209 results about "Irrigation district" patented technology

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 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 conservancy monitoring, and provides an intelligent water conservancy monitoring method for an irrigation area and related equipment thereof. Water body boundary extraction is carried out on remote sensing image data to obtain an initial water body boundary data set, time sequence interpolation processing is carried out on the initial water body boundary data set to obtain a water body change trend data set, and soil moisture content prediction deduction is carried out according to a satellite cloud picture and the water body change trend data set to generate a soil moisture content prediction data set. Performing water level and area fitting on the regional DEM according to the water body change trend data set to construct a water storage capacity model, and performing crop water demand calculation according to regional data and crop data to obtain a crop water demand matrix data set; and performing constrained programming according to the soil moisture content prediction data set, the crop water demand matrix data set and the water storage capacity model to obtain a multi-target irrigation scheduling decision set. According to the application, dynamic balance between irrigation requirements and water resource supply is realized through multi-level and multi-source data fusion and intelligent scheduling.

The invention discloses an irrigation area data anomaly analysis method and a server, and relates to the field of data anomaly analysis, and the method comprises the steps: obtaining irrigation area canal system topological data and sensor deployment information, and constructing a topological cause and effect graph; acquiring time sequence data for the sensor pair in the topological causal diagram, and determining a time-space lag parameter; constructing a physical conduction prediction model; acquiring actual measurement time sequence data of the downstream sensor and real-time time sequence data of the upstream sensor, and generating physical expected time sequence data of the downstream sensor according to the real-time time sequence data and the time-space lag parameter by using the physical conduction prediction model; and calculating a residual sequence based on the actual measurement time sequence data and the physical expected time sequence data of the downstream sensor, and determining whether the data of the downstream sensor is abnormal or not based on the residual sequence. The problem of high false alarm rate in irrigation area application can be effectively solved.

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 discloses an irrigation district water distribution scheduling method and device and a medium, belongs to the field of irrigation district management, and aims to solve the problem that accurate irrigation cannot be uniformly and efficiently carried out, and the method comprises the following steps: determining a digital elevation model and a crop planting distribution diagram of an irrigation district; according to the digital elevation model and the crop planting distribution map, determining different irrigation subareas of the irrigation area, and a water delivery energy consumption coefficient, a crop suitability coefficient and a subarea water demand critical period of each irrigation subarea; constructing a water delivery energy matrix of the irrigation area according to the water delivery energy consumption coefficient of each irrigation subarea and the irrigation water demand in the irrigation period; determining a rotation irrigation group of the irrigation area according to the water delivery energy weight combination and the water delivery energy matrix of each irrigation subarea in the current irrigation period; and determining the irrigation time sequence of the rotation irrigation group according to the crop suitability coefficient of each irrigation subarea and the subarea water demand critical period. And water distribution in the irrigated area can be more efficiently and reasonably carried out.

The invention provides an irrigation area sediment deposition prediction method and system, computer equipment and a storage medium, and belongs to the field of water conservancy project intellectualization, and the method comprises the steps: collecting historical hydrological data, real-time monitoring data and remote sensing observation data of a to-be-predicted irrigation area; the method comprises the following steps: resampling historical hydrological data and real-time monitoring data, carrying out forward filling completion on missing data, filling remote sensing observation data into a unified time axis, and filling missing spatial features based on spatial feature values of an adjacent time reference to obtain multi-source data with time-space alignment; extracting features of the multi-source data to obtain four features; and combining the four features and calculating correlation weights among the features so as to determine the sediment flow, the sediment concentration and the sediment flow velocity of the to-be-predicted irrigation area. According to the method, aiming at the defect of non-uniform spatial and temporal distribution among multi-source data sources, spatial and temporal alignment is realized through time re-adoption and spatial feature completion, the input information can accurately reflect the sediment transportation process of an irrigation area, and the prediction accuracy is improved.

