642 results about "Dry land" patented technology

The invention discloses a multi-model coupled regional terrestrial ecosystem carbon reserve estimation method, which is suitable for the field of carbon cycle and carbon reserve estimation. The method comprises the following steps: firstly, collecting remote sensing data, and then estimating overground, underground and soil annual carbon density mean values of a regional terrestrial ecosystem by adopting an ARIMA model; the method comprises the following steps: clustering regions with different carbon densities by adopting a CatBoost model, dividing the carbon densities of a regional ecological system into low, medium and high levels, and avoiding the influence of spatial heterogeneity among different density levels on subsequent model training; an RNN model is constructed to evaluate the carbon density conditions of different levels of unit grids, and interannual dynamic carbon density parameters of different types of ecosystems are obtained based on multi-source data; and finally, calculating the carbon reserves of the unit grids, analyzing the annual average change trend and the spatial distribution condition of the carbon reserves, and realizing accurate evaluation of the regional terrestrial ecosystem carbon sink. The method is simple in step and good in using effect, and the change condition of the carbon sink capacity in the corresponding time can be obtained according to the sampling time interval of the input data.

The invention provides an adaptive CFAR detection method based on scene classification, and the method comprises the steps: carrying out the scene classification of an input SAR image through employing a K-means clustering algorithm, carrying out the target detection of a pure sea area obtained through classification through employing VI-CFAR, and carrying out the CFAR detection of a coastal area through employing a significance model. According to the method, the problems that a traditional CFAR algorithm is high in false alarm rate and unstable in detection performance in port and land complex backgrounds are effectively solved, detection parameters are optimized according to the complexity of different scene backgrounds, and therefore it is ensured that the CFAR algorithm can still maintain the constant false alarm rate in the sea clutter background, and the robustness of target detection is remarkably improved. The ocean area and the land area in the image are effectively distinguished, and the land area is shielded. According to the technical scheme, the problem that a traditional CFAR detection algorithm is interfered by a complex land background when detecting ships on the sea surface is solved.

The invention provides a southern red soil dry land deacidification soil conditioner and a preparation method thereof, and belongs to the technical field of soil conditioners. The preparation method comprises the following steps: embedding bacillus subtilis, bacillus licheniformis and bacillus amyloliquefaciens to prepare bacterial microspheres, adding the bacterial microspheres into gel formed by carboxymethyl chitosan and silk fibroin peptide to prepare sustained-release bacterial microsphere gel, uniformly mixing the sustained-release bacterial microsphere gel with porous silicon dioxide loaded with basalt and charcoal, and drying to prepare the acid-reducing soil conditioner for the southern red soil dry land. The acid-reducing soil conditioner for the southern red soil dry land not only improves the pH value of the soil, but also can loosen the soil and improve the air permeability of the soil to a certain extent, and promotes the absorption of crops to moisture and nutrient elements by improving the physical and chemical properties of the soil, so that the normal growth of the crops is ensured, and the acid-reducing soil conditioner has a wide application prospect.

The invention discloses a regional GPP assimilation inversion system fusing foundation-multi-source satellite chlorophyll fluorescence, and belongs to the technical field of terrestrial ecosystem carbon cycle monitoring. The signal unmixing and simulation generation module is used for unmixing the total fluorescence of the mixed pixels into pure chlorophyll fluorescence (SIF) and driving an ecological model to generate SIF and GPP simulation values based on environmental stress data; the state component decoupling module is used for decoupling the total GPP analog value into a light response fast component, a light response slow component and a light response memory component; the state evolution prediction module is used for predicting dynamic evolution of the slow component and the memory component; and the self-adaptive assimilation inversion module is used for performing inversion on the region GPP by taking the slow component and the memory component as state variables, taking the SIF observation value as observation data and combining a prediction result of the state evolution prediction module. According to the method, systematic deviation caused by model simplification or data singleness in a traditional method is overcome.

