312 results about "Water requirement" patented technology

The invention discloses an intelligent agricultural planting management method and system, and belongs to the technical field of intelligent agriculture, and the method comprises the steps of data layer construction, water and fertilizer prediction layer construction, planting optimization layer construction and agricultural planting management. The space-time adaptive water and fertilizer prediction layer construction method combining the crop physiological load and the crop growth stage is adopted, the water demand and nitrogen, phosphorus and potassium nutrient demands of crops in the future stage are accurately predicted, the crop growth state and environment changes are dynamically responded, the water and fertilizer demand difference in different growth stages is considered, and the water and fertilizer prediction efficiency is improved. The accuracy and applicability of prediction are improved through time-space fusion, and accurate fertilization can be realized; a planting optimization layer construction method combining digital twinborn and multi-objective optimization is adopted, a water and fertilizer management strategy is subjected to refined and dynamic optimization under the condition of considering a crop growth stage, a soil nutrient condition and a future weather condition, and an optimal management strategy capable of improving the yield, saving water and fertilizer resources and reducing the nitrogen leaching risk is generated.

The invention provides an irrigation district water resource scheduling optimization method based on cloud computing, and the method comprises the following steps: collecting irrigation district multi-source data in real time through a space-air-ground integrated sensing network, and uploading the data to a cloud platform after preprocessing; the method comprises the following steps: constructing digital twin bodies of an irrigation area in a cloud platform, dividing the irrigation area into a plurality of sub-areas according to water consumption attributes, and integrating hydraulics and hydrological agriculture models; real-time data and future weather information are fused, and a water demand prediction value is generated through a water demand prediction model by taking the sub-region as a unit; a scheduling scheme is generated by adopting a multi-objective optimization algorithm based on the predicted value, and the minimum economic benefit, water resource utilization rate and energy consumption are taken as optimization objectives; and performing simulation evaluation on the scheme by using the digital twinborn body, outputting a performance index aided decision, and finally determining an optimal scheduling scheme. According to the method, accurate prediction, dynamic optimization and intelligent scheduling of the water resources in the irrigation area are realized, and the utilization efficiency of the water resources and the irrigation management level are improved.

The invention relates to the technical field of fertilization and irrigation regulation and control, and discloses a fertilization and irrigation two-way regulation and control system under water demand and fertilizer demand coupling modeling, and the system constructs the fertilization and irrigation two-way regulation and control system based on the water demand and fertilizer demand coupling modeling. The multi-source data acquisition module is used for acquiring soil, crop growth period and meteorological data through a layered soil sensor, crop image acquisition equipment and a meteorological acquisition point; the water and fertilizer scheme generation module calculates irrigation amount, fertilization type and dosage based on data, and adjusts intervals in combination with temperature; the operation execution module controls the operation of the irrigation and fertilization equipment and records the state; and the data correction module compares the sensor with the sample data to generate a correction scheme. The system realizes accurate regulation and control through a closed loop of data acquisition, scheme generation, execution and correction, simultaneously covers equipment state monitoring and early warning, and ensures efficient fertilization and irrigation to adapt to crop requirements.

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 provides an irrigation district water diversion quantity multistage distribution method under total quantity index constraint, comprising the following steps: dividing an irrigation district into a plurality of calculation units based on an administrative division boundary and a canal system network; respectively calculating the initial water demand of each calculation unit under the living water demand, the industrial water demand, the agricultural water demand and the ecological water demand; based on the initial water demand and according to multiple water resource rigid constraint indexes, performing at least one round of checking and pressure reduction on the initial water demand of each calculation unit to obtain an initial distribution water amount of each calculation unit; and carrying out secondary distribution on surplus water generated after checking and pressure reduction, and compensating the calculation units of which the water demand is not met to obtain the final distribution water of each calculation unit. According to the method, fair, reasonable and efficient distribution of water resources in a complex system with cross coupling of administrative division and canal system networks is realized, and the problems of conflict between a scheme and actual management requirements, water consumption contradiction and the like caused by a traditional single-dimension distribution method are avoided.