The invention discloses an irrigation water and fertilizer fine adjustment system and method, and relates to the technical field of agricultural irrigation adjustment, and the method comprises the steps of information collection and storage, visual feature recognition and growth stage matching, irrigation area division, water application amount and fertilization amount calculation, irrigation instruction generation and irrigation operation execution. According to the invention, crop information is collected and visual feature identification is carried out to determine a growth stage, a crop growth stage spatial distribution map is generated, and irrigation area division is carried out according to the map; water and fertility calculation is carried out according to the soil moisture content and the soil conductivity of the soil in the irrigation area to obtain the water application amount and the fertilizer application amount, finally, an irrigation instruction is generated according to the water application amount and the fertilizer application amount, irrigation operation is executed, accurate water and fertilizer supply for crops in different growth stages is achieved, and the irrigation water and fertilizer adjustment fineness is improved.

The invention discloses a digital twinborn irrigation district-oriented water resource efficient utilization and rice population quality comprehensive evaluation method and system, and relates to the technical field of irrigation district water resource efficient utilization and agricultural technology evaluation. Comprising the following steps: constructing a five-dimensional multi-level comprehensive evaluation index system, and determining a level framework; weighting the second-level indexes based on an analytic hierarchy process and calculating scores of the first-level indexes; a comprehensive integration model is established, the five first-level index scores serve as input, the nonlinear relation between the indexes is automatically learned, and an irrigation area comprehensive performance index is output; an evaluation system and a CatBoost model are integrated to a digital twinborn irrigation area platform, and multi-source data automatic access, model online reasoning and evaluation result space visualization are achieved. According to the method, the problems that an existing evaluation method is split in system, difficult in index quantification, depends on subjective authority assignment and cannot achieve dynamic spatialization display are solved, and intelligent and engineering decision support is provided for collaborative optimization of irrigation area water resources and crop production.

The invention provides an automatic irrigation device and method based on a soil humidity sensor, and relates to the technical field of water-saving sprinkling irrigation. The automatic irrigation device comprises a distributed soil humidity sensor network buried in soil of an area to be irrigated, a central controller connected with the distributed soil humidity sensor network and an irrigation execution unit electrically connected with the central controller. By arranging a distributed soil humidity sensor network and constructing a three-dimensional distribution model of soil moisture, the inherent defect that traditional single-point measurement is over-summarized is thoroughly overcome; by means of the automatic irrigation device, the real moisture conditions of each subarea and different depths in the irrigation area can be accurately mastered, so that independent and on-demand irrigation of each subarea is achieved, the high uniformity of the soil humidity of the whole field is effectively guaranteed, the optimal moisture environment is provided for crop growth, and the crop yield and quality are directly improved.

The invention relates to a random forest and model predictive control (RF-MPC) cooperation-based wheat water and fertilizer amount intelligent decision-making method and system, environmental data are collected in real time by deploying a sensor network module, and a multi-dimensional decision-making system comprising a crop growth stage model, a soil layered moisture dynamic model and a nutrient absorption efficiency prediction model is constructed. Wherein the random forest algorithm is used for predicting key environment parameters in the next eight days, and inputting a prediction result into the MPC controller; and the MPC controller dynamically solves an irrigation volume distribution scheme and an optimal ratio of nitrogen to phosphorus to potassium in the whole growth cycle through a rolling time domain optimization method based on 9 growth stages of wheat and terrain and illumination differences of an irrigation area. According to the system, by establishing a dynamic moisture balance equation of soil at different depths, accurate quantitative coupling of root system water absorption, irrigation supply and deep seepage is achieved; and the fertilization module dynamically optimizes the nitrogen-phosphorus-potassium ratio based on an irrigation event triggering mechanism, so that accurate matching of nutrient supply and demand is realized.

The invention relates to a safety monitoring method for an irrigation and drainage project operation state and an intelligent system, and belongs to the technical field of artificial intelligence. The method comprises the following steps: collecting and marking irrigation and drainage project operation monitoring data through a sensor, and constructing a training data set; completing data normalization by combining quantile and median robust scaling with adaptive nonlinear transformation, and mining and screening high-order interaction features by combining a mutual information theory and a gradient boosting decision tree; constructing a deep classification network fusing physical prior and adaptive feature interaction, introducing physical constraint and multi-scale feature fusion, and optimizing a model through adaptive marginal classification loss and physical feature manifold alignment loss; real-time data is preprocessed and then input into the model, and operation state grade classification and graded alarm are achieved. According to the method, data noise can be inhibited, a multi-index coupling relationship can be mined, the interpretability and robustness of the model can be improved by integrating a physical rule, irrigation and drainage project abnormity can be accurately identified and early warned, and the method is suitable for intelligent safety monitoring of an irrigation area.

