5336 results about "Water sample" patented technology

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The invention provides a river pollutant traceability method and a river pollutant traceability system. The method comprises the following steps: constructing a potential pollution source feature fingerprint database fused with an LSTM time sequence feature extraction model, carrying out abnormal water quality fingerprint identification on a monitored river reach, if identification is abnormal, collecting an upstream water sample, detecting to obtain a water quality fingerprint, comparing the water quality fingerprint with the abnormal water quality fingerprint, determining a target river reach according to a comparison result, and determining the target river reach according to the comparison result. The method comprises the following steps: sampling all enterprises of a target river reach in real time, comparing detection result data with detection result data of an abnormal water sample, determining potential pollution sources according to a comparison result, determining high-matching candidate sources from the potential pollution sources by utilizing an LSTM (Long Short Term Memory) time sequence feature extraction model, carrying out space transition verification on the high-matching candidate sources, and carrying out space transition verification on the high-matching candidate sources. And determining the pollution source according to the verification result. According to the method, the accuracy, efficiency and result reliability of tracing the river pollutants can be effectively improved, and the scenes of multi-source pollution, intermittent emission and the like of complex rivers can be effectively handled.

The invention relates to the technical field of water level surveying devices, and discloses a hydrogeological multi-layer underground water level surveying device and a surveying method.The hydrogeological multi-layer underground water level surveying device comprises a support and a water sampling barrel, the support is provided with a winding mechanism, and the winding mechanism is used for adjusting the sampling height of the water sampling barrel; the upper part of one side of the water sample sampling barrel is communicated with a liquid inlet pipe, and the bottom of the water sample sampling barrel is fixedly connected with a balancing weight. In the sampling process, large-particle impurities in water are blocked through the filter screen, the impact force of water flow can be converted into the rotating force of the blades, the rotating shaft and the scraping rod, the function of automatically cleaning the impurities in the sampling process is achieved, and the rope winding condition caused by uncontrollable winding position is prevented through the adjusting mechanism; the dustproof mechanism prevents dust and stones from falling into the hydrological hole to affect sampling of a water sample in the surveying process, and the highest water level in the hydrological hole can be accurately known through the water level monitoring mechanism.

Disclosed are an intelligent simulation device for bottom sediment pollution process and control as well as an experimental method. The device includes an experimental flume to which a water inlet tank and a water return tank are connected; a wave-making system, an illumination system, a dosing system and an aeration system; an environmental condition parameter online monitor capable of determining water environmental parameters online; an online water quality index analyzer for monitoring water quality indexes in real time; a water automatic sampling device for automatically collecting water samples in a single or cycle mode; an offline analyzer capable of determining water quality indexes of the collected water samples or physical-chemical indexes of sediments; and an automatic control module for automatically controlling various devices. Further disclosed is an experimental method based on the intelligent simulation device for bottom sediment pollution process and control.

The invention belongs to the technical field of water pollutant traceability, and particularly discloses a water quality fingerprint database analysis method based on feature recognition, which relates to the field of water pollutant traceability, and comprises the following steps: cross-comparing feature curved surface information of different upstream and downstream under feature peak whole database data and sorting to obtain pollutant features under different intensities; the pollution source type is identified according to the pollutant difference; sorting the characteristic curved surface information of the water body samples reflecting different nodes, calling a chemical characteristic analysis result, outputting a chemical characteristic sequence, and selecting a first sequence sampling point position of the chemical characteristic sequence corresponding to the spectral characteristics of the identified pollution source type as a pollution source; according to the method, whether the identification result is met or not is analyzed according to the biological characteristics of the pollution source, efficient source tracing is carried out on water pollutants, an accurate pollutant transmission path is output, meanwhile, the corresponding pollutant type is evaluated, the corresponding pollutant diffusion trend is given, and powerful data is provided for follow-up pollutant treatment.

