69084 results about "Environmental engineering" patented technology

The invention discloses an intelligent agricultural condition monitoring system and method for grain and oil crops, and relates to the technical field of agricultural condition monitoring. Farmland multi-source data are acquired and preprocessed in real time through a multi-source data acquisition module; multi-factor step-by-step fusion of farmland multi-source data is realized by using a D-S evidence theory through a multi-source data fusion module, and a multi-factor fusion evaluation index is formed; constructing a grain and oil crop environment-growth state comprehensive model based on LSTM through an environment state fusion module, and fusing the grain and oil crop environment-growth state comprehensive model with farmland multi-source data and multi-factor fusion evaluation indexes to obtain a farmland digital twin system; and a growth deviation index is analyzed and generated through the decision feedback optimization module and is fed back to the optimization system. The problems that in the prior art, data acquisition hysteresis is remarkable, multi-source heterogeneous information is isolated and difficult to fuse, and early warning fails due to lack of correlation between environment mutation and crop response are solved, and accurate monitoring and risk active intervention of grain and oil crops in the whole growth period are achieved.

The invention relates to the technical field of drainage basin water scheduling, and discloses a drainage basin water regulation and control optimization method based on ecological element changes. The method comprises the following steps: deploying a drainage basin monitoring system, and collecting ecological element real-time data such as a hydrological parameter sequence and a remote sensing image; after the data is cleaned and converted, hydrological trend features and spatial distribution features are extracted by adopting a feature learning model, and the hydrological trend features and the spatial distribution features are fused into unified ecological representation through a cross-modal alignment mechanism; inputting the unified ecological representation into a physically constrained neural network prediction model, and outputting a water regimen dynamic prediction value; and finally, based on the predicted value, a water resource regulation and control instruction is generated and executed by using a multi-objective decision algorithm so as to optimize the watershed water circulation process. According to the method, feature extraction comprehensiveness is improved through multi-source data fusion and cross-modal analysis, prediction reliability is enhanced in combination with physical constraints, reasonable allocation of water resources is achieved by means of multi-target decision, the ecological condition of a drainage basin can be improved, and the water utilization efficiency is improved.

The water tank assembly comprises a water tank body and a sealing side wall, the interior of the water tank body is hollow, a containing cavity is formed in the water tank body, the two ends of the water tank body are in a transverse semi-barrel shape, the middle of the water tank body is in a square column shape, and the middle of the upper portion of the water tank body is in a notch shape capable of containing a hinge head assembly to rotate. A water inlet is formed in the top wall of one end of the water tank body; a water outlet is formed in the middle of the lower part of the water tank body; the hinge head clamping cover body of the cleaning head can clamp the hinge assembly between the cleaning head shell body and the water tank body and between the cleaning head shell body and the hinge head clamping cover body through the connecting mechanism. The cleaning head comprises a cleaning head shell assembly, a cleaning roller, an extrusion roller and a water tank assembly, a driving motor is installed on the cleaning head shell assembly to drive the cleaning roller to rotate to wipe the floor, and a clean water outlet in the cleaning head shell assembly can spray out clean water to directly wash the surface of the cleaning roller.

The invention discloses a wetland ecological restoration dynamic monitoring method based on deep learning, and relates to the technical field of ecological restoration, and the method comprises the following steps: obtaining multi-source wetland ecological sensor data and remote sensing image flow in real time, constructing a space-time fusion data cube, and extracting an ecological feature tensor; performing degradation mode analysis on the ecological characteristic tensor, generating an ecological state dynamic topological graph, and calculating an ecological connectivity index; carrying out restoration demand identification based on the ecological connectivity index, positioning a degradation hot spot region through a multi-modal graph convolutional network, and generating a restoration priority region coordinate set; through multi-source data space-time fusion and deep crossing of deep learning and landscape ecology, a whole-process technical system from ecological state dynamic perception to restoration scheme intelligent optimization is constructed. The problems that in traditional wetland restoration, data scales are not matched, degradation area positioning is fuzzy, restoration path ecological adaptability is poor, and multi-target cooperation is difficult are effectively solved.

