287 results about "Irrigation district" patented technology

The invention discloses an irrigation area scale irrigation water consumption monitoring method based on physical constraint machine learning, and is applied to the technical field of irrigation water consumption monitoring. Comprising the following steps: constructing a space-time continuous sequence of irrigation response characteristics of an irrigation area by using a multi-source data integration and assimilation technology; the irrigation water amount balance equation and the earth surface energy conservation law are used as regularization terms of physical constraints to be embedded into the training process of the long and short term memory deep learning model, so that an irrigation water amount prediction model is established; and dynamically estimating the irrigation water consumption of the irrigation area based on the irrigation water consumption prediction model obtained by training. According to the method, the water balance equation and the energy conservation law are embedded into the machine learning model, so that the model prediction result follows the basic physical law, and water consumption estimation violating the physical common sense is avoided. The introduction of the physical constraint improves the robustness and generalization ability of the model under an unconventional climate condition or a limited training data condition, and enhances the credibility and interpretability of a result.

The invention belongs to the technical field of Internet of Things prediction, and discloses a soil moisture content prediction method and system based on a BiLSTM-Transform dynamic weight hybrid architecture, and the method comprises the steps: collecting an observation data set of soil moisture content influence factors of an irrigation region, the observation data set comprising a meteorological element sequence and a soil parameter sequence; the method comprises the following steps: collecting time series data of soil moisture content influence factors, carrying out noise reduction processing on the time series data by adopting a wavelet noise reduction method to obtain noise reduction data, and filling missing values of the noise reduction data by adopting a linear interpolation method to obtain a continuous data set. According to the method, a feature fusion strategy is adaptively adjusted through a dynamic weight mechanism, the time sequence modeling capability of soil moisture content prediction is remarkably improved, parameter quantities are compressed while the prediction precision is kept, the feasibility of deployment on edge computing equipment is achieved, and the constructed framework has the advantages of improving the stability of a prediction result and improving the prediction efficiency. And the prediction result error of the soil moisture content can be effectively reduced.

The invention relates to a multi-source data driven farmland irrigation decision-making method and device, equipment and a medium. The method comprises the following steps: acquiring multi-source heterogeneous data; carrying out fusion processing on the multi-source heterogeneous data, and constructing a unified farmland information database; performing spatial analysis on the data in the farmland information database; based on the analysis result, a preliminary irrigation prescription scheme is generated in combination with soil variation information and a crop water demand rule; on the basis of the preliminary irrigation prescription scheme, dividing the farmland into different irrigation areas, and calculating to obtain differential irrigation parameters of each irrigation area; integrating the differentiated irrigation parameters to obtain a differentiated irrigation strategy corresponding to each irrigation area; and dynamically optimizing a farmland irrigation decision based on each irrigation strategy. By adopting the method, multi-source data such as soil humidity, meteorological conditions and crop growth states can be effectively integrated, and a decision-making method capable of analyzing and generating an optimal irrigation scheme in real time is constructed.

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 ditch drainage-farmland waterlogging simulation evaluation method. The method comprises the following steps: S1, obtaining meteorological and hydrological data, DEM data, drainage facility vector data and land utilization classification data of a target area; s2, generalizing a drainage system of the irrigation area, and generating nodes, drainage channels and sub catchment area. Shp files; s3, converting the. Shp file into an. Inp file, constructing a parameterized model, and performing parameter calibration and verification on the model; s4, simulating waterlogging conditions under different rainfall and channel siltation situations; s5, extracting overflow node data, and performing flood inundation analysis; and S6, generating a flood risk density map according to the overflow node data. The invention further discloses an irrigation area ditch drainage-farmland waterlogging simulation evaluation system. According to the irrigation area ditch drainage-farmland waterlogging simulation evaluation method and system disclosed by the invention, the problem that ditch drainage simulation and farmland waterlogging risk evaluation cannot be carried out under an irrigation area waterlogging disaster in the prior art is solved.

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 a rice irrigation district irrigation amount simulation method and system, and the method comprises the steps: taking a region controlled by a backbone channel and a drainage main ditch as a standard for dividing sub-units based on a DEM and a digital canal system, carrying out the grid division of the sub-units, and obtaining an irrigation district sub-basin division result; constructing a dynamic irrigation triggering mechanism of each irrigation area sub-basin, and determining a multi-water-source cooperative scheduling scheme of each irrigation area sub-basin based on the division result of the irrigation area sub-basin; and when each irrigation sub-basin is irrigated according to the multi-water-source cooperative scheduling scheme, calculating the canal system leakage amount in each irrigation sub-basin, and determining a water distribution scheme of each irrigation sub-basin according to the canal system leakage amount. The method can be used for quickly and accurately simulating the irrigation amount and the runoff volume of the rice irrigation area, and provides a scientific basis for formulating agricultural management measures and screening water-saving high-yield technical modes.

The invention relates to the technical field of irrigation area water and soil resource management, and discloses an irrigation plot multi-element information coding method comprising the following steps: S1, plot coding architecture design; s2, constructing a parcel code segmentation parameter database; s3, collecting and storing multi-element information; and S4, determining the land parcel code. According to the method, the multi-element information of the irrigation district canal system and the plot is visually and conveniently expressed by adopting the limited character length according to the established rule, the water consumption information and the plot multivariate attribute information on each plot are fully combined, and a unique identification code is compiled for each plot for identity recognition of the plot; water and soil resource management efficiency and scientific management level of the irrigation area are improved, and digital twinborn construction and modernization development of the irrigation area are assisted.