The invention belongs to the technical field of ecological restoration and wetland engineering, and discloses an ecological corridor-based abandoned fishpond ecological restoration method, which comprises the following steps: S1, land forest restoration: planting saline-alkaline tolerant vegetation around an abandoned fishpond and in a land and abandoned fishpond transition area in a layered manner; s2, mangrove forest wetland construction: performing microtopography modification to adjust the bottom mud elevation, and planting mangrove forest plants in a layered manner; s3, ecological corridor construction: constructing an ecological corridor on one side of the abandoned fishpond and the land, and constructing an ecological corridor on one side of the abandoned fishpond and the ocean; s4, ecological monitoring and maintenance: carrying out hydrological, tidal and biological detection regularly; the three-dimensional ecological corridor system of'land forest-mangrove forest wetland-ocean 'is constructed, and the abandoned fish pond is transformed into the mangrove forest wetland, so that not only are biodiversity improvement and ecosystem connectivity realized, but also stable migration and inhabitation space can be provided for terrestrial and aquatic organisms.

The invention relates to the technical field of ecology and hydrology, in particular to a terrestrial ecosystem water carbon flux estimation method considering water balance constraint, which comprises the following steps: estimating leaf scale photosynthetic rate and stomatal conductance by utilizing a photosynthesis model; the leaf scale photosynthetic rate and the stomatal conductance are upscaled into canopy vegetation total primary productivity and canopy conductance to construct an evapotranspiration model to estimate evapotranspiration data; constructing a water balance model according to the evapotranspiration data so as to estimate the available water amount of the soil; constructing a soil moisture stress function according to the available water amount of the soil so as to constrain the estimation process of the photosynthesis model and the evapotranspiration model; and acquiring historical water-carbon flux data and historical remote sensing observation data of a long sequence daily scale, and calibrating the model to obtain a water-balance-constraint-considered water-carbon flux estimation model of the terrestrial ecosystem capable of estimating the water-carbon flux data. Therefore, the problems that an existing water carbon flux prediction frame is difficult to adapt to climate changes, low in prediction accuracy and the like are solved.

The invention discloses a drainage basin seasonal runoff change prediction and attribution method and system and a medium, and the method comprises the steps: carrying out the seasonal division of a hydrological year based on the monthly scale rainfall, potential evapotranspiration and land water reserve change rules in a drainage basin; establishing a plurality of coupling models of the GCM and the ABCD so as to predict the runoff process of the drainage basin under the conditions that only future climate change scenes are considered and climate change and human activity influence scenes are considered at the same time; a seasonal-scale Buddyko model is considered, and the relative influence of seasonal-scale climate change and human activities on future runoff change is quantified. The method has a strong statistical basis, can objectively reflect the change rule of the watershed hydrologic runoff, can fully decouple the complex relationship between climate change and human activity and other factors on a seasonal time scale, and provides a new technology for the research of a water circulation process driving mechanism in a changing environment.

The invention provides a method for improving flood inundation simulation precision based on fusion of VGI data and optimization of DEM, and the method comprises the steps: selecting HEC-RAS as a flood inundation simulation model, and inputting data including DEM data, river flow data, precipitation data and land coverage type data; according to a Manning coefficient range table provided by the land coverage database, setting corresponding Manning coefficients for different coverage types, and preliminarily setting the Manning coefficients as the median of each coverage type; the Manning coefficient setting is iteratively adjusted by comparing the difference between the simulation result and the actual water depth data; establishing a relation chain between the extracted water depth information and the submerged simulated water depth; height measurement data of a land observation satellite is combined with the COPDEM to estimate a residual error between the COPDEM at a water depth point position and a real elevation, and a conversion relation is established between extracted water depth and simulated water depth of a relatively optimized DEM according to an elevation difference value between the DEM and the COPDEM. Based on the technical scheme of the invention, the simulation precision is obviously improved, the VGI data is successfully combined with the optimized DEM, and the accurate correction of the Manning coefficient is realized.

The invention discloses a YOLOv8 improvement-based lightweight detection method for wheat diseases and insect pests in northwest weather, and relates to the technical field of artificial intelligence and machine vision monitoring. The method comprises the following steps: acquiring an original RGB image in a wheat filling period in a northwest dry land area environment; performing screening and Mosaic-8 data enhancement on the collected original image data set, and establishing a wheat disease and insect pest image data set; constructing an improved wheat lesion detection lightweight model based on YOLOv8, and optimizing a network structure; inputting the established wheat disease and insect pest image data set into the improved network model for training; testing the application of the improved network model in a wheat disease and insect pest image test data set, and continuously updating learning parameters of the improved YOLOv8 network model; the updated and trained YOLOv8 network model is used for monitoring a dry land area where wheat is planted in the Gansu province in real time, and the complexity and accuracy of the model are evaluated; and finally, real-time feedback of a model detection result is realized, and wheat plant diseases are dynamically updated to improve model precision.

