland, and especially the problem of water eutrophication caused by nitrogen and phosphorus pollution is serious. Traditional pollution control measures such as reduction of chemical fertilizer consumption and construction of physical isolation belts are limited in effect and high in cost. Nitrogen-fixing cyanobacteria can fix nitrogen in the atmosphere and absorb nitrogen in water, so that the nitrogen-fixing cyanobacteria is considered to be a potential natural agricultural pollution control tool. The invention aims to provide an agricultural non-point source pollution control system based on nitrogen-fixing cyanobacteria and an application method thereof, so as to efficiently replace part of chemical fertilizers, reduce agricultural non-point source pollution, improve soil fertility and promote healthy growth of crops.

The invention relates to the technical field of agricultural pollution treatment of saline-alkali soil, and provides a small farmland sewage treatment device, through the arrangement of an intelligent water inlet gate and an intelligent water outlet gate which are combined with a sensor, the pretreatment step of farmland sewage is omitted, the adaptability to extreme water quality can be ensured through intelligent regulation and control of an inlet and an outlet, and the operation is simple and convenient. The high-alkali and high-salt sewage is directly treated, the pretreatment cost is reduced, and the risk of secondary pollution is avoided to a certain extent; meanwhile, by utilizing a specific structured microorganism load and flow field environment, a commercially available composite microbial preparation is promoted to spontaneously form and maintain a functional complementary and metabolism coordinated efficient community in a single carrier, complex proportion regulation necessary for a traditional multi-strain system is avoided, and the technical threshold and the operation and maintenance cost are reduced.

The invention discloses a method for reducing perfluorooctanoic acid in crops by applying nitrate nitrogen fertilizer to competitively inhibit nitrate transporter protein, and relates to the technical field of agricultural pollutant control. Calcium nitrate Ca (NO3) 2 is used for providing 4-16 mmol / L or mmol / kg nitrate (NO3 <->) nitrogen fertilizer for lettuce planting under the water culture or soil culture condition; the transmembrane transport of nitrate transporter protein to perfluorooctanoic acid (PFOA) is competitively inhibited, and the accumulation amount of the edible part PFOA of the lettuce is reduced. By applying the nitrate nitrogen fertilizer, transmembrane absorption of NRT2.7 transport protein on PFOA is competitively inhibited, accumulation of PFOA in the lettuce is remarkably reduced, the food safety is improved, crop growth is synchronously promoted, and double benefits of pollution reduction and yield increase are achieved. The method is easy and convenient to operate, high in adaptability and suitable for water culture and soil culture conditions, and has the good popularization prospect and the cost advantage. The mechanism has universality in various crops and has wide extension application value.

The invention relates to the technical field of water and fertilizer all-in-one machine management and control, in particular to water and fertilizer all-in-one machine management and control equipment based on a crop growth model, which comprises an outer shell and a bottom frame body mounted on the bottom surface of the outer shell, a controller is mounted on the right side of the outer shell, and a fertilizer storage cavity and a water storage cavity are mounted in the upper surface of the outer shell in a penetrating manner; a mixing cavity is fixed in the lower surface of the outer shell in a penetrating manner, and the bottom surfaces of the fertilizer storage cavity and the water storage cavity are communicated with the interior of the upper surface of the mixing cavity through a discharging control pipe. The water and fertilizer all-in-one machine management and control equipment based on the crop growth model can automatically adjust the water and fertilizer proportion and the supply amount based on the crop growth model and the growth requirements of crops, achieves the purpose of precise irrigation and fertilization, and meanwhile, through combination and alternate irrigation of the drip irrigation pipe and the spraying pipe, not only improves the water and fertilizer utilization rate, but also improves the water and fertilizer utilization rate. Resource waste is reduced, the growth efficiency and quality of crops are remarkably improved, agricultural pollution is reduced, and the method conforms to the development concept of green agriculture.