The invention relates to the technical field of irrigation saline-alkali soil improvement, in particular to an irrigation saline-alkali soil improvement method based on straw adsorption and water conservancy regulation, which comprises the following steps: acquiring multi-depth soil parameters and surface meteorological data of an irrigation area, and establishing a soil water-salt dynamic migration coupling model; calculating a vertical moisture flux and a plowing layer net salt flux by using the model; calculating an accumulated salt return risk index to obtain a salt return risk grade; building a straw decomposition index by using multi-depth soil parameters; on the basis of the straw decomposition index, updating the soil water and salt dynamic migration coupling model; in response to the fact that the salt return risk level is a high risk, constructing an optimization objective function; resolving and optimizing the objective function to obtain an optimal irrigation strategy; outputting an optimal irrigation strategy to an irrigation control system, and feeding back the optimal irrigation strategy to the model as an irrigation rate; according to the invention, threats can be identified before a high-risk salt return event occurs, the timeliness and initiative of regulation and control are improved, and the balance between treatment benefits and economic cost is realized.

The invention discloses an irrigation decision determination method considering a multi-source water conversion process, and relates to the technical field of agricultural water conservancy irrigation, and the method comprises the steps: obtaining a multi-spectral image and a thermal infrared image of crops in a target irrigation region, calculating a vegetation index and a leaf area index, and combining with the actually measured growth vigor data of the crops, a growth vigor model of crops is constructed by establishing a mapping relation, the rainfall, the irrigation volume, the canal system infiltration replenishment volume and the groundwater capillary rise volume of a target irrigation area are obtained, and a soil moisture income and expenditure model is constructed based on a water circulation process. According to the method, a plurality of paths such as rainfall, irrigation, canal system leakage and groundwater capillary rise are considered through the constructed soil water volume income and expenditure model, crop physiological moisture inflection points are accurately recognized by simulating the root zone volumetric moisture content and growth vigor response curve, threshold control irrigation based on crop requirements is achieved, and the crop yield is improved. And the multi-source input and conversion process of the farmland hydrological system is comprehensively reflected.

The invention relates to an intelligent control method and system for high-pressure atomization irrigation and a storage medium of the intelligent control method and system, and aims to solve the problem that the quality is inconsistent due to the fact that traditional water and fertilizer management of high-value crops is difficult to sense the internal physiological state of the crops in real time. Randomly selecting a plurality of offering samples in each management partition for destructive sampling, and obtaining crop truth value data through physiological and biochemical detection; then, an irrigation rule base is established and dynamically updated based on the truth value data, and then variable control instructions are generated for the management partitions in combination with the real-time environment data; the invention further provides a system for implementing the method and a storage medium, accurate regulation and control starting from real demands of crop bodies are achieved, the consistency of crop quality and the resource utilization efficiency are effectively improved, and self-learning and predictive prevention and control capabilities are achieved.

The invention belongs to the technical field of remote sensing image processing agricultural information, and particularly relates to a DS-xNet-based multi-source remote sensing time sequence data cultivated land utilization current situation extraction method. According to the method, the cultivated land and the water body can still be reliably recognized under the cloud or fog condition by combining Sentinel-1 and Sentinel-2, missing detection and misjudgment caused by cloud shielding are reduced, sNET captures short-term dynamic conditions, and mNET matrix memory enhances long-term dependence modeling, so that the recognition precision of seasonal and interannual changes is improved, supervision is applied to a branch and fusion layer, and the recognition accuracy of the cultivated land and the water body is improved. According to the method, each branch can learn independent discrimination capability and can cooperatively improve fusion output, over-fitting is reduced, generalization capability is improved, training convergence is accelerated, channel splicing retains discrimination information of each modal in a fusion stage, modal information conflict or loss caused by direct early fusion is avoided, classification accuracy is improved, and classification efficiency is improved. Various optical and radar indexes are combined and used to enhance the distinguishing capability of paddy fields, irrigation areas, different crops and non-cultivated areas.