The invention provides a water quality heavy metal pollution detection method and system based on Raman spectrum. The method comprises the following steps: collecting a water sample through a water area to be detected, and scanning the water sample by adopting a Raman spectrometer to generate an original Raman spectrogram; based on the original Raman spectrogram, using a wavelet transform algorithm to perform de-noising processing, reducing background interference, using a principal component analysis technology to extract characteristic peaks, and generating a heavy metal preliminary prediction result; based on the preliminary heavy metal prediction result, constructing a heavy metal concentration prediction model by applying a partial least squares regression algorithm, performing quantitative analysis, evaluating prediction accuracy by adopting a cross validation technology, and generating a heavy metal actual concentration result; and based on the actual heavy metal concentration result, comparing with a water quality safety standard, evaluating a pollution condition, and generating a water quality heavy metal pollution detection report. The technical scheme provided by the invention has high sensitivity, can efficiently denoise and accurately predict, and provides a scientific means for monitoring and treating heavy metal pollution of water.

The invention relates to the technical field of optical line protection, and discloses a river water quality monitoring method based on an unmanned aerial vehicle hyperspectral remote sensing image and machine learning, which combines the unmanned aerial vehicle hyperspectral remote sensing image with a machine learning algorithm to construct a river water quality parameter inversion model. Comprising the following steps: collecting a water sample, obtaining an unmanned aerial vehicle hyperspectral image and preprocessing; extracting an image of the river part and selecting the reflectivity of each wave band of the image; performing spectrum transformation on the original spectrum of the image, establishing an inversion data set through feature screening, and constructing a water quality parameter inversion model by using a machine learning algorithm; and simulating the water quality parameters of the river through the water quality parameter inversion model, and visualizing the simulation result. According to the method, urban inland small river water quality monitoring can be rapidly achieved at low cost, the dual problem that the time resolution and the space resolution are limited in urban small river monitoring based on satellite remote sensing images is solved, and a scientific basis is provided for urban river intelligent inversion.

The invention provides a method for predicting the relative abundance of antibiotic resistance genes in surface water and application. The method comprises the following steps: acquiring ARGs relative abundance, water quality physicochemical indexes and genus level bacteria relative abundance of a water sample to be detected, and judging potential bacterial hosts of ARGs by Spearman correlation; the method comprises the following steps: taking water quality physicochemical indexes and relative abundance of potential bacterial hosts as characteristic variables, and respectively taking relative abundance of multidrug ARGs and total ARGs as target variables; adopting automatic machine learning to screen an optimal algorithm; determining an optimal feature set through feature importance ranking and model comparison; and establishing an optimal prediction model to predict the relative abundance of the multi-drug ARGs and the total ARGs of the water sample to be detected. According to the method, the water environment ARGs are predicted based on environmental factors and bacterial indexes, the model accuracy is high, and main driving factors and potential bacterial hosts influencing propagation and proliferation of the ARGs can be identified through interpretable analysis between features and target variables.

The invention provides a lake water chemical oxygen demand internal and external source pollution quantitative tracing method and system, and relates to the technical field of pollution quantitative tracing. The method comprises the following steps: performing three-dimensional fluorescence spectrum analysis on water samples at different point positions of a lake to obtain fluorescence excitation / emission matrix spectrum EEMS data; performing parallel factor analysis on the EEMS data, identifying and classifying the fluorescent components of the dissolved organic matter DOM, and determining the type characteristics of each component; based on the maximum fluorescence intensity and the corresponding COD value of the fluorescence component, establishing a standardized multiple linear regression equation by adopting ridge regression analysis, and calculating the contribution percentage of each fluorescence component to the COD of the lake water body; analyzing influence paths of potential variables on DOM migration and transformation, and quantifying direct contributions and indirect contributions of different pollution sources to each fluorescent component through path coefficients; and calculating the total contribution of lake-entering rivers, bottom mud release and phytoplankton to the COD of the lake water body.

The invention discloses a river water ecological health monitoring method and a river water ecological health monitoring system, relates to the technical field of ecological health monitoring, and aims to solve the problem that a traditional water quality monitoring method mainly depends on water sample collection and laboratory analysis, and judges the water quality by measuring indexes such as dissolved oxygen, pH value, ammonia nitrogen, total phosphorus, heavy metal and dissolved organic matters in water; the river runoff is calculated from the precipitation and the drainage basin area, and the monitoring points are set in combination with the environmental information, so that an accurate data basis can be provided for subsequent water quality health assessment. The water quality condition is predicted by utilizing the water flow speed and the pollution point discharge amount and then compared with an actual monitoring result, so that potential problems can be found in time and a monitoring strategy can be optimized.