A comprehensive regulation and control method suitable for improvement of a coastal mud flat severe saline-alkaline dry land comprises the steps that firstly, the area of a field needing to be improved and the soil salinity are measured, the use amount of acid volcanic rock debris and the use amount of high-fiber fermented wood chips are calculated, the application amount of the acid volcanic rock debris is 6-10 cubic meters / mu, and the use amount of the high-fiber fermented wood chips is 85-150 kg / mu; secondly, when the soil salinity is gt; when 0.8%, canal irrigation tube row is combined for concealed tube salt elimination, and the salt is reduced to about 0.4%; thirdly, uniformly scattering acidic volcanic rock debris and high-fiber fermented sawdust into the severe saline-alkali soil, then ploughing the field with the ploughing depth of 5-20 cm, uniformly mixing the field with soil, and then planting and cultivating dry farming crops to complete comprehensive regulation and control.

The invention relates to a numerical mode simulation method for CO2 flux of high-resolution rice, wheat and corn, which comprises the following steps: calculating a vegetation index and a land surface water index, and carrying out inversion to obtain key vegetation parameters of a land ecosystem; the meteorological data and the topographic data are processed, meteorological field initial and boundary condition files are generated, and CO2 chemical initial and boundary condition files are generated; integrating the gridded artificial source CO2 emission data file; applying the optimized photosynthetic and respiratory action parameters to a photosynthetic and respiratory action calculation formula of the terrestrial ecosystem, and constructing a CO2 flux simulation system of the crop system; outputting the CO2 flux of the rice, the wheat and the corn in the simulation area. The method has the advantages that CO2 flux seasonal change characteristics in the key phenological period in the growth process of rice, wheat and corn are simulated, carbon cycle characteristics in the growth process of crops can be better reflected, and more reliable data support is provided for ecological meteorological research.

The invention provides a terrestrial ecosystem service function monitoring and evaluation method, and the method comprises the steps: generating a biological feature vector and an environment feature vector according to biological data and environment data collected in an ecological protection region; performing species identification on the biological feature vector based on a biological large model, performing environment analysis on the environment feature vector based on an environment large model, and obtaining animal and plant information and environment quality evaluation conditions in the ecological protection area; and based on an ecological system evaluation model, carrying out comprehensive reasoning analysis on the organisms, the environment, the comprehensive feature vectors, animal and plant information in the ecological protection area and environment quality evaluation conditions, and evaluating an ecological system service function of the ecological protection area. Wherein the comprehensive feature vector is determined based on the fusion of the biological feature vector, the environment feature vector and the dynamically adjusted weight. According to the method, the overall ecological condition of the ecological protection area can be more comprehensively understood by adopting a large model technology, and more comprehensive, accurate, dynamic and scientific ecological system service function evaluation is provided.

The invention belongs to the technical field of mobile robots, and particularly relates to an amphibious hexapod robot which comprises a robot body, six walking feet, a protection box, propellers, a multi-sensor system and a central control unit. The six walking feet are arranged on the two sides of the robot body, and a waterproof driving joint is arranged at the tail end of each foot. The protection box is arranged at the root of the walking foot and internally integrated with propellers; the sensor system comprises a water depth sensor, an attitude sensor and a grounding detection module; the central control unit is used for collecting sensor data in real time, judging whether the current environment is a land or a water area, automatically switching a walking mode or a water propulsion mode, and meanwhile adaptively adjusting gaits and the rotating speed of propellers according to the water depth and the terrain. The robot has environment perception, mode decision, gait generation, grounding prevention protection and energy optimization strategies, full-autonomous and high-adaptability movement in the land and water environment is achieved, and the working capacity and safety of the robot in the complex environment are improved.

The invention discloses a water area and resource quantity monitoring and predicting method and system based on a remote sensing technology, and belongs to the technical field of water resource monitoring. The method comprises the following steps: determining a water area range according to historical data of a research area and an on-site survey condition, and determining a research area range; the method comprises the following steps: respectively acquiring ground data and water depth and water surface elevation data by using an unmanned aerial vehicle and an unmanned ship, respectively processing to obtain a land DEM and a water area DEM, and fusing to form an all-terrain DEM; downloading satellite image data of the research area, and performing geographical registration on the satellite image data; in the geographically registered satellite image data, describing the boundary of the water area through visual interpretation; superposing the water area boundary to an all-terrain DEM, obtaining the elevation of each point on the water area boundary line, calculating the average elevation of the water area boundary, and calculating the water area and the water resource amount to obtain the historical water area and the water resource amount; and on the basis of the obtained historical water area and water resource quantity, utilizing an ARIMA model to predict future water resource quantity and water area.

