1837 results about "Water conservation" patented technology

The invention relates to the technical field of agricultural intelligent irrigation, and discloses a meteorological data fused water-saving irrigation control method, device and equipment and a medium. According to the method, a historical meteorological data set is constructed through multi-source meteorological data fusion, a dynamic water demand table is generated in combination with a crop water demand characteristic database, and a crop water demand model is established based on soil moisture content data. A grid irrigation unit division and growth period coupling soil moisture content response matrix construction technology is adopted, a cooperative constraint is established between a water demand threshold value and a water saving benefit through a multi-objective optimization learning algorithm, and a personalized irrigation scheme is generated. A soil moisture content dynamic evaluation matrix containing a dynamic time warping operator is designed, and dynamic matching of the soil layered soil moisture content and a standard template is achieved. The contradiction between meteorological response lag and low water resource utilization rate in traditional irrigation is effectively solved, accurate irrigation decision is realized through multi-dimensional data fusion and an intelligent optimization algorithm, and the water-saving benefit and the agricultural water resource utilization efficiency are improved.

The invention discloses a water-saving control method for agricultural irrigation, a cloud platform and equipment, and relates to the technical field of irrigation water-saving control, and the method comprises the steps: determining the historical rainfall of the geographic position of a target farmland and the historical soil moisture content parameter of the target farmland; determining farmland water demand rule characteristics of the target farmland based on the historical rainfall and the historical soil moisture content parameters; constructing a farmland water-saving control model according to the farmland water demand rule characteristics; dividing a water demand area of the target farmland based on the crop information; based on the farmland water-saving control model and the soil moisture content parameter of each water demand area, obtaining a predicted irrigation value of each water demand area; acquiring a real-time irrigation value of each water demand area; and based on the predicted irrigation value and the real-time irrigation value, performing real-time regulation and control on a preset intelligent irrigation water valve in each water demand area. The problem that the utilization rate of water resources is low can be effectively solved.

The invention relates to the technical field of water and fertilizer integration, and provides an intelligent water and fertilizer integration optimization method and device based on the Internet of Things technology, and the method comprises the following three core stages and interaction mechanisms: 1, a data perception and edge processing stage; 2, an intelligent decision-making and dynamic optimization stage; and step 3, an accurate execution and closed-loop control stage. Soil parameters, meteorological parameters and crop physiological parameters are comprehensively collected through a multi-modal sensor network, the data transmission efficiency is improved by using an LoRa / NB-IoT hybrid transmission protocol, data cleaning and standardization processing are completed in combination with edge computing nodes, and the data fusion depth and quality are improved; a multi-objective optimization function is constructed based on a crop growth model, a water and fertilizer regulation and control strategy is dynamically generated through a machine learning algorithm, and collaborative optimization of water saving, yield increasing and environmental protection is achieved.

The invention relates to a supply and demand multi-source data fusion farmland water-saving irrigation water system design and dynamic water distribution optimization method, which is characterized by comprising the following steps: S1, crop-soil-weather multi-source data coupling modeling, S2, water-saving water system design optimization, S3, dynamic water-saving water distribution strategy, and S4, intelligent terminal control system control. According to the scheme, accurate configuration of water resources is achieved through the artificial intelligence technology, the irrigation water consumption is reduced to the maximum extent, and meanwhile the crop growth requirement is met.

The invention relates to the field of power system supply and demand interaction, and discloses an intelligent greening irrigation system and a water-saving control method, the system comprises a multi-source data acquisition module, a space-time tensor modeling module, a dynamic decision generation module, an edge calculation acceleration module, a distributed execution control module and a drip irrigation module; the method comprises the following steps: collecting multispectral, meteorological and soil moisture data of a plant canopy in real time to generate an original data set; a fusion data set is obtained through space-time alignment and normalization preprocessing; the water demand is predicted based on an LSTM-Transform model, and an irrigation safety interval is screened; the irrigation uniformity and water pressure distribution are simulated and evaluated through multi-physics field coupling; a double-delay DDPG algorithm is used for optimizing valve opening parameters; the model and the execution error are corrected through Bayesian modeling, and an NDVI feedback optimization strategy is combined. According to the invention, a double-delay depth deterministic strategy gradient algorithm is introduced for dynamic optimization of an irrigation strategy, so that the capability of quickly adapting to environmental changes is achieved.