The present disclosure provides a landslide identification method, a device and a storage medium based on multi-path feature fusion, and relates to the field of geological hazard monitoring and early warning. The device and storage medium are used to implement the method. The beneficial effects of the present disclosure are as follows: a landslide identification method based on multi-path is provided, deep feature-level interaction among different types of landslide image data is achieved, high-resolution feature information is preserved, landslide identification accuracy is significantly improved, the computational costs are reduced, the real-time performance of landslide identification is significantly enhanced and the real-time monitoring and early warning are achieved.

The invention relates to the technical field of error correction, in particular to a water conservancy facility environment interference error correction method and device based on multi-dimensional data. The method comprises the following steps: collecting historical monitoring logs of water conservancy facilities, carrying out environmental disturbance event identification and multi-scale disturbance relevance mining, and constructing an environmental disturbance space-time relevance map; monitoring surrounding environment water monitoring parameters of the water conservancy facility, performing sequential response trend change analysis and dynamic response characteristic modeling, and constructing a facility environment personalized change response portrait; identifying a plurality of water body position monitoring data according to the surrounding environment water body monitoring parameters, and constructing a hydrodynamic full-field sensing graph; and performing nonlinear correlation analysis based on the hydrodynamic full-field perception graph and the personalized change response portrait of the facility environment, and constructing a digital twinborn model of the water conservancy facility under the water flowing condition. According to the invention, through dynamic error trend analysis and correction, the monitoring precision and monitoring stability of the water conservancy facility are improved.

The invention discloses an indoor water tank sediment starting speed measurement system and method, and aims to solve the technical problem that data accuracy is affected due to the fact that a sensor disturbs a flow field in an existing measurement method. The core of the technical scheme is that the non-contact measurement characteristic of the PIV technology is applied to the whole process from flow field construction to data acquisition. The device is mainly composed of an imaging unit, a laser lighting unit, a movable sliding frame, a water flow adjusting unit and a buffer plate. Optical measurement is carried out through the imaging unit and the laser illumination unit, a physical sensor does not need to be arranged in a flow field, and interference of a measuring instrument on a water flow structure and a sediment starting process is fundamentally avoided. The movable sliding frame which is integrally designed integrates the functions of sediment laying, particle throwing and measuring, so that a test area can be quickly positioned; and the buffer plate and the water inlet and drainage adjusting unit are combined, so that a gradually-changed flow field from weak to strong can be accurately and stably simulated.

A long-term fire retarding biochemical liquid composition including: a dispersing agent realized in the form of a major amount of water, for dispersing alkali metal ions dissolved in the water; a major amount of a first fire retarding agent realized in the form of a primary alkali metal salt of a nonpolymeric saturated carboxylic acid, for example, tripotassium citrate, for providing metal potassium ions dispersed in the water when the at least one alkali metal salt is dissolved in the water to form a mixed retardant solution; a minor amount of a second fire retarding agent realized in the form of a secondary alkali metal salt of a nonpolymeric saturated carboxylic acid, for example, potassium, sodium, calcium and / or magnesium benzoate, for providing benzoate ions dispersed in the water when the secondary alkali metal salt is dissolved in the mixed retardant solution, for functioning as a secondary fire retardant agent.

The invention relates to the technical field of industrial flue gas purification, and discloses a flue gas denitration pollution reduction and carbon reduction method and system based on model prediction control. The method comprises the following steps: collecting flue gas data through a sensor to obtain a flue gas distribution state; the state is processed through a preset model, and a nitrogen oxide concentration predicted value is determined; judging a regulation and control demand based on the predicted value and generating an adjustment coefficient sequence; calculating an opening value of an ammonia spraying distributor by adopting a particle swarm optimization algorithm, and determining ammonia spraying amount distribution; a control instruction is sent according to ammonia spraying amount distribution, and a temperature uniformity index is evaluated based on temperature feedback data; adjusting optimization algorithm parameters according to the indexes, and generating an optimized ammonia spraying strategy; updating the predicted value and determining the stable range of the denitration efficiency; verifying the ammonia escape concentration in the stable range to obtain a system performance index; and forming a continuous regulation and control sequence according to cyclic feedback of the indexes. According to the invention, accurate dynamic regulation and control of ammonia spraying amount are realized, denitration efficiency and system stability are effectively improved, and the risk of ammonia escape is significantly reduced.