The invention relates to a shallow water dynamic process simulation method based on a local time step length, and the method comprises the steps: dividing a target region into a plurality of grids based on a shallow water dynamic process model, the target region comprising an ocean region and a land region adjacent to the ocean region; at least dividing the plurality of grids into a first grid set and a second grid set; determining a first time step length corresponding to the first grid set according to the first grid set; determining a second time step length corresponding to the second grid set according to the second grid set; determining a first simulation result of the shallow water dynamic process according to the first time step length and the second time step length; wherein the first grid set comprises a plurality of first grids, and the second grid set comprises a plurality of second grids; the first time step length is larger than the second time step length. The efficiency of the shallow water dynamic process simulation method is improved by respectively determining appropriate local time steps according to the precision requirements of different grid sets.

The invention relates to the technical field of underground space development, and provides a coastal bedrock type city underground space development geological suitability evaluation method comprising the following steps: analyzing key geological problems of land area and sea area underground space development, and extracting related geological factors; basic geological data are collected and classified, a geological suitability evaluation index system is constructed, and geological evaluation units are divided; subjective and objective weights are determined based on an analytic hierarchy process and an entropy weight method, and an optimal comprehensive weight is obtained through game theory combination weighting; modeling based on a grey correlation analysis method, and calculating and grading suitability scores of the evaluation units; and integrating evaluation results, and generating an underground space development geological suitability partition map of land-sea overall planning. According to the scheme, the underground space development pattern is optimized, comprehensive utilization of land and ocean resources is promoted, and safe, efficient and sustainable development and utilization of the coastal city underground space are powerfully supported.

The invention discloses a density interpolation-based ocean equidensity layer depth and thickness calculation method, which comprises the following steps of: acquiring an oceanographic data file which comprises salinity, temperature, layer thickness and topographic data, and filtering non-ocean region data by utilizing a land mask; based on the temperature and salinity data, calculating seawater density distribution by adopting a seawater state equation; calculating salinity and temperature gradient, and dynamically adjusting a density threshold value, so as to calculate a density gradient and generate a dynamic density threshold value; generating a target equidensity value based on the dynamic density threshold, and calculating depth distribution of a target equidensity layer through an interpolation algorithm by using a relationship between density and depth; calculating the thickness of the equal-density layer based on the depth of the equal-density layer; and performing boundary processing on the depth and thickness data of the equal-density layer obtained by calculation. According to the method, the depth and the thickness of the equal-density layer are efficiently calculated, and the calculation result can be directly used for research of a marine vertical structure, water mass analysis, position vortex calculation and marine circulation system dynamics analysis.

The invention provides an SAR image polar region sea ice detection method and system based on deep learning and a medium, the land and the water area are segmented by using a water area detection algorithm based on a DeeplabV3 network, the segmentation precision of the DeeplabV3 network is improved by means of cavity convolution, a spatial pyramid pooling module and a decoder, and the calculation and memory overhead is reduced by using a lightweight MobileNet; then, a sea ice detection algorithm based on a short-term dense cascading STDC network is used for precisely segmenting sea ice and water in a water area, the STDC network reduces the calculation complexity through specific module design and keeps multi-scale information, and meanwhile, multiple optimization means are adopted in decoder design to improve the detection performance; in addition, data is prepared and augmented, and the generalization ability of the model is enhanced. The sea ice detection precision and efficiency are improved, and the method is suitable for resource-limited environments such as on-satellite environments and the like.

The invention discloses a sea-land collaborative coastal wetland ecological quality remote sensing evaluation method under a spartina alterniflora expansion background, and the method comprises the steps: obtaining multi-source remote sensing data of a research region, and carrying out the preprocessing of the data, and obtaining a preprocessed remote sensing image; according to the preprocessed remote sensing image, obtaining a salt marsh vegetation space-time distribution diagram of the research area; remote sensing evaluation is conducted on coastal wetland land and water body ecological quality, land ecological quality remote sensing evaluation indexes integrate NDVI, WET, NDSI, LST and DHI, and water body ecological quality remote sensing evaluation indexes integrate TSM, WST, CDOM and Chl-a; and finally, quickly obtaining the ecological quality change of the affected area of the spartina alterniflora through a spartina alterniflora change condition mask evaluation result. The ecological quality remote sensing evaluation method provided by the invention is more suitable for the coastal wetland under the background of spartina alterniflora expansion, and a scientific basis is provided for making coastal wetland ecological management and protection strategies.