The invention relates to the technical field of water quality pollution detection, in particular to a water quality pollution rapid detection method driven by a quantum sensing technology. A quantum sensor array is deployed in a water area to be detected, and quantum signal response data of the water area is collected; constructing a pollutant quantum recognition model, and inputting quantum signal response data into the model to obtain an initial predicted value of pollutant concentration; generating an initial detection parameter of the quantum detection instrument based on the initial predicted value, executing primary pollution detection by the instrument according to the parameter, and collecting primary deviation data of an actual detection value and an expected detection value; determining a detection error according to the deviation data, further correcting the initial detection parameter, and generating an optimized detection parameter; and finally, the instrument performs secondary pollution detection based on the optimized detection parameters. According to the method, complex water sample pretreatment is not needed, water quality pollution detection can be rapidly and accurately completed, detection requirements of different water areas are met, and the detection efficiency and accuracy are improved.

The invention discloses an aquatic organism diversity rapid evaluation system and method based on GIS and eDNA technologies, and the method comprises the steps: selecting a plurality of sampling points in a target region to collect water samples, and integrating and processing the geographic information data of the sampling points and surrounding regions by adopting a GIS system; extracting eDNA from the collected water sample, performing amplification and sequencing on the eDNA by adopting a high-throughput sequencing technology, obtaining species and relative abundance of the species existing at the sampling point, and forming a species list; importing species distribution information corresponding to the species list into a GIS system, and obtaining a species distribution area and species types; according to the method, a species distribution prediction model is established, aquatic organism diversity change trends of the hot spot area and the potential ecological threat area are monitored in real time, an evaluation report and protection suggestions are formed, and protection measures are updated in time, so that the data acquisition and processing efficiency is improved, and the accuracy of species identification and the comprehensiveness of diversity evaluation are enhanced; and a real-time monitoring and early warning mechanism is provided.

The invention relates to the field of water resource quality detection, in particular to a sampling device for water resource quality detection. The invention provides a water resource quality detection sampling device which comprises a sampling barrel, a barrel cover is arranged at an opening of the sampling barrel, clamping seats are symmetrically distributed on one side, close to the barrel cover, of the sampling barrel, clamping pins are arranged in the clamping seats, the barrel cover is locked through cooperation of the clamping pins and the clamping seats, and the sampling barrel is connected with the clamping seats. A plurality of sampling box bodies for containing water samples are vertically arranged in the sampling barrel, a water pump is arranged in the sampling barrel, and a water inlet pipe of the water pump extends to the outer side of the sampling barrel. The stratified sampling box body and the independent flow guide assembly are combined with the servo motor to drive the staggered box cover, so that accurate stratified collection of water samples at different depths is realized, and mixed pollution is avoided; a water flow switching assembly is additionally arranged, a pipeline is automatically flushed after sampling, a residual water sample is discharged into a liquid storage box, cross contamination is reduced, independence and representativeness of the water sample are guaranteed, and detection accuracy is improved.

The invention belongs to the technical field of evaluation, development and research of oil and gas reservoirs, and discloses a T2 cutoff value calculation method based on a saturated nuclear magnetic resonance experiment. The method comprises the following steps: acquiring a saturated / bound water nuclear magnetic resonance T2 spectrum curve of a compact sandstone sample; determining a T2 cut-off value based on a saturated / bound water nuclear magnetic resonance accumulative porosity curve, and recording the T2 cut-off value as T2-Cuff; acquiring a logT2-logphi intersection curve of the saturated nuclear magnetic resonance T2 spectrum, and recording a T2 value corresponding to an inflection point of the curve as T2-Log; and determining a mathematical relationship between the T2-Log and the T2-Cuff, and establishing a T2 cut-off value calculation model based on the saturated nuclear magnetic resonance experiment. According to the method, the T2 cutoff value can be calculated only by performing the nuclear magnetic resonance experiment on the saturated water sample and performing mathematical treatment on the T2 spectrum, and the method has the advantages of being economical, simple, efficient and high in practicability.