The invention discloses a deep learning-based intelligent optimization method for farmland irrigation water quantity. The method comprises the following steps of S1, obtaining a preprocessed farmland multi-mode perception data set; s2, constructing and training a multi-scale gated SIREN water content continuous prediction model by taking the preprocessed farmland multi-modal perception data set as input; s3, dividing a planned irrigation period into a plurality of time slices, defining a water volume decision vector space and constructing a differential evolution multi-target water volume optimization model; s4, outputting a Pareto optimal water quantity decision vector set meeting a multi-target constraint condition, and selecting an optimal farmland irrigation water quantity from the Pareto optimal water quantity decision vector set according to a user weight or a preset rule; s5, the optimal farmland irrigation water amount is issued to an intelligent valve control system, and an electromagnetic valve is driven to execute irrigation according to time slices. According to the invention, an intelligent irrigation prediction-decision-execution-feedback full-link closed-loop mechanism taking SIREN as a core is realized, and the method has remarkable water-saving and yield-increasing benefits and engineering deployability.

The invention discloses an urban ecological unit scale water conservation function evolution simulation system, relates to the technical field of ecological hydrological simulation, and is technically characterized in that the system combines an InVEST model, a water balance method, a geographic detector and a Moran index to construct a multi-source data fused water conservation evaluation method. According to the system, key factors are obtained through remote sensing data and geostatistical data, a mapping model between water yield and actually measured runoff depth is established based on a regression fitting relation, and a spatial heterogeneity analysis and factor interaction detection mechanism is introduced, so that time sequence dynamic simulation and spatial pattern recognition of a water conservation function are realized. The system can be widely applied to the fields of urban water resource regulation and control, ecological space planning, hydrological safety evaluation and the like.

The invention relates to the technical field of water and soil conservation monitoring, and discloses a remote sensing image-based water and soil conservation monitoring method, which comprises the following steps of: 1, integrating optical, infrared and microwave remote sensing data, and constructing a soil information atlas; step 2, capturing soil humidity change in each season by using long-time-sequence data according to the soil information, and determining the influence of rainfall, snow melting and evaporation on the reflectivity; step 3, training data of each wave band through a deep neural network according to the influence information of the reflectivity; through an adaptive learning algorithm and a model parameter regular updating mechanism, the problem that in the prior art, characteristic spectrums of wet soil, vegetation and bare soil are overlapped due to seasonal changes is effectively solved, after the seasonal modulation factors are introduced, the system can accurately capture influences of natural factors such as rainfall, snow melting and evaporation on the soil reflectivity, and the soil reflectivity is improved. And model parameters are adaptively adjusted, so that the interference of reflectivity fluctuation on a monitoring result in wet and drought states is eliminated, and the stability of long-term monitoring is ensured.

The invention specifically relates to the technical field of intelligent irrigation, and discloses a meteorological prediction-based irrigation dynamic regulation and control system, which comprises a data acquisition module, a data analysis module, a strategy generation module, a strategy execution module, a feedback regulation module and a man-machine interaction module, the data acquisition module integrates a water quantity acquisition terminal, a crop state acquisition terminal and a meteorological monitoring terminal, acquires multi-source irrigation decision data of a target irrigation farmland in real time, judges a water shortage risk level of the target irrigation farmland through the data analysis module, and generates an irrigation strategy through the strategy generation module; the strategy execution module executes an irrigation strategy through an electrically-driven intelligent water-saving valve, the feedback adjustment module dynamically adjusts the irrigation strategy based on sensor feedback data, and the man-machine interaction module provides a data visual interface, dynamically optimizes the irrigation strategy in combination with real-time meteorological changes and irrigation feedback, divides water shortage risk levels, and provides a water-saving management system. The utilization efficiency of water resources is effectively improved, and the applicability and reliability of the system are improved.