The invention belongs to the technical field of irrigation management and control, and provides a multi-source sensing data-driven irrigation area water demand prediction and accurate water distribution method. The method comprises the steps of obtaining multi-source data of a target irrigation area when a preset irrigation condition is met; performing quantitative evaluation on the first soil water content data and the second soil water content data based on the meteorological data to determine respective confidence degrees, and giving dynamic weights based on the confidence degrees, the temporal and spatial variation characteristics and the actual condition of the irrigation area; performing fusion processing on the first soil water content data and the second soil water content data based on the dynamic weight to obtain third soil water content data; on the basis of the third soil water content data and the crop growth stage data of the target irrigation area, the water demand of the stage is predicted; and generating a control instruction of the intelligent valve of the water delivery canal system based on the water demand. The accuracy of water demand prediction can be remarkably improved, the problems of water resource waste and insufficient supply are reduced, and efficient utilization and scientific management of water resources in an irrigation area are achieved.

The invention relates to the technical field of intelligent agriculture, in particular to an intelligent water-saving irrigation system for intelligent agriculture, which comprises a multi-source heterogeneous sensing module for collecting farmland soil data, crop physiological data, meteorological environment data and irrigation equipment operation state data; the AI dynamic decision-making module constructs a TFT time sequence prediction model, calculates the real-time water demand and the ecological adaptation coefficient of crops by combining a crop physiological coupling algorithm, and dynamically generates a personalized irrigation scheme; the self-adaptive regulation and control module is used for implementing a personalized irrigation scheme and carrying out water, fertilizer and pesticide integrated precise putting and multi-water-source dynamic scheduling through a magnetic control driving mode and a flow closed-loop control algorithm; the irrigation effect feedback module verifies the execution effect of the personalized irrigation scheme in real time, and dynamically executes a feedback optimization action in combination with a preset deviation threshold value; and the block chain data security module performs encrypted storage and access traceability on the irrigation whole process data. Therefore, the problems of insufficient prediction accuracy, insufficient water, fertilizer and pesticide feeding precision and the like in the prior art are solved.

The invention discloses an irrigation index prediction method based on meteorological data and field moisture capacity, and relates to the technical field of intelligent agriculture, and the method comprises the steps: collecting real-time meteorological data, real-time soil volumetric water content data, soil matrix potential data and future precipitation forecast data, and carrying out quality control and time alignment processing to obtain a multi-source data set; the method comprises the following steps: calculating evapotranspiration of a reference crop according to real-time meteorological data, obtaining actual water demand of the crop in combination with a crop coefficient, calculating a moisture stress coefficient according to real-time soil volumetric water content data and a field moisture capacity static parameter value, and obtaining a basic irrigation demand index in combination with future precipitation forecast data. According to the method, the evapotranspiration amount is separated by adopting the Shuttleworth-Wallace model, the irrigation index integrating the crop evapotranspiration amount, the water deficit amount and the effective precipitation amount is generated on the basis of multi-period rolling water balance calculation and risk decision rules, and online calibration of soil parameters and optimization of irrigation decision are achieved.

The invention discloses an intelligent irrigation system and method for improving the utilization rate of cotton planting water resources, and the system comprises a data collection module which is used for obtaining the multi-source data of a cotton planting region in a preset time period, and carrying out the preprocessing of the multi-source data, so as to obtain a data set containing the three dimensions of soil, crops, and meteorology; the water demand prediction module is used for predicting the data set obtained by the data acquisition module by using a trained CNN-TCN-Attention model and generating a cotton field soil water demand; the irrigation module is used for formulating an intelligent irrigation strategy in combination with a cotton growth stage based on the data set obtained by the data acquisition module and the cotton field soil water demand predicted by the water demand prediction module, and irrigating a cotton planting area according to the intelligent irrigation strategy; the visual platform is used for monitoring the irrigation process in real time; efficient water saving and precise irrigation are achieved, and the utilization rate of cotton planting water resources is increased.