The present application discloses an agricultural irrigation method and system, a device, a medium, and a product. The method comprises: acquiring a farmland condition dataset of an area to be irrigated; on the basis of a comparison result between minimum soil moisture content data and farmland water-holding capacity data, determining whether to generate a first irrigation instruction, the first irrigation instruction being used for controlling on of a first solenoid valve and a first water pump which are located on a first pipe, and watering a farmland on the basis of the first irrigation instruction; on the basis of a comparison result between soil nutrition data and preset nutrition data, determining whether to generate a second irrigation instruction, the second irrigation instruction being used for controlling on of a second solenoid valve and a second water pump which are located on a second pipe, and fertilizing the farmland on the basis of the second irrigation instruction; and on the basis of a level of an expected crop disease index, determining whether to generate a third irrigation instruction, and applying pesticides to the farmland on the basis of the third irrigation instruction.

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 relates to the technical field of intelligent water conservancy, in particular to an irrigation area water demand prediction and scheduling system based on intelligent water conservancy, which comprises a disturbance identification module, a humidity sensing module, a deviation judgment module, an irrigation sequencing module and an instruction generation module. According to the method, the change degree of future weather forecast and weather data on that day is quantified to pre-judge the disturbance of the future environment, the soil moisture sensitive areas which are violently responded to the disturbance are dynamically screened out from the global irrigation area on the basis of the pre-judge, and the soil moisture sensitive areas which are violently responded to the disturbance are selected for the screened areas. Further combining with the ideal moisture demand of the crops at the current growth stage, analyzing the dynamic deviation trend between the actual soil humidity and the ideal value in the continuous time, thereby accurately identifying the land parcels really in the moisture supply deviation state, abandoning a fixed irrigation plan, and improving the irrigation efficiency. And acquiring physiological indexes such as evapotranspiration rate and leaf area index of the crops in the deviated area in real time, thereby judging the real urgent degree of the crops in each area to moisture and carrying out irrigation sequencing.

The invention relates to the technical field of edge calculation, in particular to a precise irrigation system and method based on a plant growth model and edge calculation, and the system comprises an environment perception fusion module, a growth state matching module, an edge water volume calculation module, an equipment instruction issuing module and a feedback cycle recognition module. According to the invention, continuous detection and unified processing are carried out on environmental data through edge nodes, data integrity and space mapping efficiency are improved, moisture absorption capability and root distribution are matched according to crop growth stage parameters, an area to be irrigated is accurately calibrated, and target water volume calculation is locally completed in combination with a real-time soil state. A time and flow matching structure is constructed, pertinence of irrigation control is improved, control instructions are executed through distributed control equipment, response behaviors are recorded, equipment state traceability is achieved, continuous feedback recognition is conducted on soil moisture changes after irrigation, dynamic adjustment of a closed loop is promoted, the system response speed and irrigation precision are improved, and the risk of resource waste is reduced.

The invention discloses an automatic farmland irrigation control system, and relates to the technical field of farmland irrigation. The farmland automatic irrigation control system comprises a time sequence state acquisition unit used for acquiring time sequence data of land, plants and environment states of each irrigation area in a farmland; the time sequence feature extraction unit is used for extracting time sequence feature data of each region on the basis of a pre-trained model; the judgment and analysis unit is used for calculating and analyzing an irrigation demand index of each area based on the extracted data and comparing the irrigation demand index with a preset demand interval; the time sequence state data acquisition unit is introduced, the land, plant and environment state data are collected and processed in real time, effective time sequence characteristics are extracted, the irrigation demand index is accurately calculated, the actual area, the soil moisture content and other parameters are combined, and the real-time monitoring of the irrigation demand index is achieved. The system can reasonably calculate the irrigation amount and duration, water resource waste is avoided, and therefore the water resource utilization efficiency is improved.