The invention provides a submarine topography and land elevation matching method based on multi-source data fusion, and belongs to the technical field of geographic information technology and ocean engineering cross fusion. Seamless splicing of sea and land topographies is realized through multi-source data preprocessing, topographic feature correlation extraction, dynamic compensation matching and adaptive weight fusion; according to the method, the problems of data heterogeneity, dynamic environment adaptability and insufficient feature association can be solved, the matching precision can reach + / -3cm, the processing efficiency is also improved, and the method is suitable for coastal zone modeling, ocean engineering and other scenes.

The invention discloses a construction method of an earth system coupling device and the earth system coupling device, and the construction method comprises the steps: a first component module construction step: constructing a plurality of first component modules of a global climate system based on full coupling, the plurality of first component modules comprise an atmospheric component module, a land component module, a sea ice component module, a ground ice component module, a river component module, a first ocean component module and a sea wave component module; a second component module construction step: constructing a second component module based on the ocean circulation simulation system, wherein the second component module is a second ocean component module; a replacement step: replacing the first ocean component module with the second ocean component module; and a coupling step: reconstructing a coupling application interface of the coupler of the global climate system based on full coupling, and carrying out data exchange and interaction among different component modules through the coupling application interface.

The invention discloses a method for fertilizing dry land white slurry soil by coupling liquid fermentation cow dung and straw to return to field. The Baijiang soil fertilizing method provided by the invention comprises the following steps of: throwing crop straws and stubbles into the field in a full amount, then sowing liquid fermented cow dung, and turning over and burying soil; the liquid fermented cow dung dirt is a product obtained by anaerobic fermentation of cow dung, urine and colony house flushing sewage. According to the method, the liquid fermented cow dung and the straws are fully crushed and returned to the field to jointly fertilize the Baijiang soil, so that the cultivated land quality of the Baijiang soil can be remarkably improved, the straw decomposition and nutrient release rate can be accelerated, planting and breeding circulation and livestock and poultry manure resource utilization can be promoted, and the method has important significance on guaranteeing the national food safety.

The invention discloses a land water reserve prediction method and system based on artificial intelligence and electronic equipment. The prediction method comprises the following steps: collecting an atmosphere reanalysis data set and gravity satellite land water reserves data, and obtaining various global climate mode output data; constructing a long-short-term memory model for simulating long-series land water reserves; adopting the corrected lattice global climate mode output data to drive a long-short term memory model, and simulating a first prediction result of land water reserves in a future prediction period; fitting a hook-shaped response function of the land water reserves and the dew-point temperature, and obtaining a second prediction result of the land water reserves in the future prediction period; and constructing an emergence constraint model for correcting the prediction result. According to the method, the land water reserve space-time evolution rule under the influence of climate change can be fully reflected, the land water reserve prediction period is remarkably prolonged, the prediction effect is improved, and the defect that in the prior art, land water reserve prediction is large in uncertainty is overcome.

The invention discloses an arid region groundwater reserve estimation method and system based on multi-source remote sensing data, and relates to the technical field of groundwater monitoring, and the method comprises the steps: collecting land water reserve data and remote sensing image data of a target arid region, obtaining a land water reserve change sequence according to the land water reserve data, carrying out the region weighting of the target arid region, and obtaining a target arid region groundwater reserve change sequence; obtaining a land water reserve change sequence of the target arid region; based on the remote sensing image data of the target arid region, using a digital elevation model to obtain a surface water reserve change sequence of the target arid region, using a land surface process model to obtain a soil water reserve change sequence of the target arid region, and establishing an underground water reserve model of the target arid region; and performing error analysis on an output result of the groundwater reserve model by using a Monte Carlo simulation method. According to the method, through collaborative inversion of multi-source remote sensing data and integration of the groundwater reserve models, accurate quantification of spatial-temporal dynamic of the groundwater reserves in the arid region is realized.

