85 results about "Cyanobacterial bloom" patented technology

The invention relates to the technical field of data processing, and discloses an intelligent monitoring method and system for cyanobacterial bloom outbreak. The method comprises the following steps: collecting a water surface spectrum and underwater particle size data, carrying out atmospheric correction, calculating a normalized algae index and a blue-green wave band ratio, inputting the normalized algae index and the blue-green wave band ratio into a U-Net network to obtain a water bloom coverage area, carrying out integral interpolation on the particle size data to obtain a vertical section distribution curve, and calculating a surface layer enrichment degree and a floating trend index, and establishing a water surface-underwater association relationship through random forest regression training, and inputting the multi-dimensional features into a CNN-LSTM model to predict a water bloom outbreak probability and determine an early warning level. According to the method, the problem that the cyanobacterial bloom three-dimensional structure cannot be comprehensively described due to the lack of effective fusion of the water surface spectral data and the underwater vertical section data is solved, the problem that the early warning timeliness of cyanobacterial bloom outbreak is insufficient due to the lack of a multi-source data time sequence analysis model is solved, and the spatial integrity and early warning advance of cyanobacterial bloom monitoring are improved.

The invention relates to the technical field of remote sensing monitoring, and discloses a lake cyanobacterial bloom detection method and system fused with a remote sensing image. The method comprises the following steps: acquiring a multispectral remote sensing image and a synthetic aperture radar image of a target lake; calculating a phycocyanobilin characteristic index and a chlorophyll fluorescence peak index according to the characteristic wave band reflectivity, and screening pixels meeting discrimination conditions to obtain an optical water bloom distribution mask; calculating a radar inversion phycocyanobilin index through a nonlinear regression model according to the dual-polarization backscattering coefficient to obtain a radar water bloom distribution mask; and fusing the double masks to obtain a cyanobacterial bloom monitoring result. The method solves the problems that an existing cyanobacterial bloom detection method cannot realize all-weather monitoring, lacks cyanobacterial specific recognition capability and is insufficient in reliability of a single data source, and improves the timeliness, accuracy and reliability of cyanobacterial bloom detection.

A lake cyanobacterial bloom pixel level prediction method based on multi-source data fusion belongs to the technical field of algae prediction, and comprises the following steps: collecting lake pixel level multi-source basic data in a satellite image and carrying out preprocessing, calculating an algae index to generate a binary distribution product, carrying out space-time matching according to a zoning factor suitability parameter table, and carrying out prediction according to the zoning factor suitability parameter table. Inverting a blue-green algae proliferation rate and adjusting a factor weight; calculating a pixel comprehensive suitability degree; identifying a hysteresis effect factor through correlation analysis and causal test; screening a high impact factor through feature sorting, constructing a diffusion rule, extracting an initial water bloom pixel and determining a diffusion starting point; and constructing a neighborhood iterative diffusion model by using the space-time dynamic pixel-level suitability matrix, and iteratively simulating and outputting a pixel-level water bloom prediction map. According to the method, through multi-source pixel-level data standardization processing and partition threshold modeling, the coupling diffusion model is optimized in combination with the multi-source data, accurate water bloom prediction is achieved, and the space-time precision and practicability of pixel-level prediction are improved.

The invention discloses a lake cyanobacterial bloom intelligent early warning method based on unmanned aerial vehicle remote sensing and image recognition, and the method comprises the steps: fusing an unmanned aerial vehicle multispectral image and a convolutional neural network, extracting the spectral features of cyanobacteria, and calculating the concentration distribution; image registration and a dynamic model are combined to track water bloom boundary change and drift trajectory, satellite remote sensing is used to verify precision and invert biomass density, early warning levels are divided according to the precision and the biomass density, decision information is generated, and intelligent monitoring and accurate early warning of cyanobacterial bloom are realized. The comprehensive technical effects of water bloom dynamic monitoring, accurate early warning and efficient management are achieved, and a scientific basis is provided for water environment treatment.