The invention discloses an intelligent irrigation regulation and control system and method for dynamic balance of water and salt in saline-alkali soil, and belongs to the technical field of intelligent agriculture. Comprising the following steps: collecting dynamic monitoring data influencing the water-salt dynamic state and storing the dynamic monitoring data in a basic database; calculating the crop evapotranspiration water demand based on the data of the basic database; in combination with the calculated crop evapotranspiration water demand and data of the basic database, salt profile estimation is achieved, a dynamic target salt threshold value is set, the self-adaptive leaching water amount is calculated, the salt return risk is evaluated, and an evaluation report at the end of the growth season is generated; based on all calculation and evaluation results, key strategy control parameters for guiding irrigation are generated and optimized by adopting a reinforcement learning algorithm; generating a self-adaptive irrigation strategy and auxiliary measure suggestions by combining all the obtained results and fusing weather forecast data; the irrigation strategy is converted into an irrigation and drainage executable instruction, and meanwhile, the execution state of irrigation and drainage is monitored to be used for achieving double-path feedback.

The invention provides a water plant raw water and clear water lifting pump station joint optimization energy-saving dispatching method and system for solving the problems that traditional pump station dispatching depends on artificial experience, global optimization is lacked, and energy waste is serious. Comprising the steps that a flow-lift and flow-efficiency relation model is established, and a variable frequency pump deduces a performance formula under any frequency based on the similarity law; in the first-stage optimization scheduling, the optimal flow of a water intake pumping station and the optimal water storage level of a clean water tank in each time period are determined by adopting a dynamic programming algorithm and taking the minimum total work of the system as a target, and the conditions of flow balance, water level constraint and the like are met; and in the second-stage optimization scheduling, the genetic algorithm is adopted to optimize the combination and operation frequency of the water pumps in each time period by taking the minimum total power of the pump set as a target, and a flow and lift deviation penalty term is introduced. According to the method, water taking, water storage and water supply whole-process collaborative optimization is achieved, the energy saving rate exceeds 10%, the operation cost is reduced, the method adapts to dynamic changes of the water source tide level and the water demand, and the dispatching intelligent level is improved.

The embodiment of the invention discloses a water resource dynamic evolution simulation analysis method and system based on digital twinning, and the method comprises the steps: calling a target drainage basin water resource monitoring data set from a preset distributed database cluster after obtaining the authorization authentication of a digital twinning server; performing space-time correlation processing on the data set and the meteorological environment data of the target watershed to obtain a conjoint analysis data set with a unified space-time reference system; performing time-space coupled water resource cyclic evolution simulation on the conjoint analysis data set through a preset MIKESHE model to obtain a target drainage basin water resource dynamic evolution process simulation result; according to the result, a quantitative influence simulation result of the climate change on the agricultural irrigation water resource of the target watershed is generated, the result comprises an irrigation water demand change trend, water resource supply and demand balance and agricultural water efficiency fluctuation characteristics, and a scientific basis is provided for agricultural irrigation water resource management.

The invention relates to the technical field of garden irrigation, in particular to a landscaping irrigation intelligent management system based on the Internet of Things, and the system comprises an environment monitoring module which is used for obtaining the real-time environment monitoring data, the real-time irrigation amount and the historical irrigation amount of a landscaping area; the data storage module is used for storing information of different vegetation units in the landscaping area and plant identity information corresponding to the vegetation units, the vegetation unit information comprises water and soil loss amount and soil water storage change amount, and the plant identity information comprises plant species and water amount required by plants; the irrigation prediction module is used for combining the real-time environment monitoring data, the real-time irrigation amount, the historical irrigation amount and the plant identity information through a prediction model to generate a predicted irrigation amount, adjusting the real-time irrigation amount based on the predicted irrigation amount, and generating an irrigation control instruction; the irrigation control module is used for issuing the irrigation control instruction to the corresponding irrigation equipment; and the self-maintenance diagnosis module is used for identifying the execution condition of the irrigation equipment according to the control instruction.