The invention provides an agricultural polluted water treatment device and method, and relates to the technical field of sewage treatment.The agricultural polluted water treatment device comprises a first treatment pond, a second treatment pond, a third treatment pond, a top plate, a bearing plate, a first filter plate, a first spring, a sliding assembly, a rotating assembly and a stirring assembly; a water outlet is formed between the first treatment pond and the second treatment pond, a filtering assembly is arranged between the second treatment pond and the third treatment pond, the rotating assembly and the sliding assembly are connected with the bottom of a top plate arranged above, and the two ends of the rotating assembly are connected with a bearing plate and a filtering plate correspondingly; the bearing plate is connected with the bottom of the first treatment pond through a first spring, the rotating end of the rotating assembly is meshed with one end of the sliding assembly, the other end of the sliding assembly is connected with the stirring assembly, and the stirring assembly is used for stirring polluted water in the third treatment pond. According to the invention, the produced agricultural polluted water can be quickly and effectively treated, and the pollution of the polluted water to the surrounding environment is avoided.

The utility model provides a dual-mode agricultural sewage integrated treatment device, including a first dual-mode pool, a second dual-mode pool, an inclined plate sedimentation tank, an inner return pipe and an outer return pipe, the first dual-mode pool is provided with a water inlet, the inclined plate sedimentation tank is provided with a water outlet, the two ends of the inner return pipe are respectively located in the first dual-mode pool and the second dual-mode pool, and the two ends of the outer return pipe are respectively located in the inclined plate sedimentation tank and the first dual-mode pool. When the C / N (carbon-nitrogen ratio) of the agricultural sewage and domestic sewage inlet water quality is normal, the utility model adopts the AO process mode, when the C / N (carbon-nitrogen ratio) of the agricultural sewage and domestic sewage inlet water quality is unbalanced and the carbon source in the incoming water is insufficient, the OA process mode is adopted, and the aerobic pool in the front section can directly remove COD, TN, etc. in the water, avoiding the low efficiency operation caused by insufficient carbon source when the traditional front section is an anoxic pool, and the back section is treated in the anoxic pool and then refluxed into the front section aerobic pool, thereby improving the treatment efficiency, reducing energy consumption, avoiding the addition of external carbon source, and saving medicine consumption.

The invention discloses an agricultural pollution inspection management method and system based on big data analysis, and relates to image processing, and the method comprises the steps: collecting the hyperspectral image data and laser point cloud data of an agricultural pollution facility, and carrying out the denoising of the hyperspectral image data through employing an improved minimum noise separation transformation MNF algorithm, and obtaining a spectral characteristic wave band Z; the improved minimum noise separation transform MNF algorithm optimizes a noise covariance matrix by introducing correlation estimation between noise bands, optimizes an MNF transform process by using spatial information of hyperspectral image data, and classifies a spectral characteristic band Z by using a support vector machine (SVM) based on a kernel function. The material and the pollutant type of the agricultural pollution facility are obtained; according to the SVM based on the kernel function, an SVM classification result is optimized by setting a space regularization strategy based on a Markov random field (MRF) in SVM classification. In view of incomprehensive pollution information acquisition in agricultural pollution inspection, the application comprehensively evaluates the agricultural pollution information.

This application discloses a method and system for agricultural pollution inspection management based on big data analysis. The method involves image processing, including: collecting hyperspectral image data and laser point cloud data of agricultural pollution facilities; denoising the hyperspectral image data using an improved minimum noise factorization transform (MNF) algorithm to obtain a spectral feature band Z; the improved MNF algorithm optimizes the noise covariance matrix by introducing inter-band correlation estimation, and optimizes the MNF transformation process using the spatial information of the hyperspectral image data; classifying the spectral feature band Z using a kernel-based support vector machine (SVM) to determine the material and pollutant type of the agricultural pollution facility; and optimizing the SVM classification results by implementing a spatial regularization strategy based on a Markov random field (MRF) in the SVM classification. To address the incomplete acquisition of pollution information during agricultural pollution inspections, this application comprehensively assesses agricultural pollution information.