This invention discloses a smart irrigation management system based on soil and crop moisture status identification, belonging to the field of crop moisture status monitoring technology. The system includes: acquiring leaf electrophysiological signal sequences and multi-depth water potential parameters of the rhizosphere microdomain of the target crop; determining the onset time of water stress and its corresponding first characteristic frequency based on the leaf electrophysiological signal sequences; determining the active water-uptake layer and its corresponding second characteristic water potential based on the multi-depth water potential parameters; performing a coupled comparison based on the first characteristic frequency and the second characteristic water potential, and determining whether irrigation triggering conditions are met based on the comparison results. If the irrigation triggering conditions are met, a differentiated irrigation quota is determined for different irrigation areas. This invention determines irrigation triggering conditions by comparing the consistency and degree of deviation between the first and second deviation directions, avoiding premature or late irrigation caused by misjudgment based on a single indicator.

The invention provides an intelligent agricultural production control method and system based on artificial intelligence, and relates to the technical field of intelligent agriculture, and the method comprises the steps that S1, an unmanned plane carries out the real-time monitoring of a farmland every 10 minutes, and collects environment data, and the environment data comprises soil humidity, temperature, illumination intensity and air humidity; s2, analyzing the environmental data based on a deep learning algorithm and generating an irrigation control strategy; s3, automatically adjusting the operation parameters of the unmanned aerial vehicle according to the irrigation control strategy, wherein the operation parameters comprise irrigation time, irrigation water amount and irrigation area. According to the intelligent agricultural production control method and system based on artificial intelligence, real-time monitoring and data acquisition are performed on a farmland through the unmanned aerial vehicle, environmental data are analyzed by using a deep learning algorithm, and an irrigation control strategy is generated, so that accurate water resource management is realized, and the irrigation time, the irrigation water amount and the irrigation area are automatically adjusted; therefore, efficient use of water resources is ensured.

The application relates to an intelligent control method and system of high-pressure atomization irrigation and a storage medium thereof, and aims to solve the problem that traditional water and fertilizer management of high-value crops cannot realize real-time sensing of internal physiological states of crops, leading to inconsistent quality. The intelligent control method divides an irrigation area into multiple management partitions, randomly selects a plurality of sacrifice samples in each management partition, destructively samples the sacrifice samples, obtains true value data of crops through physiological and biochemical detection, establishes and dynamically updates an irrigation rule library based on the true value data, generates variable control instructions for each management partition in combination with real-time environmental data, and finally controls a high-pressure atomization sprinkler irrigation system to accurately execute. The application also provides a system and a storage medium for realizing the method, realizes accurate regulation and control starting from the real demand of crops, effectively improves the consistency of crop quality and the resource utilization efficiency, and has self-learning and predictive prevention and control capabilities.

This invention discloses an intelligent decision-making system for precise water allocation in agricultural irrigation districts based on crop water requirement coefficients. The system comprises three main modules: hardware acquisition and execution, software algorithms and modeling, and digital twin simulation and decision-making. These modules operate in a closed-loop logic of acquisition, processing, simulation, decision-making, execution, and feedback. The hardware module employs a four-dimensional collaborative acquisition, dual-mode transmission, and edge computing scheme. The software module incorporates algorithms and adaptation rules such as dual-factor coupling and dynamic water requirement coefficient correction. The digital twin module completes instruction issuance and parameter correction through full-element modeling, LOD optimization, and multi-objective decision-making. This invention, through dual-path feedback, digital twin collaboration, and multi-algorithm coordination, combined with dynamic water requirement coefficient correction, terraced field spatial adaptation, and soil water-salt coupling modeling, accurately matches plot requirements, balancing water conservation, crop adaptation, and energy consumption, thereby reducing irrigation district management costs and adapting to complex irrigation district operations.