The invention discloses an intelligent greenhouse irrigation system taking water from air, which belongs to the field of agricultural engineering and intelligent control and comprises a greenhouse main body, a flow guide device, a photovoltaic module, a storage battery, a multi-source sensor, a digital twinborn module, an irrigation decision module, an intelligent execution module, a visual management platform and an ecological collaboration module. The greenhouse main body realizes cooling and condensed water collection by utilizing a surface functional coating, and water is guided into the water cellar through the flow guide device; the photovoltaic system cooperates with the phase-change material to realize power generation, heat storage and temperature compensation; the digital twinborn module is fused with multi-source data to construct a virtual model, and crop water demand and environment change are predicted; the irrigation decision module formulates an optimization strategy according to the water volume, the electric quantity and the prediction result; the intelligent execution module accurately controls irrigation and feeds back and adjusts in real time; and the ecological cooperation module is linked with regional environment data to realize overall management of greenhouse water consumption and ecological protection. According to the system, cooperative utilization of water resources and energy is achieved, and irrigation intellectualization is improved.

The invention relates to the technical field of digital rural agricultural treatment, in particular to a digital rural agricultural treatment method and system based on artificial intelligence. Obtaining a water demand characteristic parameter of the type of a crop currently planted in the Badzhou field from a crop database; superposing the spatial distribution data of the soil moisture content and the spatial distribution map layer to generate a Badzhou field moisture state map layer; the accurate water supplementing amount of the Badzhou field is obtained through water demand analysis of the Badzhou field with the water stress; an irrigation path is planned according to the position proximity relation and gradient information of all the Buddha fields in the Buddha field moisture state graph layer, and differential irrigation schemes are generated by combining the precise water supplementing amount corresponding to each Buddha field; sending the differential irrigation scheme to irrigation execution equipment, and supplementing water to each palm field; the problem that precise irrigation is difficult due to scattered distribution and large environmental difference of the palm field in the mountainous area is effectively solved.

The invention relates to the technical field of irrigation prediction, in particular to a soil moisture content-based irrigation water consumption prediction method. According to the method, the water consumption rate is calculated by synchronously obtaining the photosynthetic radiation intensity and the matrix water content in a sliding time window; determining a load index representing moisture extraction resistance based on a mean ratio of radiation to consumption rate, and constructing a fluctuation transmission index reflecting matrix hydraulic connectivity based on a ratio of variation coefficients of the radiation and the consumption rate; combining the two indexes to generate a hydraulic blocking risk coefficient for identifying recessive drought caused by capillary fracture; and finally, predicting the actual water demand according to the risk coefficient and the preset maximum irrigation amount. According to the method, physiological regulation of crops and physical water shortage of the substrate can be effectively distinguished, the judgment accuracy of the microcosmic hydraulic communication state of the substrate is remarkably improved, then irrigation water consumption prediction is more targeted and timeliness, and mistaken irrigation or leakage irrigation is avoided.

The invention provides a green concrete mix proportion optimization method and system, and relates to the technical field of mix proportion optimizing.The green concrete mix proportion optimization method comprises the steps that firstly, the dosage of cement, fly ash, slag powder, water and a water reducing agent serves as variables, the material cost and the predicted compressive strength serve as targets, and a Pareto solution set is generated through a multi-target optimization algorithm to serve as a preliminary scheme pool; thirdly, calculating the carbon cost efficiency of other schemes by taking the scheme with the lowest cost as a benchmark, and screening out a potential optimization scheme; then, through Monte Carlo simulation, considering the fluctuation of the water demand ratio of the fly ash, the activity index of the slag powder and the water-reducing rate of the water reducing agent, and evaluating the variable coefficient of the strength of each scheme so as to measure the robustness; and finally, carrying out weighted scoring on the normalized carbon cost efficiency and variation coefficient, and sorting according to a comprehensive score to select an optimal mix proportion. According to the method, the economical efficiency, the environmental protection property and the production robustness are comprehensively optimized on the premise of ensuring the performance of the concrete.