The invention relates to the technical field of plant cultivation, in particular to a cultivation method of cadmium-enriched potherb mustard suitable for being planted in winter in the north. The cultivation method comprises the steps of S1, preparation before planting, wherein land is leveled, and a test fertilizer is added into the soil; s2, soil microbiological treatment: one week before sowing, a fungicide and potassium fulvate are mixed and then applied to the soil; s3, sowing: during July to September, sowing is carried out in the morning or at dusk after raining, and the sowing amount per mu is 0.5 kg; wherein the test fertilizer comprises urea and calcium superphosphate; the fungicide is bacillus subtilis and trichoderma harzianum. The method is expected to provide a basic theoretical basis for repairing an agricultural Cd-polluted site by potherb mustard and provide a reference for a soil heavy metal phytoremediation technology.

The invention discloses agricultural non-point source pollution multi-stage treatment equipment and a treatment method, and relates to the technical field of agricultural pollution treatment. Comprising an interception ditch, an ecological purification module, a composite wetland module and a deep purification module, wherein the interception ditch is arranged at a to-be-restored farmland drainage outlet; through a four-stage treatment system of interception ditch pretreatment, adsorption and degradation of an ecological purification module, deep purification of a composite wetland module and precise separation of a deep treatment module, the synergistic effect of multiple processes such as physical interception, chemical adsorption, biodegradation and membrane separation is integrated, specifically, suspended solids are removed through a front-end interception ditch, pesticides are removed through the ecological purification module, and the treatment effect is achieved. Total nitrogen and total phosphorus are removed by the composite wetland module, and finally, after being treated by the MBR membrane tank, the wastewater comprehensively meets the farmland irrigation water quality standard, so that the problem that complex non-point source pollutants are not thoroughly removed by a traditional single treatment process is solved.

The invention relates to the technical field of information, and discloses an agricultural sewage treatment control method based on the Internet of Things, which comprises the following steps: acquiring sewage water quality data in different time periods and preprocessing the sewage water quality data to obtain standard water quality data; extracting time sequence data of the water quality indexes from the water quality indexes, and obtaining smoothed time sequence data by using a time sequence analysis method; according to the smoothed time sequence data, through a trained long-short-term memory neural network model, obtaining prediction data of a future time sequence of the water quality index; according to the prediction data, constructing an objective function of an optimization problem so as to establish a multi-objective optimization model; solving the multi-objective optimization model by adopting a particle swarm optimization algorithm to obtain an optimal combination of process parameters; and converting the optimal combination into a control instruction, issuing the control instruction to execution equipment of the sewage treatment system, and controlling the operation state of the execution equipment. According to the method, the process parameters can be adjusted in time, and the efficiency and the effect of agricultural pollution treatment are improved.

The invention discloses an air quality monitoring system and method based on deep learning, and relates to the technical field of air quality monitoring. According to the air quality monitoring system and method based on deep learning, a hardware-level encryption identifier and a federated learning architecture are adopted to ensure that sovereignty ownership is clear during data cross-border circulation, and ownership dispute caused by data format difference in a traditional scheme is avoided; the dual-channel analysis module fuses GAN spectral decomposition and morphological waveform detection, realizes precise separation of industrial / agricultural pollution sources in a single PM2.5 data stream, and reduces the misjudgment rate; the dynamic weight distributor is combined with terrain correction parameters, so that the monitoring network automatically optimizes space coverage in a complicated border landform, and the equipment blind area is reduced compared with a fixed station layout; the differential privacy and gradient desensitization technology constructs multiple protections, and the data leakage risk is effectively controlled on the premise of keeping the model precision.