The invention relates to the technical field of soil erosion monitoring, in particular to a shallow mountain belt abrupt slope shrub land soil erosion monitoring method and system, and the method comprises the following steps: S1, collecting topographic point cloud data and vegetation reflectivity data; s2, spatial interpolation is carried out on the terrain point cloud data to generate three-dimensional terrain grid data, and meanwhile, boundary coordinates of a shrub coverage area are taken; s3, calculating a root system corrosion resistance strength value of each grid; s4, generating a real-time erosivity index of each grid; s5, extracting a real-time erosivity index of the grid where the corresponding node is located and a terrain parameter of the associated grid; and S6, calculating the soil erosion amount grid by grid, and generating a three-dimensional erosion space distribution diagram. According to the invention, through integration of multi-source data acquisition, real-time data processing and three-dimensional visual monitoring, accurate evaluation and dynamic early warning of the soil erosion process of the shrub forest land with the abrupt slope in the shallow mountain are realized, so that decision support is provided for water and soil conservation and ecological restoration.

The invention relates to the technical field of intelligent irrigation, in particular to an agricultural water-saving irrigation intelligent regulation and control system which comprises a growth stage recognition module, a moisture monitoring module, a meteorological data synchronization module, an irrigation strategy scheduling module and a feedback correction module. According to the method, high-precision identification of crop stage states, improvement of stage judgment accuracy, screening of key growth period blocks, focusing of regulation and control targets, improvement of resource utilization efficiency, layered acquisition and trend comparison of humidity data and construction of a deep and shallow layer dynamic response structure are realized through time sequence analysis of rice key growth parameter amplification; the method comprises the following steps of: enhancing moisture change resolution, synchronously fitting a humidity rhythm and weather prediction, improving regulation and control perspectiveness, eliminating a rainfall interference window, combining with a water demand gear, realizing block precise irrigation, feeding back a regulation and control result through double indexes of humidity and leaf chromatic aberration, constructing set mapping, forming a closed-loop regulation and control mechanism, and enhancing adaptability and execution precision.

The invention discloses a garden multi-source intelligent water-saving regulation and control method and system, and belongs to the technical field of garden intelligent irrigation. The method comprises the following steps: collecting water quantity and water quality data of rainwater, reclaimed water and tap water in real time, and generating a structured data set after space-time alignment and exception processing; a parallel prediction model is adopted to fuse water quantity prediction and water quality trend analysis, and a water source available amount sequence is output; generating a dynamic scheduling instruction based on the multi-objective optimization function and the quantum decision forest model; the risk instruction is issued and executed after being simulated, verified and corrected through a digital twin engine; and finally, optimizing model parameters according to actual execution deviation feedback. According to the invention, intelligent cooperative scheduling of multiple water sources is realized, the utilization rate of non-traditional water sources is obviously improved, the dependence degree of tap water is reduced, meanwhile, the operation safety of a pipe network and the stability of water quality are ensured, and an efficient and energy-saving intelligent solution is provided for garden irrigation.

The invention relates to the technical field of intelligent control, and discloses a water-saving fertilization variable control method suitable for sandy soil, and the method comprises the steps: obtaining collection data based on a sensor; and establishing and updating an infiltration-storage-leaching loss prediction model of the sandy soil according to the collected data, performing state estimation on soil moisture and nutrient states, and calculating root layer moisture deviation, fertilizer concentration deviation and deep seepage risk. And executing model predictive control in the rolling time domain to obtain a control result. And executing water-saving fertilization operation according to the control result. In the execution process, the soil volume moisture content, the soil water potential, the soil conductivity and shallow layer leakage observation data are fused, the prediction model is corrected, the control result is dynamically adjusted according to the correction result, and when the environment wind speed exceeds a set threshold value, the spray irrigation parameters are corrected. The fine level of control is improved, deep layer leakage can be inhibited under the sandy soil condition, water and fertilizer balance of a root layer is guaranteed, and external disturbance is coped with.