The invention relates to the technical field of water quality detection, and discloses a water quality detection method and device based on an electrochemical sensor. The method comprises the following steps: deploying a multi-depth electrochemical sensor array in a target water body according to different water depth positions and carrying out real-time monitoring to obtain electrochemical response signal data; performing electrochemical fingerprint feature recognition on the electrochemical response signal data to obtain electrochemical feature vectors of water sample pollutants at different water depth positions; carrying out pollutant analysis through a hierarchical electrochemical transfer-attention network model to obtain types and concentrations of heavy metal ions and organic pollutants in water samples at different water depth positions; and executing Kriging space interpolation and environmental factor correction to generate a three-dimensional pollutant distribution dynamic map of the target water body. According to the method, high-precision identification of low-concentration multi-component coexisting pollutants is realized, and visual analysis of spatial distribution characteristics and migration rules of water pollutants is realized.

The invention relates to the technical field of water quality detection, and discloses a water quality sampling monitoring method and system for an intelligent water station based on ultraviolet spectrum, and the method comprises the steps: carrying out the regional division of the intelligent water station, and obtaining a plurality of water areas; performing water quality analysis according to the ultraviolet spectrum data of the water sample at the central sampling point of each water area to obtain a normal water area and an abnormal water area; performing water quality analysis on all sampling point water samples in the abnormal water area to obtain pollution source sampling points; the intelligent water station is subjected to regional treatment, so that the water sample collection quantity is reduced, and the water quality detection process is accelerated; different water quality analysis methods are adopted in different water quality analysis stages, dynamic adjustment of the analysis process is achieved, a sampling point closest to a pollution source is determined, and water station water quality treatment is facilitated; the model parameters of the water quality detection model are optimized by using a multi-objective optimization method, so that local optimum is effectively avoided when a multi-output objective problem is processed, and the accuracy of a water quality detection result is improved.

The invention particularly relates to a water pollution intelligent traceability system based on a three-dimensional fluorescence spectrum, which relates to the technical field of environmental monitoring, and comprises a water sample collection and three-dimensional fluorescence data acquisition module, a data preprocessing and PARAFAC component decomposition module, a multi-source pollution characteristic fingerprint database module and an intelligent comparison and pollution source analysis module. According to the method, standard acquisition and preprocessing are adopted, and the original data quality is ensured by means of scattering rejection, instrument correction and the like; pure fluorescence components are decomposed through a PARAFAC algorithm, and feature extraction reliability is guaranteed through triple verification. In the comparison link, spectrum similarity, concentration proportion difference and space-time hydrological constraint multi-round screening are adopted, and irrelevant pollution sources are removed; and then the contribution proportion is quantified, and Monte Carlo simulation, water quality and specific pollutant cross validation are carried out, so that the crossing from suspected tracing to quantitative responsibility investigation is realized.

The invention relates to the technical field of drinking water safety monitoring, and discloses a rural drinking water safety monitoring method, which comprises the following steps: S1, water sample collection; s2, monitoring a water sample; s3, data acquisition and transmission; s4, data processing and analysis; s5, early warning; s6, water quality reporting, water quality safety of rural drinking water sources and water delivery pipe networks is ensured by monitoring and evaluating water quality parameters in real time, potential water quality problems can be found and dealt with in time through regular and instant monitoring, health risks caused by water quality pollution are reduced, automatic and continuous water quality monitoring and data transmission are achieved, and the water quality monitoring efficiency is improved. The frequency of manual sampling and inspection is reduced, the monitoring efficiency is greatly improved, real-time collection and analysis of data also shorten the problem discovery and response time, the response speed is improved, and a scientific basis is provided for water quality management and decision making through comprehensive water quality index CWQI calculation and water quality report generation. A decision maker can analyze according to data and trends in the report.