The invention relates to the technical field of environmental governance and remediation, in particular to a combined contaminated site soil remediation data management method, which comprises the following steps of: firstly, integrating multi-source heterogeneous data through a unified space-time coordinate system to generate a fusion data pool, and then driving a pollution assessment model to generate a multi-dimensional space-time pollution map; and then intelligently matching a candidate repair process chain based on an associated knowledge base, performing iteration deduction through a dynamic multi-objective optimization engine to obtain an optimal repair scheme, converting the optimal repair scheme into a digital regulation and control instruction, and finally monitoring an execution state and environmental response data in real time and feeding back and updating a data pool to realize closed-loop optimization. According to the method, the data quality and the pollution evaluation accuracy are improved, the adaptability of the repair process and the cost performance of the scheme are optimized, the repair effect is ensured to be stable and reach the standard, and the efficiency and reliability of the repair project are improved.

The invention relates to the technical field of soil monitoring, in particular to a soil-groundwater pollution risk threshold dynamic adjustment method and system based on an environment model, and the method comprises the steps: collecting soil and groundwater monitoring data, constructing an environment model containing the soil pollution concentration, the groundwater pollution concentration and the pollutant migration rate, obtaining comprehensive pollution characteristic data, extracting main characteristics, and determining the contribution degree of each characteristic to risk assessment; calculating the initial weight of each feature according to the contribution degree, and obtaining a weight distribution scheme; calculating pollution risk values of the soil and the underground water in combination with the pollution load data and the weight values, and preliminarily setting a risk threshold value; monitoring pollutant concentration fluctuation data in real time, predicting a pollutant migration trend through a time sequence analysis algorithm, and obtaining a risk change prediction result; and combining the risk change prediction result and the environmental capacity constraint optimization risk threshold to obtain a dynamically adjusted risk threshold. According to the invention, accurate extraction of pollution characteristics and dynamic adjustment of weights are realized.

The invention discloses an offshore red tide multi-parameter real-time monitoring method and monitoring system based on a buoy array. The method comprises the following steps: S1, performing array deployment and topology configuration according to a sea area sensitivity degree, tide characteristics and a historical red tide trajectory; according to the invention, through risk differentiation buoy array deployment and redundancy topology, traditional isolated monitoring limitation is solved, and sea area full coverage and red tide diffusion tracking are realized; physical-chemical-biological multi-source sensing and in-situ detection are combined with data fusion, so that the problem of single parameter is solved, and the monitoring accuracy is improved; by means of liftable stratified sampling and in-situ algae species and toxicity analysis, the vertical monitoring blank is filled up, and the complete life cycle process of red tide from occurrence to regression is completely captured; through linkage of edge-cloud multi-model early warning and field equipment, a'monitoring-early warning-disposal 'closed loop is formed, and the red tide monitoring real-time performance and the emergency response capability are greatly improved.

The invention discloses an ecological restoration effect evaluation and simulation system after polluted soil restoration, and relates to the technical field of soil restoration, and the system comprises a soil feature generation module which generates an ecological feature data set; the ecological restoration evaluation module is used for establishing a multi-dimensional evaluation model by using an analytic hierarchy process and a fuzzy comprehensive evaluation method based on the ecological characteristic data set, and generating an ecological restoration effect index; the dynamic simulation prediction module is used for constructing an ecological restoration dynamic simulation model and simulating the evolution trend of a soil ecological system under different environment conditions; and the restoration strategy optimization module is used for generating a targeted ecological restoration optimization scheme by combining a preset restoration strategy library according to the ecological restoration effect index and the dynamic simulation prediction result. According to the method, a closed-loop system integrating multi-source data acquisition and processing, multi-dimensional evaluation, dynamic simulation prediction and stepped strategy optimization is constructed, and accurate evaluation of the ecological restoration effect after contaminated soil restoration and scientific optimization of the restoration strategy are achieved.