The invention discloses a lake and reservoir dominant algae community structure prediction method and system based on machine learning and a storage medium, and relates to the technical field of water environment monitoring and ecological prediction. Comprising the following steps that multi-source heterogeneous spatio-temporal data are obtained and fused, and the multi-source heterogeneous spatio-temporal data are historical time sequence data of a target water area; generating a feature vector from the fused multi-source heterogeneous spatio-temporal data; constructing a multi-output regression machine learning model, and inputting the feature vector into the multi-output regression machine learning model for training to obtain a multi-output prediction model; and inputting real-time monitoring data into the multi-output prediction model to generate a prediction result of a future dominant algae community structure. According to the method, whether cyanobacterial bloom or diatom bloom exists in the future can be clearly early warned, so that a manager can take targeted measures, for example, a specific algicide or ultrasonic equipment is used for the cyanobacteria, blind pesticide application is avoided, and the cost and the secondary pollution risk are reduced.

The invention relates to a cyanobacterial bloom remote sensing recognition system based on a multi-source satellite and intelligent threshold correction, and the system comprises an intelligent image retrieval and screening module which is used for calling a multi-source image according to a daily frequency / weekly frequency period and generating a candidate set; the water body mask and preprocessing module is used for cloud removal, cutting, water body extraction and non-target plaque removal; the water bloom index and threshold value module is used for automatically calculating an ABDI or FAI index according to an image source and carrying out peak height proportion threshold value segmentation; the pattern spot extraction and clustering module is used for extracting algal bloom patches, merging pattern spots and removing small patches; and the standardized product generating and pushing module is used for generating and pushing grids, vectors, daily frequency brief reports and weekly frequency thematic reports. According to the invention, daily frequency / weekly frequency automatic and intelligent identification and achievement business output of cyanobacterial blooms can be realized, and the precision and continuity of remote sensing monitoring are significantly improved.

The invention relates to a cyanobacterial bloom analysis method based on a 720-degree panoramic photo, and belongs to the technical field of image processing. According to the method, shooting is carried out right above a cyanobacterial bloom distribution center point to obtain a 720-degree panoramic photo, the 720-degree panoramic photo is unfolded in a plane coordinate mode to carry out direction calibration, then a coordinate orientation grid is established, cyanobacterial blooms are identified, position statistics is carried out, and finally the cyanobacterial bloom area is calculated. The 720-degree panoramic picture is adopted for analysis, and the height angle is the lowest, so that the area calculation error is small, and the precision is high. And the efficiency of single investigation and analysis can be greatly improved.

The invention discloses a blue-green algae identification and quantification method and device based on unmanned aerial vehicle remote sensing images and deep learning and a medium, and relates to the technical field of information data processing. Combining meteorological data and water quality monitoring data to construct an adaptive dynamic environment algorithm to extract EXIF metadata including camera parameters and attitude angle information, and establishing a geometric projection model to perform coarse orthographic correction on an original aerial image; the method comprises the following steps: extracting a multi-scale cyanobacterial bloom image feature map by stages based on a ResNet architecture and in combination with a feature pyramid network FPN fused with an attention mechanism, and obtaining an instance mask of cyanobacterial bloom through an anchor-free region proposal network, ROI Align and a head network; based on an improved GIS space projection and deep learning algorithm, carrying out high-precision area measurement and calculation on a binary mask image converted from the instance mask; according to the method, the influence of irrelevant interference on blue-green algae identification can be reduced, and the accuracy and comparability of blue-green algae identification and area calculation are improved.

The cyanobacterial bloom salvaging device comprises a rubber boat, the top of the rubber boat is fixedly connected with a sewage collecting pool, the rear side of the sewage collecting pool is fixedly connected with a lifting mechanism, the top of the front side of the lifting mechanism is fixedly connected with an air flotation machine, and the air flotation machine is fixedly connected with a water outlet of the air flotation machine. A slag scraping plate is fixedly connected to the top of the air flotation machine, a shovel plate is fixedly connected to the front side of the top of the sewage collection tank, a traction rope roller is arranged in the middle of the top of the rear side of the sewage collection tank, and a positioning mechanism is fixedly connected to the middle of the rear side of the sewage collection tank; by arranging the rubber boat, the sewage collection tank, the air flotation machine, the slag scraping plate, the shovel plate, the traction rope roller and the positioning mechanism, efficient salvage and collection of cyanobacterial blooms are achieved; an operator only needs to float the whole device on the surface of a water pool through a rubber boat, and cyanobacterial blooms are conveyed into a sewage collection pool through a shovel plate and separated through an air flotation machine.