The invention discloses a timed and quantitative full-automatic intelligent water replenishing method and system, and relates to the technical field of intelligent water replenishment, and the method comprises the steps: generating a dynamic water replenishing control signal based on municipal pipe network pressure data, water tank liquid level height and water replenishing flow data which are monitored in real time; dividing and defining a water supplementing flow threshold range of a corresponding time period according to a preset time period, adjusting the opening degree of an electric adjusting valve based on the dynamic water supplementing control signal, supplementing water, and when it is monitored that the pressure of the municipal pipe network is lower than a preset protection threshold value, attenuating the water supplementing flow through a dynamic pressure compensation mechanism, and maintaining the stability of the pressure of the pipe network; predicting the water demand in the future time period, updating the target liquid level, and when the liquid level of the water tank reaches the target liquid level, triggering a redundancy protection mechanism to forcibly stop water replenishing. By introducing a dynamic pressure compensation mechanism, flow regulation and chaos disturbance factor feedback, the pipe network pressure stability, the water replenishing flow regulation precision and the response speed are optimized, the actual water use requirement is met, and the safety and the energy efficiency are improved.

The invention discloses an intelligent management method based on landscaping plant irrigation, and relates to the technical field of landscaping management, and the intelligent management method comprises the following steps: obtaining multi-source real-time data of a landscaping area, and based on terrain elevation data and plant physiological data, in each irrigation grid unit, carrying out the irrigation of the landscaping area; the method has the advantages that it is ensured that the units are accurately matched with the surface fluctuation and the plant water demand difference, in each grid, in combination with soil characteristics and meteorological data, the soil moisture migration simulation result and the plant physiological data are combined, and the plant moisture migration simulation result and the plant physiological data are combined to control the irrigation equipment to execute operation. According to the method, the soil moisture kinetic equation coupled with the root system water absorption function is used for finely simulating moisture migration, the problem of uneven local irrigation caused by terrain complexity and plant water demand space difference is effectively solved, the water resource space configuration precision is remarkably improved, and a scientific foundation is laid for accurate irrigation decision making.

The invention relates to the technical field of tobacco seedling raising, and discloses a dry-wet alternation tobacco seedling raising method, which comprises the following steps: performing water control management on a seedling raising pond for culturing tobacco seedlings in a periodic circulation mode, performing dry-wet alternation in each period, and realizing dry-wet alternation by sequentially performing a water inlet stage, a water leakage stage and a drought stage in each period. The tobacco seedling root toughness, stress resistance and adaptive capacity can be improved, and the tobacco seedling returning speed and the early-growing and quick-sprouting progress are accelerated. According to the actual water requirement rule of tobacco seedling root growth, the drought alternating seedling raising water control method is provided by combining the characteristics of tobacco seedlings, and the seedling raising quality is greatly improved. Moreover, according to the method, the temperature and humidity changes of the seedling raising substrate are monitored in real time, so that effective control over crop growth is achieved. Water control is implemented by using water leakage and natural permeation theories, so that the use and energy consumption of natural resources are reduced, the aim of simply and conveniently implementing healthy seedling culture is fulfilled, and the cost is reduced.

The invention provides a water conservancy irrigation water intelligent scheduling method based on big data analysis, and the method comprises the steps: obtaining soil moisture content real-time data, meteorological dynamic data, crop growth cycle data and water source water supply record data of an irrigation region, and carrying out the time-space correlation fusion processing, and obtaining a standardized multi-source data set; feature extraction is carried out on the standardized multi-source data set, a water demand prediction model is input for prediction, and the accurate water demand of the irrigation area is obtained; acquiring real-time water supply amount of a water source and water delivery efficiency data of an irrigation pipe network, and performing supply-demand balance analysis on the accurate water demand, the real-time water supply amount of the water source and the water delivery efficiency data of the irrigation pipe network to obtain a dynamic irrigation distribution scheme sorted according to crop water shortage sensitivity; and performing deviation analysis on execution process data of the dynamic irrigation distribution scheme and post-irrigation soil moisture content feedback data, and feeding back to the water demand prediction model for parameter correction. According to the invention, the defects of inaccurate water demand prediction and low water resource distribution efficiency are overcome.