The invention discloses an intelligent agricultural water-saving irrigation system and a control method, and relates to the technical field of agricultural irrigation. Comprising the following steps: a land area planning module performs equal-area division on a farmland, sets a detection node array, and monitors water retention conditions of different soil depths; the moisture gradient characterization module calculates the vertical moisture gradient and the direction of the vertical moisture gradient of the evaluation area in real time through edge calculation. And the irrigation water amount correction module fuses and generates a target water-holding capacity based on the leaf stomatal conductance signal and the moisture gradient. The irrigation circulation termination control module uses pulse type infiltrating irrigation, and sets double termination conditions of the water-holding capacity change rate and the permeability. The closed-loop feedback adjustment module detects the soil water content after irrigation, characterizes the water leakage risk and feeds back and adjusts the irrigation water amount, closed-loop control is formed, and effective utilization of water resources is ensured.

The invention relates to an inter-basin water saving amount transaction and scheduling optimization method, which comprises the following steps of: performing dynamic contrast analysis on water saving behaviors and water resource response on the basis of historical water consumption behaviors, resource regulation and control records and meteorological basic data, judging the autonomy and continuity of the water saving behaviors, and obtaining the right-confirmable water saving amount; according to the watershed water resource tension degree, the water ecology sensitivity and the water transfer cost, a cross-watershed conversion rule is adopted, a conversion scale factor is set, and resource value transverse butt joint of water saving behaviors of different areas is achieved; calculating the flow attenuation, the regional bearing threshold and the water quality compatibility in the allocation path based on the water-saving amount obtained by the water-saving transaction, and determining the available transmission range and the sustainable allocation amount of the water-saving amount; and according to the distribution of the water-saving quotas and the corresponding value grades, carrying out combined screening according to the use priority, the basin compensation relationship and the space-time adaptation requirements, outputting a resource allocation scheme, and forming a cross-basin water-saving-quantity-driven water resource optimal allocation structure.

The invention discloses a high-water-saving accurate drip irrigation optimization method based on a population algorithm. The method comprises the following steps: S1, constructing a comprehensive input data set; s2, forming a multi-dimensional collaborative vector coding set; s3, constructing a multi-objective optimization model; s4, generating an initial improved shark search algorithm population; s5, in a global exploration stage, forming an evaluation result data set; s6, in a local development stage, recording a current optimal multi-target solution; s7, decoding the multi-dimensional collaborative vector code corresponding to the current optimal multi-target solution into a drip irrigation pipe network implementation data set and an irrigation scheduling implementation data set; and S8, generating an irrigation control instruction set based on the drip irrigation pipe network implementation data set and the irrigation scheduling implementation data set, and executing partition irrigation operation. According to the method, the pipe arrangement rationality and the water resource utilization efficiency can be optimized at the same time, and higher convergence and generalization ability are shown in complex terrains and heterogeneous crop distribution environments.

The invention relates to the technical field of intelligent agriculture and precise irrigation, in particular to an intelligent control system for agricultural irrigation. Comprising a water-saving valve module, a sensing layer module, a control layer module, an execution layer module and a data and application layer module, and the water-saving valve module is used for achieving microsecond level flow regulation and control through piezoelectric ceramic driving and energy recovery and integrating a self-maintenance function. According to the invention, the LSTM network and the Duelling DQN algorithm are utilized to accurately discriminate the soil type and formulate an extreme weather coping scheme, dynamic optimization of an irrigation strategy is realized based on low-power-consumption edge calculation and an intelligent control algorithm, the adaptability and decision accuracy of the system are greatly improved, multiple advanced technologies are integrated, and the system is suitable for large-scale popularization and application. Comprising a magneto-rheological buffer, a TSN valve controller, an SMA emergency pressure release valve and a variable frequency water pump driver, pressure balance of a pipe network, high-precision synchronization of valves and safe treatment of sudden failures are ensured, and the stability and flexibility of an irrigation system are comprehensively improved.

The invention discloses a garden partition intelligent water-saving irrigation regulation and control system based on the Internet of Things, and belongs to the field of irrigation regulation and control systems. According to the system, a basic water demand model containing static characteristics of plants, soil and the like is established for each subarea through a central processing controller, real-time environment data and weather forecast are fused, and future irrigation water demand and optimal time are calculated in a prospective mode. The core innovation of the method lies in that after irrigation, the system performs feedback iterative optimization on a basic water demand model by comparing the efficiency deviation of the actual change and the predicted change of the soil humidity to form a self-learning closed loop. According to the method, conversion from passive response to active prediction is achieved, the method has the advantages of being accurate, prospective and self-adaptive, the method can continuously adapt to environmental changes, and the intelligent level and the water saving effect of irrigation are remarkably improved.