A regenerative filter that includes a filter housing having inlet and outlet zones; a fluid path provided between the inlet and outlet zones; a plurality of filter elements each having an outer surface filter media applied thereto and functioning to filter particulate or contaminants from the fluid path. The filter elements are disposed in an monolithic array. An inlet port arrangement is disposed at the filter housing leading to the inlet zone and is constructed and arranged to direct the fluid path into the filter housing in a manner so as to maintain a controlled turbulence at the inlet zone. The inlet port arrangement comprises a pair of inlet ports that are arranged in juxtaposition at the inlet zone and each having one end where the fluid flow enters. Embodiments that are considered as falling under the scope of the present invention include 1. Single inlet / two or more outlets; 2. Two or more inlets / single outlet, or 3. Two or more inlets and two or more outlets.

A direct air capture (DAC) system for capturing carbon dioxide (CO2) from a dilute gas source includes a gas-liquid contactor subsystem and a wash water regeneration subsystem. The gas-liquid contactor subsystem includes a capture section, a wash section, and at least one fan to produce a CO2-rich capture solution in the capture section and a used wash water stream in the wash section. The wash water regeneration subsystem is in fluid communication with the at least one gas-liquid contactor subsystem. The wash water regeneration subsystem receives at least a portion of the used wash water stream, regenerates the wash water stream, and flows the regenerated wash water stream to the wash section. The DAC system can include a capture solution regeneration subsystem receiving at least a portion of the CO2-rich capture solution, regenerate the CO2-rich capture solution, and flow the regenerated CO2 capture solution to the capture section.

The invention discloses a cable tunnel fire risk feature identification system and identification method, and belongs to the technical field of cable tunnel safety monitoring. The whole stage of a fire is covered through multi-class cooperative detection, the target identification precision and scene adaptability are greatly improved, and the safety of the cable tunnel is improved. According to the whole system, a flame and smoke detection unit and a flame / smoke special detection unit are innovatively added to a detection engine module, an original heat source detection unit and an original human body detection unit are combined, a heat source-flame-smoke-human body four-category collaborative detection framework is formed, high-precision recognition is achieved on the basis of a YOLO model framework, and the detection efficiency is improved. Compared with the problems that a traditional system is high in single target detection omission ratio and cannot cover the whole stage of smoldering-initial open fire-violent combustion of a fire, the system has the advantages that the recognition rate of early flame and weak smoke is increased, the false alarm rate is greatly reduced, meanwhile, a heat source of operation and maintenance personnel is prevented from being misjudged as a fire hazard through human body detection, and the safety of the fire hazard is improved. And cable monitoring and personnel safety protection are both considered.

A direct air capture (DAC) of CO2 system includes a reaction reactor having a solid, amine-functionalized sorbent configured to sequester CO2 from air; an in-situ dual-function device configured as a CO2 conversion reactor and an exchange fluid regeneration device; and the exchange fluid, recirculating between the reaction reactor and the dual-function device, configured to capture the sequestered CO2 from the solid sorbent in the reaction reactor and release the captured CO2 in the conversion reactor, the exchange fluid including one or more amino acids.

The invention relates to the technical field of data integration, and particularly discloses a perfluoro / polyfluoroalkyl substance multi-source exposure data integration risk assessment system, which is characterized in that environmental exposure data of perfluoro / polyfluoroalkyl substances is acquired through a multi-source environmental sensor array, and a PFAS multi-mode exposure feature database is established; carrying out pollution source isotope fingerprint analysis, and obtaining source contribution rate distribution maps of three pollution sources of industrial emission, surface runoff and atmospheric settlement through a nonlinear source analysis algorithm; constructing a three-dimensional geographic information dynamic migration model according to the source contribution rate distribution map, and generating a multi-medium dynamic migration flux matrix; a composite risk assessment model is established based on the multi-medium dynamic migration flux matrix, probability risk assessment is executed in combination with an ecological toxicity threshold database, and a space gridding risk grade map is output; the method not only fills the blank of the prior art in the aspects of multi-medium dynamic modeling and nonlinear source analysis, but also provides powerful technical support for environmental pollution control and ecological risk prevention and control.