The invention provides a soil improvement method for a sugarcane seedling seedbed. The soil improvement method comprises the following steps that a small-particle-size water-retaining agent containing a water-absorbing component and a biodegradable natural fiber material is spread on the surface layer of soil, and a large-particle-size water-retaining agent containing a water-absorbing component and a biodegradable natural fiber material is spread in a root zone. The water-retaining agents with different particle sizes and mixed with biodegradable natural fibers are spread in a layered manner, so that fine regulation and control can be performed according to the water requirements of different depths of the seedbed. The small-particle-size water-retaining agent is distributed on the surface layer, can rapidly absorb rainfall or irrigation water, reduces surface water evaporation, effectively inhibits weed growth, and meanwhile is not prone to being washed away by rainwater due to the small particle size. The large-particle-size water-retaining agent is concentrated in the root zone, has higher water-retaining capacity, can continuously provide stable water for the root system, and avoids wilting of the root zone due to water shortage. The biodegradable natural fibers are mixed, so that the water-retaining agent is expanded to form a porous structure, and root respiration and healthy growth are promoted.

The invention relates to the technical field of agricultural irrigation control, in particular to an intelligent cotton irrigation control method and system based on stem flow data, and the method comprises the following steps: collecting data, calculating a stem flow rate, constructing a monitoring data set, extracting morning data, calculating a morning optical flow conversion coefficient, deducing a noon theoretical potential stem flow rate, and calculating a noon optical flow conversion coefficient. Comparing the theoretical value with the actual value to calculate the instantaneous deficit depth, calculating the deficit width based on the duration continuously lower than the theoretical value, screening the maximum depression depth, multiplying the maximum depression depth by the deficit width to calculate the pore closing resistance index, and constructing an opening instruction when the index is greater than a threshold value. According to the method, the potential rate is deduced through the morning conversion relation, the deficit depth and width are quantified, the pore closing resistance index is calculated to evaluate water stress, the instruction is triggered based on the physiological response, water demand diagnosis is achieved, timely water supplementing is ensured, the irrigation precision is improved, and the photosynthetic efficiency is guaranteed.

The invention relates to the technical field of intelligent irrigation, and discloses an intelligent irrigation system for a fruit tree planting greenhouse. The system comprises a multi-dimensional data acquisition module, a data fusion processing module, an irrigation decision module and an irrigation control execution module which are connected in sequence. The system obtains a root soil image, a leaf surface temperature distribution map and stem micro-deformation data, and performs multi-dimensional fusion calculation to generate a spatial water potential distribution map capable of representing the overall moisture condition of crops. And calculating specific regional water demand and preferential irrigation sites based on the map, and further driving an execution terminal to realize precise irrigation. According to the method, the physiological water demand signal of the crop can be responded, the spatial difference of water stress can be identified, the limitation that the traditional technology depends on single soil information is overcome, the crossing from environment monitoring to crop body sensing is realized, and the irrigation accuracy and the water resource utilization efficiency are improved.

The invention relates to the technical field of agricultural irrigation, in particular to an agricultural irrigation intelligent monitoring system based on multi-modal data. The system comprises a data acquisition module for acquiring humidity data in a period by using a humidity sensor on each area of a farmland to form a humidity sequence; acquiring different types of irrigation data of each time of irrigation in different regional periods; the region similarity analysis module is used for acquiring the soil state similarity of the two regions according to the humidity difference and the irrigation data difference in the periods of the two regions; the clustering analysis module is used for clustering all the regions to obtain different class clusters; the areas in one class cluster form a to-be-analyzed area; and the water demand analysis module obtains the final water demand coefficient of the to-be-analyzed region, constructs a water demand model, and then brings the area of the to-be-analyzed region and the final water demand coefficient into the water demand model to obtain the water demand of the to-be-analyzed region. The method can accurately determine the amount of water needing to be irrigated in each to-be-analyzed area.