The invention provides grouting and filling equipment for water-preserved mining of a coal mine, and relates to the technical field of mining equipment, and the grouting and filling equipment comprises a base frame piece, a grouting guide pipe piece, a slurry post-processing assembly and a plugging driving assembly. A plurality of groups of outer ring parts with hole wall pressure sensors are arranged on the outer wall of the grouting guide pipe piece, and a pipe end micro sensor is arranged at the grout outlet end; the inserting and pulling driving assembly drives the stirring assembly to push the outer ring part through the motor, and inserting and pulling of the grouting guide pipe piece are controlled. During working, the guide pipe piece is inserted into a grouting hole to a goaf, the sensor monitors rock mass pressure, temperature and sound wave signals in real time, the grouting pressure is dynamically adjusted in combination with formation resistance, and grout fluid channeling or insufficient filling is avoided. Through precise pressure regulation and automatic insertion and extraction, the problems of material waste, underground water pollution and insufficient goaf filling in traditional grouting are solved, and the environmental protection property and the engineering efficiency of water-preserved mining are remarkably improved.

The invention relates to the technical field of the Internet of Things, in particular to a landscaping intelligent management method and system based on the Internet of Things, and the method comprises the following steps: obtaining humidity, temperature, pH value and salinity sensors deployed in a landscaping area, collecting the monitoring data of an integral point, synchronizing the values of the four types of sensors, and eliminating change rate abnormal points. And a distributed soil sensing data set is generated after integration and archiving. According to the method, the time consistency is ensured and the monitoring precision is improved through hourly data synchronization and abnormal value elimination, the microenvironment change identification capability is enhanced through comprehensive analysis of salinity, humidity and temperature, the abnormal region discrimination accuracy is improved, and after a plant database is matched, the actual guidance value of plant adaptability assessment is improved, the health risk direction is defined, and the health risk assessment efficiency is improved. Historical irrigation and salinity analysis reveal the structural deviation of irrigation behaviors, the irrigation scheme is adjusted in a partitioned mode, the pertinence of resource allocation and the water-saving efficiency are enhanced, and efficient, accurate and self-adaptive development of landscaping management is promoted.

The invention relates to the technical field of planting, in particular to drip irrigation equipment for agricultural water-saving irrigation, and aims to overcome the defects that according to drip irrigation equipment in the prior art, a drip irrigation pipe is damaged and the planting efficiency is affected due to the fact that the drip irrigation pipe is inconvenient to automatically release and wind and is inconvenient to wash. According to the scheme, the device comprises a fixing frame; the number of the moving wheels is four, and the four moving wheels are all installed at the bottom of the fixing frame; the intelligent electromagnetic valve control cabinet and the intelligent water and fertilizer all-in-one machine are fixedly mounted at the top of the fixing frame; the storage barrel is fixedly installed at the top of the fixing frame, a stirring shaft is rotatably installed at the top of the storage barrel, and a plurality of blades are fixedly installed on the stirring shaft. According to the drip irrigation device, a drip irrigation pipe can be conveniently and automatically released and wound, the drip irrigation pipe can be conveniently washed, the situation that the drip irrigation pipe is damaged is avoided, and the planting efficiency is improved.

The embodiment of the invention discloses a method for intelligently assisting in reviewing a water conservation scheme of a water and soil conservation production and construction project, and the method achieves the intelligent feature matching of a new scheme and similar cases through the construction of a tagged knowledge base integrating historical cases of multiple industries, so as to recognize the generality compliance. A double-engine review mechanism is adopted, a form review module automatically checks document structure integrity and format specifications, and a logic review module executes cross-chapter data consistency check and business logic compliance analysis and highlights and positions error positions in a document. And recording decision logic in real time to form a feedback closed loop. And dynamically optimizing case library matching weight and recognition rules based on high-frequency error statistics and expert correction records. The modes of positioning review key points to chapters and sections, describing specific requirements of each review key point in a language, adding a check formula among data to review content needing to be calculated, determining a check type to which each review key point belongs, and the like are adopted, and the model is trained more clearly, so that the model has relatively professional review ability.