The invention relates to the technical field of ocean formation activity monitoring, in particular to an ocean formation activity real-time monitoring method, which mainly comprises the following steps of: connecting a communication optical cable existing at the ocean bottom with a land demodulator to form a distributed optical fiber sound wave sensing monitoring system, and carrying out time-space uninterrupted continuous observation on ocean formation activity signals; a deep learning algorithm is trained, and efficient and accurate pickup of the marine stratum activity DAS monitoring signals is achieved; a DAS positioning algorithm is developed, and the space accurate position of the underwater vibration signal is accurately obtained; and in combination with a time-frequency analysis technology, a time-space-frequency-strong association relationship of the marine formation activity is constructed, and an evolution law of the marine formation activity is explored. According to the method, the reliability and decision-making capability of marine geological disaster risk assessment are improved, and important support is provided for sustainable development and utilization of future marine resources.

The present invention provides a source-sink matching method based on hydrate method and saline CO2 storage, which can improve the efficiency of carbon dioxide storage and reduce environmental risks. The method comprises the following steps: optimizing the terrestrial carbon source distribution points through a mixed integer linear programming (MILP) model to minimize the transportation cost and path. Accurately determine the geological characteristics of the storage target area using three-dimensional seismic data. Comprehensively evaluate the storage capacity of saline aquifers and hydrate method through numerical models, considering three mechanisms of structural storage, dissolution storage and residual gas storage. The MILP model is applied again for cost analysis and source-sink matching. The environmental footprint is analyzed through life cycle assessment (LCA) to ensure the sustainability of the storage scheme. The method provides an efficient, economical and environmentally friendly solution for geological storage of carbon dioxide.

The embodiment of the invention discloses a quantitative evaluation method for the influence of climate change and human activity on land water reserves, and relates to the technical field of geographic information, and the method comprises the steps: obtaining first TWSA data and climate-driven remote sensing data related to climate factors; reconstructing TWSA data in combination with a gradient lifting regression model, and outputting climate-driven second TWSA data; verifying the second TWSA data, and extracting third TWSA data related to the human activity factors through a separation method under the condition that the verification is passed; and respectively calculating composition contribution rates of the second TWSA data and the third TWSA data, and determining main factors for driving land water reserves to change. According to the embodiment of the invention, the direct driving effect of the climatic factors on the TWSA data is comprehensively considered, the dynamic relationship between the climatic factors and the TWSA data is combined, and a scientific basis can be provided for quantifying the relative contribution of the climatic factors and human activity factors.

The invention discloses a water depth inversion and coastal zone topographic surveying and mapping method based on a laser radar, and the method is applied to a surveying and mapping instrument mounted on a small unmanned helicopter, and achieves the quick and accurate measurement of the coastal zone topography. The surveying instrument comprises the following instruments: a laser radar, a camera, an inertial measurement unit and a global positioning unit. The method comprises the following steps: completing internal and external parameter calibration of each sensor on a surveying instrument; using the unmanned aerial vehicle to mount the surveying instrument to the to-be-measured area, and moving to obtain topographic data of the to-be-measured area; preliminarily constructing an odometer by using Kalman filtering, and constructing a land topographic map; the method comprises the following steps: recording motion characteristics of sea waves by using a laser radar point cloud elevation, obtaining a laser radar point cloud elevation program sequence, obtaining the water depth of an offshore sea area through a cBathy water depth estimation algorithm, and converting the water depth into a sea area topographic map; and combining the two topographic maps into a complete coastal zone topographic map based on the geographic coordinates.

The invention belongs to the technical field of intelligent irrigation, and particularly relates to a dry land terrace intelligent irrigation control system based on multi-modal data, which comprises a data acquisition module, a data analysis and processing module, a water source and water delivery module, an irrigation execution module and a user interface and monitoring module. According to the invention, sudden water deficit (such as late spring coldness) is dealt with through path re-planning by the mobile irrigation unit, the emergency response speed is increased by 70%, and the drought loss rate is reduced by 54% by a synchronous digital twinning alarm strategy. The core breakthrough is that a closed-loop dynamic optimization mechanism of multi-source data acquisition-edge cloud collaboration-execution feedback is formed, and the problem of resource mismatching caused by data splitting of a traditional system is thoroughly solved, so that the emergency capability is improved; through collaborative optimization of an edge calculation layer (for example, more than 50% humidity data is removed in real time in continuous 3 hours) and a cloud decision layer (three-dimensional control matrix output), a valve is dynamically adjusted in combination with gravitational potential energy, so that the irrigation misjudgment rate is reduced.