An atmospheric CO2 capture system includes a compartment housing a solid CO2 sorbent, an exchange fluid including a chemical component with selectivity towards CO2, and an electrochemical cell or mineralization reactor in fluid communication with the compartment, the system having a cycle including a first state of sorbing CO2 from incoming air onto the solid CO2 sorbent until a saturation point is reached; a second state of regenerating the sorbent by flooding the compartment with the exchange fluid to detach CO2 from the saturated sorbent and bind the detached CO2 to the chemical component; and a third state of regenerating the chemical component and utilizing the CO2 in the electrochemical cell or mineralization reactor.

The invention belongs to the crossing field of environmental engineering and hydrology and hydrodynamics, and particularly relates to a traceability method based on coupling hydrodynamics and a pollutant degradation equation, which comprises the following steps: firstly, acquiring and preprocessing multi-source heterogeneous monitoring data, then selecting a one-dimensional Saint-Venant equation or a two-dimensional shallow water equation according to a water body form to solve a hydrodynamic field, and finally, determining the hydrodynamic field. A multi-component convection-diffusion-reaction equation is coupled to simulate pollutant migration and transformation; an LSTM module is introduced to identify suspected pollution events, pollution source parameters are inverted through a two-channel framework of PDE constraint optimization and Bayesian inference, uncertainty is quantified, model parameters are updated online in combination with data assimilation, and finally the uncertainty is quantified and verified. The method considers traceability precision, efficiency and compliance, supports multiple water bodies and multiple data sources, and is suitable for complex water body pollution traceability.

The invention belongs to the technical field of river and lake water quality monitoring, and discloses a river and lake water quality intelligent traceability monitoring system and method.Dissolved organic matter fluorescent fingerprints are analyzed in real time through a three-dimensional fluorescent monitoring unit, pollution markers are detected, and parameters such as COD, ammonia nitrogen and total phosphorus are synchronously detected through a full-spectrum monitoring unit; the video monitoring unit is used for collecting section images / videos of rivers and lakes, other sensors are used for collecting real-time values of chlorophyll, pH, conductivity, turbidity and dissolved oxygen in a water body, then the data processing module is used for carrying out normalization processing on multi-source data, and the analysis and early warning module is used for analyzing water quality early warning scores, spectrum early warning scores and video early warning scores. All scores are synthesized to obtain a comprehensive early warning score, traceability is started when comprehensive early warning is larger than or equal to the grade II, pollution sources are recognized based on three-dimensional fluorescence spectrum comparison and upstream patrol, and a river and lake water body monitoring-early warning-traceability-verification closed loop is achieved.

The invention discloses an inland river basin intelligent ecological scheduling rehearsal method fusing a scheduling process and an ecological process. The inland river basin intelligent ecological scheduling rehearsal method comprises the steps of multi-source data acquisition and digital twinborn construction; carrying out reservoir intelligent scheduling reinforcement learning modeling; ecological process lag response modeling is carried out; spatial diffusion modeling of ecological influence; performing cross attention guided ecological response interpolation; and carrying out rehearsal and visual display on the ecological scheduling scheme. According to the method, a hydrological-ecological response modeling mechanism is introduced, and a time-space response relationship between scheduling behaviors such as water level and water volume and ecological indexes such as vegetation indexes and habitat indexes is combined, so that lagging response characteristics of an ecological process to the scheduling behaviors can be quantitatively described, and the defect that a traditional scheduling model is insufficient in ecological expression capability is overcome. A reinforcement learning algorithm is utilized to fuse multi-source data for state perception and strategy iteration, and the scheduling strategy can be dynamically adjusted according to the current hydrological situation and ecological feedback result of the watershed. Compared with static rule type scheduling, the regulation and control efficiency and ecological adaptability are remarkably improved.