The invention discloses a method for predicting a heavy metal pollution source in soil, which comprises the following steps: collecting 0-20cm surface soil, and obtaining the heavy metal content of explained variable soil; respectively processing and quantifying the data of the explanatory variables of the pollution sources; the pollution sources comprise heavy industrial pollution sources, agricultural pollution sources, main road traffic pollution sources and natural pollution sources, and the natural pollution sources are from surface water, underground water, rainfall and dust fall; quantized data of all pollution sources serve as explanatory variables of agricultural land soil heavy metal content C and heavy metal to be added into a spatial measurement model, an inverse distance spatial weight matrix is adopted for analysis of heavy metal sources in small-size and regional-range point-shaped soil, and spatial dependency and heterogeneity inspection is conducted on the data. According to the method, heavy metals in soil in a certain area can be predicted according to the model, the prediction effect accords with the actual situation, and technical support is provided for local soil heavy metal pollution prevention and control, monitoring and early warning.

The present application relates to the field of non-point source pollution analysis and management technology, and specifically discloses a method for calculating the load of agricultural pollution sources entering water bodies based on data analysis. After calculating the pollutant influencing factors of multiple dimensions based on a variety of basic data of the area to be studied, it further introduces data analysis technology based on deep learning to semantically embed and encode the attribute descriptions and numerical values ​​of each pollutant influencing factor, so as to achieve a deep understanding of each pollutant influencing factor. Then, by performing semantic correlation interaction analysis on each pollutant influencing factor, the causal relationship and synergistic effect between the pollutant influencing factors are excavated, so as to more accurately estimate the number of water inflows and realize the accurate calculation of the load of agricultural pollution sources entering water bodies. In this way, the correlation between the various pollutant influencing factors can be comprehensively considered, the calculation accuracy of the load of agricultural pollution sources entering water bodies can be improved, and more scientific decision-making support can be provided for pollution control.

The invention discloses an agricultural non-point source pollution abatement monitoring and evaluation method based on an entropy weight comprehensive pollution index, and belongs to the field of agricultural pollution abatement. The method comprises the following steps: determining monitoring point positions, monitoring frequencies and monitoring indexes of each treatment project according to a monitoring thought of pollution source-conveying path-receiving water area; a single-factor evaluation method and a comprehensive pollution index method are adopted to perform quantitative analysis on the pollution control effect, and an entropy weight method is combined to calculate the pollution removal rate, so that the effect of the pollution control project is evaluated. The method can be used for various agricultural non-point source pollution treatment scenes such as livestock and poultry breeding pollution treatment and aquaculture pollution treatment, and the scientificity and accuracy of pollution treatment monitoring are improved.

The application discloses a kind of agricultural pollution source investigation method and system based on stratified random sampling, it is related to agricultural environmental monitoring technical field, which comprises: the planting production pollution load and livestock breeding production pollution load of target area are calculated respectively;Based on the planting production pollution load and livestock breeding production pollution load of target area, the pollution load grade of each to be investigated field plot and each to be investigated breeding farm in target area is determined;Load area grade is high load, medium load or low load;The minimum sample size sampling method is used to stratified sampling to the to be investigated field plot or to be investigated breeding farm under different pollution load grades, and the final sampling survey sample size of the to be investigated field plot and the final sampling survey sample size of to be investigated breeding farm under different pollution load grades are obtained;The stratified sampling includes: first-level stratified sampling and second-level stratified sampling.The application improves the accuracy and scientificity of agricultural pollution source investigation result.

The invention discloses a rural domestic sewage treatment effect image recognition and evaluation method, system and platform based on deep learning. The method comprises the following steps: constructing a problem picture data set corresponding to a treatment effect evaluation associated object; generating and acquiring first data corresponding to each associated object, labeling and processing a type label of a target object in the first data, and creating a corresponding training set and verification set; building an image recognition model based on deep learning, optimizing model parameters through the training set and the verification set, and generating second data corresponding to each associated object according to the image recognition model; performing scoring processing on the second data according to a preset score assignment rule, and generating third data corresponding to the second data; and the third data is evaluation treatment effect data integrating the scores of the associated objects, and a system and a platform corresponding to the method can solve the problems of high professional requirements of evaluation personnel, poor result consistency, low efficiency and high cost of an existing agricultural pollution effect evaluation mode.