The utility model provides a kind of anti-seepage channel construction structure of irrigation area water-saving project, relate to water channel construction technical field.The anti-seepage channel construction structure of irrigation area water-saving project, including first laying channel block, the outer wall of first laying channel block is inserted with second laying channel block.The utility model in need improves the shielding protection effect of anti-collapse layer after construction, and improves the anti-seismic buffering effect of water channel under daily use, insert rod is inserted into the inner side wall of connecting block, and rotate bolt is limited by the limiting effect of mounting nut, so that bolt is inserted into the inner wall of clamping groove, so that baffle and anti-collapse layer surface are fixed closely, and when telescopic column is extruded, it will drive telescopic column to slide along the inner wall of fixed column synchronously, and reciprocating extrusion force is generated to extrusion ball, reach the effect of force relief to the force received by telescopic column, improve the daily use life of water channel of irrigation area water-saving construction.

The application discloses a distributed brackish water resource utilization system, comprising: a water taking device, wherein the water takers of the water taking device are distributed in different water body areas and / or different areas of the same water body; a water treatment device integrated in a movable transfer equipment and connected with each water taking device through a pipeline; the water treatment device adjusts water treatment parameters based on the water inlet salinity and the target water outlet salinity; wherein the target water outlet salinity is lower than the salt tolerance threshold of the target irrigation crops, and the difference between the two is maintained within a set range; the water treatment device is also used for outputting the treated water to the target irrigation area with the target irrigation crops, or connecting with a drip irrigation system arranged in the target irrigation area; and a control device is in communication connection with the water treatment device and used for adjusting the water treatment parameters of the water treatment device. The distributed brackish water resource can be efficiently and flexibly utilized.

The invention belongs to the technical field of control, and particularly relates to an intelligent remote control method and system for an irrigation electric valve, and the method comprises the following steps: S1, obtaining a target soil humidity set value and a current soil humidity actual value of an irrigation region; based on the network communication quality parameters between the remote control terminal and the electric valve, the pipe network pressure sensor data and the historical instruction execution data, the predicted execution lag time of the current control period is obtained through calculation; s2, calculating a theoretical prediction value of the soil humidity by using a preset water and soil model according to the valve opening degree and the environmental parameters of the previous period, and obtaining a model deviation value between the theoretical prediction value and the current actual soil humidity value; by comprehensively analyzing the network quality, the pipe network pressure and the historical data, execution lag in the control process can be recognized and compensated in advance, excessive or insufficient irrigation caused by delay is avoided, and the control stability is improved.

This invention discloses a method for improving the accuracy of rice irrigation forecasts in irrigation districts based on digital twins, belonging to the field of agricultural water conservancy engineering technology. Based on digital twin technology, this invention divides the irrigation district into sub-regions using GIS and constructs a digital mapping model; it establishes a dynamic adaptive calculation system with multi-model selection, combining meteorological data completeness, rice growth period, and historical errors, and calculates the appropriate model using a dynamic weighted adaptation algorithm, obtaining the final value from the input data; it introduces soil moisture and field management correction coefficients to construct a dynamic calculation model; combined with the calculation of real-time water requirements for rice, it generates a refined irrigation scheduling plan for the sub-regions and achieves coordinated irrigation; and it corrects parameters using a gradient descent algorithm to ensure forecast accuracy. This method, through its dynamic adaptive calculation system, solves the accuracy problem in scenarios with missing data and has broad application value.

The invention discloses a water-saving precise irrigation control system and method, and relates to the technical field of agricultural irrigation, and the method comprises the steps: obtaining an irrigation region and an environment data set, preprocessing the environment data set, generating credible data, carrying out fluctuation evaluation on the credible data, and generating a data quality index; executing a gating decision on an irrigation mode judgment basis based on a data quality index, generating a partition target irrigation instruction set, executing infiltration capacity online identification on historical irrigation responses in the partition target irrigation instruction set and the environment data set, and generating a pulse irrigation sequence; and executing hydraulic state analysis on the pipe network flow pressure and the pump station operation data in the environmental data set, generating a water supply constraint, scheduling a pulse irrigation sequence based on the water supply constraint, and issuing the pulse irrigation sequence to a valve and a pump station to generate an irrigation execution result. According to the method, by forming water supply constraints, the strategy performability is improved, and meanwhile the field deviation is reduced.