The invention discloses a flocculation treatment device and method for removing high turbidity of a water sample. The method comprises the following steps: monitoring an inflow turbidity parameter in real time, continuously collecting original optical characteristic data of water through an optical sensor array, and calculating a turbidity fluctuation rate parameter after noise reduction treatment; carrying out graded rotational flow mixing treatment, forming a pressure gradient through three stages of tapered rotational flow pipes in sequence, activating an ultrasonic frequency field, and synchronously adding main and auxiliary flocculants; the method comprises the following steps: introducing a water sample into a multi-stage gradient flocculation reaction zone, and sequentially executing turbulent flow enhanced flocculation, slow stirring flocculation and pulsed electric field assisted flocculation to form a floc structure with different particle size distribution; running parameters of a sedimentation module are adjusted according to real-time effluent turbidity feedback, and the inclination angle of an inclined plate assembly and the opening degree of a mud discharging valve are dynamically adjusted; a parameter set is updated through a prediction model based on periodically collected system operation data, a closed-loop optimization control strategy is formed, the adaptability to extreme turbidity is enhanced, the solid-liquid separation efficiency is improved, the overall energy consumption is reduced, and the efficient and stable requirements of emergency treatment are met.

The invention relates to the technical field of intelligent monitoring, in particular to an underwater robot monitoring device and method based on muon imaging and navigation positioning, and the device comprises a transmission and control subsystem which is used for driving an underwater robot to complete a target action task in an underwater pipeline; the muon imaging positioning subsystem is used for acquiring high-energy imaging information and a three-dimensional coordinate position of the underwater robot so as to assist the underwater robot in completing a target action task; the underwater scanning, monitoring and early warning subsystem is used for evaluating a water sample of the underwater pipeline to generate a water quality evaluation report and acquiring surrounding terrain and geological feature information of the underwater pipeline to generate an underwater three-dimensional image; and the multi-source data fusion transmission base station is used for fusing the water quality evaluation report, the high-energy imaging information and the underwater three-dimensional image to generate a state evaluation report. Therefore, the problems of insufficient penetrating power, low resolution, signal interference and the like of the existing underwater monitoring technology and the like under the conditions of deep water, high turbidity or complex terrains are solved.

The present invention discloses an automatic water quality monitoring system with an intelligent operation and maintenance mode, and relates to the technical field of water quality monitoring. It includes a water sample acquisition unit, a water quality detection unit, a cleaning unit and an operation and maintenance control unit, wherein the operation and maintenance control unit controls the cleaning unit to clean the water sample acquisition unit and the water quality detection unit; the water sample acquisition unit includes a water pump and a water sample tank, and the water sample tank is used to hold the sewage sample sucked by the water pump; a drain port is provided at the bottom of the water sample tank; the water quality detection unit is connected to the water sample tank through a pipeline main pipe; the cleaning unit includes a first cleaning component and a second cleaning component, and the operation and maintenance control unit obtains the dirt conditions of the inner wall of the water sample tank and the pipeline main pipe through a sensor, and controls the cleaning unit to clean the water sample acquisition unit and the water quality detection unit. The present invention realizes the automatic cleaning of pipeline pollutants and the intelligent management of monitoring data, thereby improving the monitoring accuracy and reducing the operation and maintenance costs.

The invention discloses a water quality detection and evaluation method and system for environmental engineering, and relates to the technical field of environmental engineering. The method comprises the following steps: collecting and detecting an environmental engineering target water sample to obtain concentration data of various pollutants; constructing a pollutant collaborative influence matrix, calculating a collaborative index of the influence of each pollutant on the overall water quality, and generating a comprehensive pollution collaborative score; obtaining a water body function type of the target water sample, performing water body function matching judgment on the target water sample, and outputting a function adaptability grade; collecting a pollutant concentration change sequence in a historical period of time, and performing time sequence analysis on the concentration of each pollutant to obtain a predicted pollution trend; and dynamically adjusting the comprehensive pollution collaborative score and the functional adaptability grade to obtain a dynamic standard evaluation result of the target water sample. According to the method, comprehensive dynamic evaluation on the pollution status, functional adaptability and future trend of the target water sample is realized, and the scientificity and timeliness of water quality evaluation are remarkably improved.