The invention belongs to the technical field of air pollution monitoring, and particularly relates to an air pollution monitoring system and method based on big data. According to the method, the pollutant diffusion topological structure is constructed through collection degree fusion of the multi-source environmental data, the prediction accuracy of air pollution monitoring is effectively improved, and when the pollutant diffusion topological structure is constructed, the influence of meteorological parameters and geographic information on a pollutant transmission path is comprehensively considered, so that the prediction accuracy of the air pollution monitoring is improved. The method enables a corresponding prediction mechanism to more accurately describe a pollutant space-time evolution rule in an air environment, introduces a prediction error-based iterative optimization mechanism after a prediction result is output, and compares the pollutant prediction concentration with the actual monitoring concentration in real time, thereby achieving the real-time prediction of the pollutant. And a diffusion weight coefficient and a diffusion probability matrix in the pollutant diffusion topological structure are adjusted, so that a corresponding prediction mechanism can maintain high-precision prediction capability, and relatively accurate data support is provided for early warning of an air environment.

The invention provides an irrigation water demand prediction method based on meteorological soil crop multi-source feature fusion, and relates to the field of data prediction, and the method specifically comprises the steps: firstly collecting farmland region multi-source feature data, and constructing an original data set; then, a nonlinear disturbance relation between farmland characteristics is extracted through a high-order disturbance encoder module, and a structure energy tensor is introduced to describe high-order structure relevance; thirdly, a dynamic gating characteristic generator module is introduced, a disturbance gain factor and a time coupling factor are combined to generate a gating signal, and dynamic screening of multi-source characteristics is achieved; then constructing a cross-variable interaction modeling module, and generating a feature embedding vector to model a complex coupling relationship among weather, soil and crops; and finally, outputting an irrigation water demand predicted value by adopting a multi-layer sensing network in combination with channel mapping and a cross memory mechanism, so that efficient dynamic prediction of the farmland water demand is realized, and the water resource utilization efficiency and the accurate regulation and control capability are improved.

The invention discloses a cementing material for a solid waste-based road of a coal-fired power plant and a preparation method of the cementing material. The cementing material mainly comprises a cementing component, an alkali-activated component and a reinforcing component, the gelling component is a mixture of coal-fired power plant fly ash and furnace slag; the alkali-activated component is a mixture of alkali residues, red mud, blast furnace slag and coal-fired power plant desulfurized gypsum; the reinforcing component is rice hull ash or peanut hull ash. The mass ratio of the gelling component to the alkali-activated component is (4 / 1)-(10 / 1); and the addition amount of the reinforcing component is 1-3% of that of the main body material. The coal-fired power plant solid waste fly ash, the furnace slag and the desulfurized gypsum are used as main bodies, a small amount of other industrial solid waste is added, and the cementing material belongs to a full-solid-waste low-carbon cementing material and can be applied to a road base, a subbase or a base layer. The invention has the characteristics of low carbon emission, high solid waste consumption, simple production process and strong pavement performance, and in addition, the invention has a good stabilization effect on the problem that part of solid waste heavy metals and sulfate ions in a coal-fired power plant exceed the standard.

The invention relates to the technical field of carbon emission monitoring and environment perception, and discloses a user-side carbon emission real-time monitoring and tracing system, which comprises a multi-source data integration module, which is used for acquiring microenvironment parameters related to carbon emission in real time; the microenvironment feature analysis module is used for analyzing the feature parameters of the traffic road section through a microenvironment perception algorithm and establishing a microenvironment feature library; the environment relation modeling module is used for constructing a vehicle performance and microenvironment relation model and calculating an environment adjustment coefficient; the dynamic carbon emission calculation module is used for generating a carbon emission estimated value; the abnormal recognition and early warning module is used for recognizing an abnormal emission mode under a specific microenvironment combination and constructing an early warning mechanism; the carbon emission map building module is used for building an urban microenvironment carbon emission influence map; the carbon footprint analysis and report module generates a refined carbon footprint report through a microenvironment factor contribution degree quantitative decomposition algorithm; according to the method, through microenvironment influence decomposition and visual display, a carbon emission result has good interpretability.