The invention belongs to the technical field of biology, and particularly relates to a method for increasing the fucoxanthine accumulation amount by using microcystis subjected to depolymerization treatment to feed palmarthria formosana. According to the method, microcystis subjected to depolymerization treatment are added in the culture process of the palmitothecium for heterotrophic culture, meanwhile, continuous inflation is conducted, the microcystis subjected to depolymerization treatment are swallowed by the palmitothecium, and the higher fucoxanthine accumulation amount in the palmitothecium is obtained by means of the culture mode. The experiment proves that after the microcystis is subjected to pretreatment and depolymerization, the removal efficiency of the microcystis is higher by the brown algae, the limitation of treatment of harmful cyanobacteria and ingestion of protozoa is made up, and meanwhile, an integrated solution is provided for biological treatment of cyanobacterial bloom and resource utilization of the microalgae; meanwhile, a new way is provided for obtaining fucoxanthine with higher accumulation amount.

This application relates to the field of aquatic environmental pollution monitoring technology, specifically disclosing a method for extracting the area of ​​cyanobacterial blooms in lakes. The method utilizes remote sensing data to calculate the FAI index and abundance value of the monitoring area. Based on slope and statistical analysis, the FAI threshold is determined, yielding the area and spatial distribution of cyanobacterial blooms in the study area based on FAI. The F(S)-L method is used to determine the threshold for extracting cyanobacterial blooms based on abundance, obtaining the area and spatial distribution of cyanobacterial blooms in the study area based on mixed pixel decomposition. A comparative analysis of the results of cyanobacterial bloom extraction using mixed pixel decomposition and FAI shows that the overlapping areas extracted by the two methods represent the true cyanobacterial bloom regions, thus obtaining the area and spatial distribution of cyanobacterial blooms in the study area. This method solves the problem of difficulty in determining the abundance threshold, thereby improving the accuracy of cyanobacterial bloom extraction, and also has the advantages of being rapid, objective, and easy to promote.

The invention discloses intelligent blue-green algae outbreak emergency treatment equipment and method, and belongs to the technical field of water treatment equipment.The intelligent blue-green algae outbreak emergency treatment equipment comprises a water pumping mechanism installed on a buoyancy base, and further comprises a conveying and filtering mechanism, a collecting mechanism, a drainage mechanism, a chemical adding mechanism and a transmission mechanism. According to the intelligent blue-green algae outbreak emergency treatment equipment, the single motor drives the transverse rod to rotate, then the spiral blades are synchronously driven to convey blue-green algae, the transmission mechanism drives the extrusion assembly and the chemical adding mechanism to operate, multi-link cooperation of blue-green algae conveying, dehydration and chemical adding can be achieved, a traditional framework of respective driving of multiple motors is replaced, and the practicability is high. And the equipment complexity is reduced, the energy consumption is reduced, the fault rate of a motor is also reduced, and meanwhile, all links are synchronously linked, so that the process blockage caused by lagging of a single link can be avoided, and the overall processing efficiency is improved.

The invention discloses a compound microbial agent and application thereof in prevention and control of cyanobacterial bloom, two algicidal bacteria are obtained through screening, the preservation number is CCTCC NO: M 2024698, and the preservation number is CCTCC NO: M 2024699, and the compound microbial agent is proved to have obvious inhibition effects on a plurality of cyanobacteria bacteria such as microcystis aeruginosa, lacustrine triphora, anabaena and cylindrocystis, and can be used for preventing and controlling cyanobacteria bloom. And the composite bacterial agent combined by the two algicidal bacteria has a remarkable algicidal effect on algal blooms in natural water areas, can be applied to the field of biological prevention and control of freshwater cyanobacterial blooms, and provides an ideal choice for treatment of cyanobacterial blooms in water bodies.