The invention discloses an optical dissolved oxygen sensor calibration method based on nonlinear temperature compensation, and belongs to the field of sensor calibration, and the method comprises the following steps: S1, building a calibration platform; s2, data acquisition: under a plurality of temperature gradients, generating a dissolved oxygen saturated water sample through nitrogen-oxygen mixed gas, and synchronously acquiring fluorescence lifetime and influence factors; s3, establishing a nonlinear compensation model of the fluorescence lifetime and the temperature, and optimizing model parameters through a Levenberg-Marquardt algorithm; s4, dynamically allocating a weight coefficient; and S5, predicting the drift distance of the optical dissolved oxygen sensor to be calibrated, and realizing closed-loop self-maintenance calibration. By adopting the optical dissolved oxygen sensor calibration method based on nonlinear temperature compensation, not only is the influence of temperature on the optical dissolved oxygen sensor considered, but also multiple environmental factors such as salinity and pressure are incorporated, and the calibration accuracy and comprehensiveness are improved through multi-parameter collaborative correction.

The invention relates to the technical field of data processing evaluation, in particular to a water ecological health evaluation method based on fish environment DNA experiment big data. The method comprises the following steps: acquiring a water sample in a target area; filtering the water sample in the target area to generate water sample filtering data; performing water centrifugation on the target area water sample to generate water centrifugation data; performing fish environment DNA extraction on the target area water sample based on the water sample filtering data and the water body centrifugation data to obtain area fish environment DNA data; performing target DNA fragment determination on the regional fish environment DNA data to obtain target DNA fragment information; through a data processing technology, a high-throughput sequencing technology and a machine learning algorithm, flow parameter water level correlation analysis is carried out on a specific water body area, and index determination is carried out in combination with a fish community structure, so that the accuracy of water ecological health assessment is improved.

The invention relates to a method for predicting river nitrogen metabolism gene abundance and key influence factors thereof based on automatic machine learning. Comprising the following steps: collecting a river water sample, detecting water quality physicochemical indexes, and performing metagenome sequencing to obtain nitrogen metabolism gene abundance; taking conventional water quality physicochemical indexes as explanatory variables, taking nitrogen metabolism gene abundance as a target variable, adopting automatic machine learning to construct a model, evaluating the performance of the model through a mean square error (MSE) and a fitting coefficient (R), and selecting an optimal algorithm for prediction; the model analyzes the relative contribution of each water quality index through an SHAP value graph, and reveals the relationship between each water quality index and gene abundance by using a partial dependency graph (PDP). The method shows high precision and good generalization performance in the aspect of predicting the abundance of the nitrogen metabolism gene, and is suitable for describing the nitrogen dynamic process of a river water body. The model can explain, analyze and quantify the influence of different water quality indexes on the nitrogen metabolism gene afterwards, and a scientific basis is provided for river water quality management and nitrogen metabolism optimization regulation and control.

The present invention discloses a three-dimensional fluorescence portable water quality analyzer for pollution component determination and source tracing, and relates to the technical field of water quality analysis, the analyzer comprises the following components: a sample collection and processing module for collecting a water sample from a to-be-detected water body, filtering to remove impurities, and diluting the water sample according to a self-adaptive dilution multiple algorithm; fluorescence intensity information of a water sample under different excitation wavelengths and emission wavelengths is obtained through the three-dimensional fluorescence detection module, rich three-dimensional fluorescence spectrum data is formed, the real-time fluorescence lifetime imaging module is introduced, and by measuring the fluorescence lifetime of a fluorescent substance and utilizing the principle that different fluorescent substances have different fluorescence lifetime characteristics, the real-time fluorescence lifetime of the water sample is obtained. Various pollution components in the water sample are further distinguished and recognized, the pollution components can be accurately distinguished through fluorescence lifetime measurement and imaging, the accuracy of pollution component judgment is greatly improved, and a reliable basis is provided for accurate treatment of water quality pollution.