The invention relates to the technical field of agricultural irrigation, and discloses an intelligent agricultural water-saving irrigation and fertilization device which comprises an irrigation box, sliding rails, an irrigation assembly, a self-walking stirring assembly, a scraping and blowing assembly and a cylindrical filter part, the irrigation box is arranged on the two sliding rails, the cylindrical filter part is arranged in the irrigation box, the irrigation assembly is installed on one side of the irrigation box, and the self-walking stirring assembly is installed on the other side of the irrigation box. The spraying device is used for spraying water and fertilizer to crops; the self-walking stirring assembly comprises a rolling wheel, a rod type stirring piece and a driving piece. Water-soluble fertilizer water beads on the surfaces of seedlings are scraped and blown through the scraping and blowing assembly, water-soluble fertilizer attached to the surfaces of leaves and stalks of the seedlings can be effectively removed and shaken off to the bottoms of the seedlings, and therefore waste of the water-soluble fertilizer is reduced, meanwhile, the water-soluble fertilizer can directly act on root systems of the seedlings and is fully absorbed by crops, and the water-soluble fertilizer can be applied to the roots of the seedlings. The utilization rate of the water-soluble fertilizer is increased, and the problem of volatilization of nutritional ingredients caused by strong quick-acting property and short lasting period of the water-soluble fertilizer is reduced.

The invention relates to the technical field of environmental assessment, and provides a plateau region soil erosion attribution method, system, medium and equipment, and the method comprises the steps: calculating the soil erosion rate of each calculation unit in a research region through a soil erosion model based on multi-source geographic space data; the soil erosion rate is a product of a rainfall erosivity factor, a soil erodibility factor, a slope length gradient factor, a vegetation coverage management factor and a water and soil conservation measure factor; a rainfall erosivity factor, a soil erodibility factor, a slope length and gradient factor, a vegetation coverage management factor and / or a water and soil conservation measure factor are used as key driving factors, and the control degree of the key driving factors on the soil erosion rate change is calculated by adopting a logarithmic mean Dewei index method; wherein the control degree sets a weighting coefficient for each calculation unit in the calculation process, and the weighting coefficient is constructed based on the difference between each calculation unit and the preset reference region. And the independent contribution of each factor to the erosion change can be accurately separated.

The invention provides an irrigation district reservoir and canal system water resource joint optimization scheduling method and device based on partition decoupling, and the method comprises the steps: obtaining the topological information of a target irrigation district reservoir and canal system, carrying out the irrigation division, and determining the water supply and demand of a future time period; based on the topological information, aggregating and generalizing each reservoir and channel in the irrigation area reservoir and channel system into a plurality of aggregated reservoirs and aggregated channel systems according to a coupling relationship, and dividing the target irrigation area reservoir and channel system into a plurality of subareas; channel water distribution flow feasible regions of different types of aggregation channel systems are deduced step by step from bottom to top from the last-stage channel; a double-layer water resource joint optimization scheduling model is established, the upper layer takes the maximum sum of the ratio of the water supply amount to the water demand amount of each subarea as the optimization target, and the lower layer takes the shortest water delivery time and the minimum water delivery loss of each subarea as the optimization target; the model is solved, the optimal water supply amount of each partition and the flow of the reservoir and the channel of each partition are obtained, and a scheduling optimization scheme is obtained. The method can maximize the water-saving benefit of the irrigated area.