The present application relates to a kind of preparation method of floating catalyst carbonized corncob load flower-shaped copper sulfide, through simple chemical precipitation method, in situ synthesis copper sulfide flower-shaped microspheres, and using the adhesion ability and chelating metal ion ability of polydopamine, copper sulfide is deposited on carbonized corncob, and constructs the photocatalytic efficiency high, reusable floating catalyst carbonized corncob load flower-shaped copper sulfide.The present application selects carbonized corncob as floating carrier, can achieve the effect of resource recycling, waste utilization, practices the concept of environment-friendly, sustainable development.And the synthesis method is simple and mild, solve the technical difficulty of traditional hydrothermal method high temperature and high pressure, low cost, high efficiency and economy.The prepared floating catalyst carbonized corncob load flower-shaped copper sulfide can efficiently remove Microcystis aeruginosa under visible light (λ≥420 nm) irradiation for 180 min, and has good stability, and has good application prospect in the treatment of cyanobacterial bloom.

The present application relates to a kind of blue-green algae bloom ground multispectral remote sensing monitoring system and method, to solve the technical problems such as low resolution and weather influence of satellite remote sensing to inland lake blue-green algae bloom monitoring frequency low, this system Ground multispectral remote sensing observation subsystem includes electric control box, ground support, setting on two-dimensional turntable of ground support and blue-green algae bloom multispectral camera fixedly set on two-dimensional turntable;Blue-green algae bloom multispectral camera contains at least 4 spectral bands;Ground multispectral remote sensing service subsystem includes control acquisition module and data processing analysis module.The method includes calibration to blue-green algae bloom multispectral camera, start ground multispectral remote sensing monitoring system;Record the multispectral image of multiple angles of entire lake area;Multispectral image data analysis extraction;With the change trend of satellite remote sensing data comparison;Repeat the operation of recording multispectral image, according to the result of comparative analysis gives blue-green algae bloom warning.

The invention relates to the technical field of environment monitoring, in particular to a Taihu lake cyanobacterial bloom extraction method based on sentinel No.2 images. The method comprises the following steps: S1, obtaining and preprocessing remote sensing data: correcting by using a Sen2Cor plug-in to obtain L2A-level data, and re-sampling waveband data to 10m through SNAP software; s2, water area contour extraction: according to the multispectral remote sensing data in the step S1, respectively calculating NDWI of each group of data, and according to a threshold value, completely excluding a land part to obtain a Taihu Lake water area range mask to be applied to subsequent cutting; and S3, contour extraction of cyanobacterial bloom: calculating the NDVI of each group of data, wherein the extraction threshold value of the NDVI is-0.0693. The Taihu Lake and cyanobacterial bloom images obtained according to the method have good consistency with field sampling data, and can be subsequently used for visual evaluation of the Taihu Lake cyanobacterial bloom.

The application discloses a material for treating water bloom by a photocatalytic method, a preparation method and application of the material, and the preparation method comprises the following steps: adding bismuth nitrate, iron nitrate and polydiallyldimethylammonium chloride into ethylene glycol, heating and reacting, and the reaction condition is that the ethylene glycol is refluxed and heated at 150-200 DEG C for 2-6 hours; after cooling, centrifugation and washing are carried out, the obtained precipitate is dried, and the obtained material is Fe-doped BiOCl, namely Fe-BiOCl; wherein the adding ratio of the bismuth nitrate, the iron nitrate, the polydiallyldimethylammonium chloride and the ethylene glycol is 60-100 mg: 30-50 mg: 3-6 mL: 60-100 mL. The application provides a preparation method of the functional material Fe-BiOCl for treating water bloom, and the functional material prepared by the method can effectively inhibit the formation of algae under the photocatalytic action, and is especially suitable for treating blue-green algae bloom.