The invention relates to the technical field of data processing, and provides a water quality detection method, device and equipment and a storage medium, and the method comprises the following steps: obtaining the temperature and turbidity of a specific water sample, carrying out standardization treatment on the temperature to obtain a standardized temperature, analyzing the standardized temperature and the turbidity, obtaining long-term water quality change prediction, and carrying out data driving simulation. The method comprises the following steps: obtaining a simulated water quality change path and expected environmental influence, adjusting temperature by utilizing the simulated water quality change path to obtain a temperature adjusting scheme, optimizing turbidity by utilizing the expected environmental influence to obtain a turbidity optimization scheme, and combining the temperature adjusting scheme and the turbidity optimization scheme to obtain the turbidity optimization scheme. And obtaining a comprehensive water quality management scheme and generating a water quality maintenance report. Dynamic monitoring and accurate prediction are realized by using monitoring data of temperature and turbidity, and the problems of insufficient detection accuracy and prediction capability caused by incapability of effectively predicting and coping with a long-term water quality change trend when the water quality is detected are solved.

The invention relates to the technical field of deep-sea microorganism nucleic acid detection, in particular to a long-term experimental platform for deep-sea microorganism in-situ nucleic acid detection and a detection method. According to the invention, a water sample is subjected to tangential flow filtration and concentration through the filtration and sampling module, so that a concentrated microorganism sample is obtained. The method comprises the following steps of: transferring a sample into an amplification detection module under reduced pressure, transferring into a lysis purification module for cell lysis, injecting the cracked sample into a chromatographic column, filtering impurities and intercepting DNA by the chromatographic column, then washing by using an eluent to obtain a high-purity DNA sample, loading a suction head through a transfer washing liquid gun, mixing the high-purity DNA sample with an enzyme solution, adding into the amplification detection module for reaction, and detecting the DNA in the amplification detection module. And carrying out fluorescence labeling on the amplified gene, obtaining an amplification curve by using a fluorescence detector, and detecting the in-situ nucleic acid of the deep-sea microorganisms according to the change of the amplification curve. An automatic cleaning assembly is designed in the filtering and sampling module, and the cracking and purifying module is used for sampling and cleaning a cracking chamber and switching pipelines, so that cross contamination caused by deep sea in-situ multiple detection is prevented.

The present invention relates to the technical field of water pollution detection, and discloses an evaluation system and method for water sample detection, the system comprises: a sensor assembly including a water depth sensor and a water temperature sensor, the sensor assembly being arranged at different positions of a sampling ship rope; the control module is configured to collect water samples of different areas of the same horizontal plane and water areas of different depths of the same area, and detect and evaluate the water samples; wherein the control module comprises an acquisition unit, a detection unit, an adjustment unit and a grade determination unit. A detailed water quality analysis unit is provided, the detection unit can identify pollutant information in a water sample and comprehensively evaluate the pollution degree of the water sample in combination with PH value detection, the comprehensive evaluation value accurately reflects the health condition of a water area, the PH evaluation value is adjusted, the reliability of an evaluation result is enhanced, and the monitoring efficiency is improved; a scientific basis is provided for sustainable management of water resources, and protection of the ecological environment and safety of water quality are ensured.

The invention discloses a method for evaluating enhancement and release seedling resources based on environmental DNA polymerization analysis. The method comprises the following steps: carrying out gridding partition on a target water area, collecting a water sample through a designed sampling scheme, and carrying out DNA extraction and high-throughput sequencing to obtain species sequence information of each sampling point. Sequencing data is subjected to species identification by using a bioinformatics method, released species are identified, a spatial abundance model is established, and a preliminary distribution map is generated. And establishing a DNA degradation kinetic model in combination with water area environmental parameters, and carrying out reverse correction on abundance distribution. And through a resource inversion model coupled with hydrodynamics, analyzing biomass distribution characteristics and migration laws of the release group, and obtaining a resource evaluation result. And finally, a species environment preference model is constructed based on migration path analysis, an optimal release area is matched in a target water area, a scientific scheme including release point locations, opportunities and quantity is generated, and a whole-process technical support and a decision basis are provided for enhancement and release.