The invention relates to the technical field of water-saving irrigation, in particular to a drought risk management-based corn planting water-saving irrigation system, which comprises a crop stress state monitoring module for acquiring a corn canopy temperature and an environment temperature and calculating a temperature difference value between the canopy and the environment. According to the method, the actual stress state of the crop is quantified by acquiring the difference value between the corn canopy temperature and the environment temperature in real time, and the crop water stress index which is dynamically calculated is combined, so that the water stress identification precision and the response time efficiency are improved, and the problems of irrigation decision lag and blindness are avoided; further, the real evapotranspiration demand of crops is accurately judged by dynamically monitoring the change rate of latent heat flux, misjudgment possibly caused by single monitoring of temperature difference is avoided, and the irrigation demand judgment accuracy is ensured; meanwhile, the prices, the flows and the available amounts of different water sources are comprehensively optimized, the taking proportion of multiple water sources is configured with the lowest total irrigation cost as the standard, water source economical efficiency optimization becomes possible, and irrigation operation cost and resource consumption are effectively reduced.

The invention relates to the technical field of mountain afforestation, provides an efficient nursery stock planting method suitable for mountain afforestation, and aims at solving the problems that in existing mountain afforestation, planting is not standard, the survival rate is low, the water and soil conservation capacity is weak, and the labor intensity is high. The forest space layout is optimized, and the water and soil conservation capability is enhanced; the mellow soil and immature soil layered stacking and backfilling technology is adopted, the natural structure of the soil is recovered, and the root zone microenvironment quality is improved; a fertilizer isolation layer is arranged and degradable container seedlings are implanted, so that the risk of root burning is avoided, the integrity of root systems is protected, and the survival rate of the seedlings is remarkably increased; by combining root fixing water slow irrigation, water retention covering and slope water collection and soil conservation structures, natural rainfall is effectively utilized, evaporation and runoff are reduced, and water saving and drought resisting are achieved; the whole process flow is standard, the replicability is high, and the dependence on artificial experience is reduced.

The invention belongs to the technical field of sewage treatment and comprehensive utilization of water resources, and particularly relates to a reclaimed water reuse and rainwater collection and utilization system in an expressway service area. A sewage treatment, rainwater collection and water-saving irrigation integrated system is constructed, and the MBR process is emphatically applied to treat sewage. The system can effectively remove various pollutants in the sewage, so that the effluent reaches the reclaimed water reuse standard, and the sewage recycling is realized. Meanwhile, rainwater is efficiently collected and utilized, and the water demand of vegetation is accurately met in combination with an intelligent water-saving irrigation technology. The dependence of the service area on fresh water resources is reduced on the whole, the pollution of sewage discharge to the environment is reduced, the water resource management level is improved, remarkable economic, social and environmental benefits are achieved, and an innovative scheme is provided for sustainable utilization of the water resources in the small service area of the expressway.

The invention discloses a regional farmland water-saving irrigation and conventional irrigation classification and high-precision mapping method based on machine learning. The method comprises the following steps: S1, acquiring climate, geography, crops and remote sensing image information data related to a farmland in a research area; s2, selecting seven indexes including ELE, LS, ET, LAI, CI, DLST and LTH to represent water-saving irrigation (WI) and conventional irrigation (FI), performing binary segmentation by using a threshold method, obtaining classification of WI and FI under each index, and generating WI candidate samples; s3, WI and FI typical pixels are determined, and a training sample library is formed; s4, synthesizing a characteristic wave band as a classifier input characteristic; s5, based on the training sample library and classifier input features, training a classifier through a machine learning algorithm; and S6, applying the classifier to the characteristic wave band in the research area to obtain the classification and classification graph of the farmland WI and FI in the research area.

The invention discloses a multi-dimensional trade-off analysis method for watershed ecological service optimization, which belongs to the technical field of multi-dimensional trade-off analysis, and comprises the following steps: S1, adopting a multi-source heterogeneous data fusion algorithm, combining remote sensing, GIS (Geographic Information System), weather and social economic data, and extracting key ecological factors through a random forest; according to the method, Monte Carlo simulation is utilized to generate multiple groups of land utilization scenes, and key tradeoff pairs are identified in combination with principal component analysis, so that challenges of uncertainty and multi-target conflicts in ecological service optimization are effectively coped with; thousands of groups of land utilization patterns are generated through random sampling, ecological service values under different scenes are simulated, and the limitation of single scene hypothesis is avoided; principal component analysis eliminates dimensional differences through standardization processing, extracts dominant ecological service types, and provides a mathematical basis for quantification of a tradeoff relationship.