The present application relates to blue-green algae bloom control technical field, disclose a kind of sodium percarbonate combined with EM bacteria reinforced severe blue-green algae bloom control method, the present application uses sodium percarbonate combined with EM bacteria to control severe blue-green algae bloom, on the basis of adding sodium percarbonate 5mg / L further add EM bacteria 0.075mg / L, the algal cell density of experimental group is always lower than the control group of simply adding sodium percarbonate, and after adding sodium percarbonate 6h immediately further add EM bacteria, and the reducing effect is most remarkable, it shows that EM bacteria has the effect of reinforcing the effect of sodium percarbonate to control algae, and it is best to add EM bacteria after adding sodium percarbonate 6h, in the experimental group of adding EM bacteria 6h, algal cell density removal rate is 94.19% when experimental duration=48h, and the algal cell density removal rate of control group of only adding sodium percarbonate is only 69.77%.

The invention relates to a cyanobacterial bloom extraction method based on spectrum and phenological characteristics, and relates to the field of ecology, and the method comprises the steps: selecting a vegetation index PCI which is excellent in cyanobacterial bloom recognition, building a localized phycocyanobilin inversion model, and carrying out the homogeneity test of pixels around a sampling point; by calculating a PCI gradient image time sequence, cyanobacterial bloom and background water boundaries are identified, and a threshold value for distinguishing cyanobacteria and non-cyanobacteria pixels is determined by using a maximum gradient average value; constructing a cyanobacterial bloom recognition model based on the LSTM neural network; calculating cyanobacterial bloom outbreak intensity and coverage area, identifying a hot spot area and a cold spot area, and depicting distribution characteristics of cyanobacterial bloom in space; a PCI time sequence data set is synthesized, the evolution trend of a cyanobacterial bloom key phenological index time sequence is described, the innovation of the method lies in that spectrum and phenological characteristics are fused, cyanobacterial bloom spatial and temporal distribution is accurately analyzed, and guarantee is provided for water environment treatment and drinking water safety.

The invention relates to the technical field of environment monitoring, in particular to a method for observing the temporal and spatial change rule of cyanobacterial bloom in the Taihu Lake based on a Sentinel-2 remote sensing image. The method comprises the following steps: S1, obtaining remote sensing data: obtaining a remote sensing image of Sentinel-2 and multispectral remote sensing data corresponding to the remote sensing image; s2, contour extraction of a water area: calculating to obtain a Taihu Lake water area range mask according to the multispectral remote sensing data in the step S1; s3, division of a Taihu Lake water area observation area: dividing the Taihu Lake water area contour obtained in the step S2 into seven areas; s4, extracting the contour of the cyanobacterial bloom: calculating the intensity and range of the cyanobacterial bloom according to the multispectral remote sensing data in the step S1; and S5, observing the temporal and spatial change rule of cyanobacterial bloom: analyzing the spatial change characteristics of the cyanobacterial bloom in the Taihu Lake according to the result obtained in the step S4. By analyzing the remote sensing image of the existing Sentinel-2 and the multispectral remote sensing data corresponding to the remote sensing image, the change rule of the cyanobacterial bloom in the Taihu Lake can be conveniently summarized and evaluated.

The embodiment of the invention discloses a multi-time-scale prediction method and system for cyanobacterial bloom, and the method comprises the steps: obtaining a cyanobacterial bloom spatial-temporal distribution prediction result through a pre-constructed hydrodynamic water quality bloom model, and obtaining a cyanobacterial bloom spatial-temporal distribution prediction result through a pre-constructed prediction model based on data driving based on a current chlorophyll a concentration sequence. Obtaining a chlorophyll a concentration prediction value sequence, and finally generating cyanobacterial bloom prediction information of the first time scale. And based on weather forecast data, obtaining a chlorophyll a concentration predicted value of a second time scale through a hydrodynamic water quality and water bloom model. Based on the historical environment monitoring data, through a pre-constructed multivariate statistical regression model, obtaining a cyanobacterial bloom intensity index; based on a historical chlorophyll a concentration monitoring sequence, a cyanobacterial bloom prediction result of a third time scale is finally obtained by analyzing a chlorophyll a concentration periodic change rule; the predicted periods of the first time scale, the second time scale and the third time scale are increased in sequence.