An apparatus for detecting a substance comprising a direct analysis in real time apparatus; a neutral excluder; a mass spectrometer; and a vessel in. The apparatus may also comprise a separator, a gas, an alcohol, a filter, and a pump. The apparatus may also comprise electrodes in communication with the direct analysis in real time apparatus and the neutral excluder. A method for detecting a substance comprising contacting the substance with a direct analysis in real time apparatus ion stream; forming an ion and a neutral particle; flowing the ion and the neutral particle into a neutral excluder; contacting the ion and the neutral particle with a gas; and flowing the ion into a mass spectrometer.

The present application relates to a small watershed agricultural non-point source pollution intelligent monitoring and early warning method and system based on hyperspectral remote sensing, which solves the defect that it is difficult to real-time small watershed agricultural non-point source pollution intelligent monitoring and early warning compared with the prior art. The present application comprises the following steps: monitoring partition and control section layout of agricultural non-point source pollution; investigation and monitoring of small watershed water environment agricultural non-point source pollution background; construction of small watershed water environment hyperspectral remote sensing background database; small watershed agricultural non-point source pollution intelligent monitoring and early warning. The present application is used for monitoring the pollution situation and change trend of agricultural pollution source and receiving water body, understanding the spatio-temporal evolution law of small watershed agricultural non-point source pollution, realizing real-time dynamic monitoring and early warning of the influence of regional agricultural non-point source pollution on water environment quality, and providing basic support for agricultural non-point source pollution control.

The invention discloses a nitrogen and phosphorus vertical seepage barrier plate for a farmland in a karst region, and belongs to the technical field of agricultural pollution treatment. The barrier plate is formed by mixing three materials of biochar, sepiolite and quick lime according to different particle sizes and different proportions, three nitrogen and phosphorus vertical seepage barrier layers with different thicknesses from top to bottom and from coarse to fine are constructed, and nitrogen and phosphorus in soil can be prevented from flowing into a water source by compacting the barrier plate and placing the barrier plate below a farmland plowing layer in the karst region. The barrier material designed by the invention has good adsorption and barrier effects on nitrogen and phosphorus, does not cause pollution to soil, and can be used for a long time. After adsorption saturation, the barrier layer can be taken out, adsorbed nitrogen and phosphorus are desorbed, and the nitrogen and phosphorus can be used as a barrier material again subsequently; or the barrier layer subjected to saturated adsorption is taken out to serve as a nitrogen-phosphorus fertilizer and a carbon source to be applied to the plough layer, so that the fertility of the barren soil is increased, carbon sequestration is achieved, pollutants such as heavy metal and antibiotics in the plough layer are adsorbed, and the mobility of the pollutants is reduced.

The utility model discloses an agricultural pollution interception ecological ditch which comprises a ditch main body and two fixing frames, the two fixing frames are fixedly connected to the top end of the ditch main body and are symmetrically arranged on the front side and the rear side, threaded rods are fixedly connected to the middles of the close sides of the two fixing frames, guide rods are arranged on the two sides of the threaded rods, and the guide rods are fixedly connected to the two sides of the ditch main body. The front end and the rear end of the guide rod are fixedly connected to the corresponding fixing frames correspondingly, a connecting block is arranged in the ditch body, the transmission device is arranged at the top end of the connecting block and comprises a shell fixedly connected to the top end of the connecting block, and through holes are formed in the middles of the front end and the rear end of the shell correspondingly. An intercepting device is arranged at the bottom end of the connecting block. The device has the advantages that the intercepting device is arranged, dirt such as silt can be intercepted in a classified mode, and the intercepting effect is better; and the transmission device is arranged and can drive the intercepting device and the connecting block to reciprocate, and manual labor is reduced.