The invention relates to the technical field of agricultural irrigation, in particular to a precision agricultural drip irrigation system based on intelligent sensing and a control method thereof, and the system comprises an intelligent sensing module which is used for collecting meteorological data, soil humidity data and soil temperature data of different irrigation areas; the model prediction module comprises a moisture diffusion model and a rainfall prediction model which are respectively used for performing soil moisture diffusion prediction and rainfall prediction on different irrigation areas by utilizing the soil humidity data, the environment temperature data and the meteorological data, and outputting prediction results; the drip irrigation control module is used for controlling operation of a drip irrigation pump; the drip irrigation control module is further used for controlling electromagnetic valves in drip irrigation pipes in different irrigation areas to be opened and closed by utilizing an intelligent control mechanism according to the prediction result of the model prediction module so as to adjust the irrigation volumes in the different irrigation areas; the soil moisture diffusion rule can be predicted, repeated irrigation and irrigation blind areas are reduced, and waste of water resources is reduced.

The invention relates to spray irrigation equipment and method, and belongs to the technical field of irrigation, a plurality of spray irrigation units are arranged on the side face of an irrigation area at intervals, and the spray irrigation area of the spray irrigation units completely covers the irrigation area; the water tower is arranged on the outer side of the irrigation area, connected with the sprinkling irrigation unit through a pipeline and used for storing a water source, and the water source is naturally injected into the sprinkling irrigation unit through the height difference between the water tower and the sprinkling irrigation unit; the air compressor is arranged on the outer side of the irrigation area, the air compressor is connected with the spray irrigation unit through a pipeline, and compressed air generated by the air compressor generates negative pressure in the spray irrigation unit to suck out a water source and scatter the water source at a high speed and spray the water source to the irrigation area; the technical problem that in the prior art, soluble minerals form incrustation, a small-interval structure is blocked, and the sprinkling irrigation stability is affected can be solved.

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 utility model relates to the technical field of sewage treatment, and discloses a water-saving and pollution-reducing ecological circulation treatment system for an irrigation area, which comprises a main channel, a branch channel, a water diversion channel, the irrigation area, a channel tail ecological pool system, a water lifting channel and a pump station, the branch channel is arranged on one side of the main channel, one end of the branch channel is connected with the main channel, and the other end of the branch channel is connected with the water diversion channel. The water inlet end of the water diversion channel is connected with the first water outlet end of the branch channel, the water outlet end of the water diversion channel is connected with the second water outlet end of the branch channel, the irrigation area is located between the branch channel and the water diversion channel, and the water outlet end of the water lifting channel is connected with the branch channel; the water-saving and pollution-reducing ecological cycle treatment system for the irrigation area solves the problems that existing rural domestic sewage treatment has pollution risks, lacks high-quality real-time monitoring data and irrigation water demand prediction and cannot meet the requirement for timely monitoring water quality pollution or change trend.

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 relates to Internet of Things agricultural spraying irrigation equipment for intelligent agriculture, and belongs to the technical field of agricultural irrigation, the Internet of Things agricultural spraying irrigation equipment comprises irrigation equipment for agricultural spraying, and the irrigation equipment comprises an irrigation assembly and a water delivery assembly arranged on the bottom side of the irrigation assembly; the water conveying assembly is provided with a transmission structure and a supporting assembly used for supporting. According to the internet-of-things agricultural spraying irrigation equipment for intelligent agriculture, the spraying pipe is transversely arranged, the communicating pipe is rotationally connected with the top water conveying pipe, when water enters the spraying pipe to overflow and is sprayed out of the spraying pipe, thrust generated by water flow drives the spraying pipe to rotate, the irrigation area can be enlarged, and irrigation is more uniform; the liquid medicine enters the expansion pipe, the expansion pipe provides sufficient space and time for further mixing of the liquid medicine and water, the liquid medicine and the water can be fully and evenly mixed, it is guaranteed that the liquid medicine can evenly act on an irrigation area during irrigation, and the irrigation effect and the utilization rate of the liquid medicine are improved.

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 provides an irrigation district engineering management method, device and equipment based on digital twinning and a medium, and belongs to the technical field of irrigation district engineering management.The method comprises the steps that irrigation district information data are collected and preprocessed; the method comprises the following steps: carrying out oblique photography on an irrigation area to collect image data of the irrigation area, constructing an irrigation area basic base map in combination with geographic information data of the irrigation area, introducing key elements of the irrigation area, carrying out three-dimensional digital modeling on the irrigation area, and introducing a BIM model of a hydraulic structure to obtain a digital twin irrigation area system; monitoring an irrigation district project through a digital twinborn irrigation district system; and according to the real-time irrigation district information data and the engineering management model, matching an irrigation district management scheduling instruction, sending the irrigation district management scheduling instruction to execution equipment of the hydraulic structure, and displaying the operation state of the corresponding hydraulic structure. According to the invention, by introducing digital twinning, refined and intelligent management of irrigation district engineering is realized, and the problems of insufficient water resource scheduling monitoring, low scheduling efficiency and high error rate in traditional irrigation district management are solved.

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 irrigation monitoring device (500) includes an area receiving unit (511) that receives the designation of an area, a water area identification data acquisition unit (512) that acquires water area identification data, which is image data observed by an observation satellite for an area including the received area and is used to identify water areas on the ground, and a filling amount estimation unit (513) that identifies an irrigation area, which is an area of ​​a paddy field being irrigated, by analyzing the water area identification data and estimates the amount of water filling into the groundwater volume in the identified irrigation area from an estimation model that estimates the water volume as the attributable filling amount due to irrigation. The irrigation monitoring device (500) can provide a device that estimates the amount of water filled as groundwater due to winter irrigation.

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.