The invention relates to the technical field of cyanobacterial bloom treatment, and discloses a composite slow-release algal-inhibiting colloid and a preparation method and application thereof.The composite slow-release algal-inhibiting colloid comprises phenolic acid algal-inhibiting active substances, chitosan, polyvinylpyrrolidone and lactic acid, the average hydrodynamic particle size of the composite slow-release algal-inhibiting colloid is 50-800 nm, and the average hydrodynamic particle size of the composite slow-release algal-inhibiting colloid is 100-200 nm. The phenolic acid algal inhibition active substance is selected from one or more of gallic acid, pyrogallic acid and p-hydroxybenzoic acid. Targeted enrichment of algae is achieved through the electrostatic adsorption effect between positive charges of a chitosan molecular chain and negative charges on the surface of cyanobacteria cells; meanwhile, a three-dimensional network structure jointly constructed by the chitosan and the polyvinylpyrrolidone wraps the active substances, long-acting slow release is achieved, the colloid has the dual functions of targeted adsorption and long-acting slow release, and the utilization efficiency and action durability of the algal inhibition active substances are improved.

The application discloses a method for synthetically determining water bloom prevention and treatment measures according to total phosphorus and suspended matter thresholds, and comprises the following steps: measuring total phosphorus concentration I and suspended matter concentration I of eutrophic water, then implementing algae control measures, carrying out water-algae separation, measuring total phosphorus concentration II and suspended matter concentration II of the separated water; calculating total phosphorus removal rate and suspended matter removal rate according to total phosphorus concentration I and total phosphorus concentration II, and suspended matter concentration I and suspended matter concentration II; carrying out function fitting on total phosphorus removal rate and total phosphorus concentration I, and carrying out function fitting on suspended matter removal rate and suspended matter concentration I; determining total phosphorus threshold and suspended matter threshold according to total phosphorus and suspended matter fitting curve formula; and comparing total phosphorus concentration I with the total phosphorus threshold, comparing suspended matter concentration I with the suspended matter threshold, and taking corresponding prevention and treatment measures. The application prevents lake blue-green algae water bloom by controlling total phosphorus concentration, and effectively guarantees lake water ecological environment quality.

The invention relates to the technical field of electronics, and discloses a mobile variable-water-depth cyanobacterial bloom monitoring and early warning system, method and device, and the system comprises a mobile monitoring device, a control module, and a data collection and analysis module. The control module is connected with the mobile monitoring equipment and used for controlling the mobile monitoring equipment to collect water quality data, meteorological data and water surface image data of a plurality of monitoring areas in the target water body, and each monitoring area is provided with at least one monitoring point in advance; and the data collection and analysis module is connected with the mobile monitoring equipment, and is used for determining algae density prediction data of the corresponding monitoring area based on the water quality data, the meteorological data and the water surface image data of each monitoring area, and generating water bloom early warning information of the corresponding monitoring area based on the algae density prediction data of each monitoring area. The algal bloom early warning information of the corresponding monitoring area is generated by analyzing the algal density prediction data, so that the early warning accuracy and timeliness are improved, and the harm caused by cyanobacterial bloom is reduced.

The application relates to the technical field of remote sensing monitoring, and discloses a lake cyanobacterial bloom detection method and system fusing remote sensing images. The method comprises the following steps: acquiring multispectral remote sensing images and synthetic aperture radar images of a target lake; calculating phycocyanobilin characteristic indexes and chlorophyll fluorescence peak indexes according to characteristic band reflectivity, screening pixels meeting a discrimination condition to obtain an optical water bloom distribution mask; calculating a radar-retrieved phycocyanobilin index according to a dual-polarization backscattering coefficient through a nonlinear regression model to obtain a radar water bloom distribution mask; and fusing the two masks to obtain a cyanobacterial bloom monitoring result. The application solves the problems that the existing cyanobacterial bloom detection method cannot realize all-weather monitoring, lacks cyanobacterial specificity recognition capability, and has insufficient reliability of a single data source, and improves the timeliness, accuracy and reliability of cyanobacterial bloom detection.