The present embodiment relates to a control method for a cleaning robot and a related device. The method comprises: acquiring a contaminant type and a contaminated area of a floor to be cleaned, wherein the contaminant type comprises a liquid contaminant; when there is the contaminated area having the liquid contaminant on the floor to be cleaned, turning a body of the cleaning robot around and driving the cleaning robot to perform a cleaning operation in a reversing posture, so as to use a wet cleaning member to clean the liquid contaminant in the contaminated area. The present invention solves the problem that a dry cleaning member of the cleaning robot is easily wetted when cleaning the liquid contaminant, improving the cleaning effect on the floor having the liquid contaminant.

The invention relates to the technical field of water quality data analysis, and discloses a river water quality pollution assessment method and system based on big data analysis, and the method comprises the steps: building a water quality parameter set; obtaining a preprocessed water quality data set; obtaining a global statistical analysis result through descriptive statistical analysis; carrying out hierarchical multi-time evaluation analysis to obtain a hierarchical evaluation result; obtaining a deviation value between the current water quality data and standard water quality data of a laboratory; reliable water quality characteristic data are obtained; a difference trend analysis result is obtained; performing relevance verification on the river water quality distribution map and the time change map of the target area according to the difference trend analysis result to form a comprehensive analysis result; and finally generating a comprehensive water quality pollution assessment report containing water quality traceability information and a comprehensive analysis result. According to the invention, a multi-parameter sensing technology and intelligent data processing are organically combined, so that the water quality of the river is efficiently, accurately and carefully analyzed, and the pollution degree is evaluated.

The invention discloses a drainage basin water body heavy metal pollution prediction system based on multi-modal attention, and the system comprises a data collection module which is used for collecting multi-modal data related to drainage basin water body heavy metal pollution, and a preprocessing module which is used for carrying out the standardization processing of the obtained multi-modal data. The multi-modal attention fusion module is used for performing feature extraction and cross-modal interaction on the preprocessed multi-modal data to generate fusion features; the dynamic prediction module is used for outputting a spatial-temporal distribution prediction result of the heavy metal pollutant concentration in the drainage basin by constructing a spatial-temporal coupled prediction model; according to the method, the cross-modal interaction accuracy is improved by dynamically focusing the key association information of the multi-modal data through the intra-modal and inter-modal attention mechanism, meanwhile, the data-driven prediction model is constructed, the prediction precision of the high-risk area is optimized through the weighted loss function, the prediction error is effectively reduced, and the prediction efficiency is improved. And high-precision dynamic prediction of heavy metal pollution under the watershed scale is realized.

The invention discloses a rhizosphere deposited carbon flux real-time monitoring method adopting a sensor array, and relates to the technical field of soil carbon cycle monitoring, and the method comprises the steps: determining a layered sampling depth and a horizontal concentric circle partition range based on the three-dimensional distribution characteristics of a target plant root system, and mapping the layered sampling depth and the horizontal concentric circle partition range to a preset three-dimensional grid coordinate system; gas sensors and environmental parameter sensors are deployed according to root system partitions, and a multi-dimensional sensor array is constructed. Through the three-dimensional grid coordinate system and the root system density gradient model, accurate spatial mapping of rhizosphere carbon flux is realized, high matching of sensor layout and root system biomass distribution is ensured by utilizing division of vertical layering and horizontal concentric circle partition, and the gas sensor and the environmental parameter sensor are cooperatively deployed, so that the reliability of the system is improved. The device can capture instantaneous changes such as root exudate pulse and microbial respiration, generates a continuous and consistent carbon flux data set, and provides a high-resolution dynamic observation basis for researching plant-soil-microbial interaction.