The invention relates to the technical field of agricultural irrigation, in particular to a farmland irrigation drainage dike which comprises a drainage channel, dikes are installed on the inner bottom wall of the drainage channel in the water flow direction at intervals, the height of the dikes is 10 centimeters higher than the height of a water inlet of the drainage channel, drainage pipes are installed in the dikes in a penetrating mode, and gates are installed on the drainage channel. A filtering part is arranged at a water inlet of the drainage channel; the drainage channel is divided into a plurality of independent irrigation units through the arrangement of the multiple dams, each dam is 10 centimeters higher than the water inlet, when the water level reaches the height of the dam, redundant water automatically overflows, the water amount can be flexibly adjusted according to the water requirement of different crops, it is ensured that water enters each land evenly, and uneven drought and flood are avoided.

The present application relates to the field of crop cultivation and soil improvement technology, and discloses a wheat-corn-sunflower-legume green manure crop rotation carbon fixation and water saving method suitable for arid irrigation areas, which comprises wheat planting, corn planting, sunflower planting and legume green manure planting. The present application replaces traditional flooding irrigation with high-frequency low-amount drip irrigation mode, combines with precise water supply according to the water requirement characteristics of each crop growth period, and avoids invalid irrigation. Meanwhile, through straw returning to field, soil water evaporation is reduced, and soil conservation capacity is improved. Moreover, the present application constructs a double carbon fixation path of straw returning to field and green manure turning, straw is crushed and returned to field, organic carbon is input into soil every year, legume green manure is turned and decomposed, and soil organic matter content is improved. The present application also reduces nitrogen fertilizer application through symbiotic nitrogen fixation of legume green manure and rhizobium, protects soil microbial activity, optimizes soil carbon cycle, relieves soil degradation, and improves long-term carbon fixation potential of soil.

This invention relates to the field of remote control technology for plant irrigation, and discloses a remote control method for irrigation of plants under bridges based on the Internet of Things. This method collects soil moisture gradient, light intensity distribution, and air temperature and humidity stratification data through a three-dimensional gridded sensor array, constructs a heterogeneous transmission network based on LoRaWAN and NB-IoT to achieve dynamic compression and encrypted transmission, establishes a digital twin model integrating BIM and point cloud data on a cloud platform, uses a fuzzy neural network to predict plant water requirements and generate zonal irrigation decisions, and performs timing optimization scheduling of multi-level PWM commands through an edge computing gateway to control a modular solenoid valve array to perform precise irrigation. This method solves the technical problems of insufficient environmental parameter acquisition dimensions, poor data transmission stability, limited dynamic control adaptability, and lack of system collaborative control capabilities.

The utility model provides a drip irrigation emitter for blueberry planting, which relates to the technical field of blueberry planting and comprises a water tank and a cover plate. The water containing tank is fixedly arranged in soil and is provided with a plurality of water outlet holes; the cover plate is rotatably arranged on the water containing tank in a covering mode and provided with a plurality of plugs, the cover plate is rotated to drive the plugs to plug different numbers of water outlet holes, and a multi-gear water outlet amount adjusting structure is formed. The water containing tank and the cover plate are annular and hollow in the middle, a plurality of inserting rods used for being inserted into soil are arranged at the bottom of the water containing tank, blueberry plants are arranged at the hollow positions of the water containing tank and the cover plate in a sleeving mode, the inserting rods are inserted into the soil, and water outlet holes in the bottom of the water containing tank are formed around the plants. The water can be adjusted according to different plant water demands, and the operation is simple and convenient.

This invention discloses an agricultural water resource optimization method based on crop water requirement and multi-objective optimization. The method includes: S1 Constructing a multi-objective programming model that maximizes crop yield, irrigation water productivity, and minimizes planting water costs; using the Zimmerman method to transform the multi-objective programming model into a deterministic single-objective model; S2 Reading monitoring data collected in the current monitoring period and monitoring data from the previous monitoring period corresponding to periods not collected in the current monitoring period; the monitoring period includes a complete planting cycle for corn and wheat; S3 Inputting all monitoring data into the deterministic single-objective model and solving the single-objective model using Lingo programming to obtain the irrigation amount for corn and wheat at each growth stage within the current monitoring period; S4 Using the irrigation amount obtained in step S3 for the corresponding growth stage of corn and wheat as the guiding irrigation amount for the current growth stage of corn and wheat, based on their current growth stage.