The present application belongs to the technical field of algae removal, and particularly relates to a belt type biological filter-feeding device for removing planktonic algae, which comprises a rope body, a plurality of floats arranged on the rope body and floating in a water body, a plurality of biological bins arranged on the rope body, the biological bins being internally provided with filter-feeding organisms and being in communication with the external water body, and a collection bin arranged at the lower end of the biological bin and in communication with the lower end of the biological bin. The belt type biological filter-feeding device for removing planktonic algae is suitable for use in a near-shore area where algae blooms are accumulated due to water flow, wind or other reasons. The filter-feeding effect of the filter-feeding organisms is utilized to filter algae in water. Blue algae which are difficult to digest and utilize can be gathered to form algae groups in the form of pseudo-feces through the filtering effect. The pseudo-feces and excrement of the filter-feeding organisms are deposited into the collection bin under the action of gravity. The concentrated algae in the collection bin are collected periodically, so that the number of algae in water is reduced, and the occurrence of blue algae blooms is controlled.

The invention belongs to the technical field of biological coal bed gas, and particularly relates to a method for regulating and controlling a co-fermentation anaerobic system to increase yield of biogas. The method comprises the following steps: mixing cyanobacteria liquid, pulverized coal, a methanogenic inorganic salt culture medium and a sludge inoculum to obtain a co-fermentation system; and mixing the bacteriophage enrichment liquid and the Escherichia coli liquid according to a ratio that the infection complex number MOI is 1 or 10, adding the mixture into a co-fermentation system, and culturing under an anaerobic condition until the biogas yield is stable. The T4 bacteriophage is used for accurately regulating and controlling the flora, optimizing the methane production metabolic pathway and remarkably improving the biogas yield, and the T4 bacteriophage has the advantages of being environmentally friendly, low in cost and free of high-energy-consumption equipment or strong acid and strong alkali, and can be used for coal mine biogas yield increase and cyanobacterial bloom resource treatment.

The present application relates to the technical field of recurrent neural network prediction, in particular to a watershed blue-green algae bloom evolution prediction method and system based on improved PredRNN. The specific implementation process comprises: constructing the spatio-temporal feature sequence of the watershed; in the PredRNN, the spatial position migration is extracted by using the flow field flow velocity vector, the distribution intensity fluctuation is extracted by using the environmental factor, and the mixed hidden state is generated by feature recoupling; based on the cross-step history recall mechanism, the historical evolution trend item is retrieved from the watershed historical evolution library, the mixed hidden state is information compensated through the memory enhancement channel, and the water bloom evolution distribution field of the future period is output. Through the fusion of hydrodynamic constraint, environmental modulation mechanism and historical memory enhancement, the present application effectively improves the problem of insufficient description of migration mechanism in water bloom prediction, long-time sequence prediction easy to blur and distorted, and improves the spatial retention and time stability of watershed blue-green algae bloom evolution prediction.

1. Name of the product in this design: Algae Controller (Ultrasonic). 2. Application of this design: This design is for the prevention and control of cyanobacterial blooms in lakes, reservoirs, rivers and other water bodies. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention discloses algicidal bacteria TH41 and application thereof in inhibiting cyanobacterial bloom, and belongs to the technical field of biology. The algicidal bacterium TH41 is identified as bacillus pumilus TH41 and is preserved in the Guangdong Microbial Culture Collection Center, and the preservation number of the algicidal bacterium TH41 is GDMCC No: 66948. The invention also provides an algicidal bacterial agent containing the algicidal bacteria TH41. The invention further provides application of the algicidal bacterium TH41 or the algicidal fungicide in inhibiting cyanobacterial bloom. The algicidal bacterium TH41 has a degradation effect on harmful blue-green algae, has an efficient blue-green algae inhibition effect, has biological safety on daphnia magna and zebra fish in an algae killing concentration range, is suitable for preventing and treating various blue-green algae such as microcystis aeruginosa, cuscuta larakii, pichia mold and anabaena pseudosciaena, and has a wide application prospect.