737 results about "Water demand" patented technology

The invention relates to the technical field of agricultural intelligent irrigation, and discloses a high-standard farmland intelligent irrigation system based on Internet of Things and data analysis, and the system comprises a soil moisture content sensing module which collects data through a multi-source sensor to construct a three-dimensional soil moisture content distribution model, and generates a soil moisture content characteristic spectrum; the soil moisture content prediction module generates water demand prediction data based on the soil moisture content characteristic spectrum, the meteorological data and the crop growth stage; the irrigation strategy module fuses terrain elevation and pipe network pressure parameters to generate an irrigation control map; the equipment state monitoring module collects water pump current waveform and other data to generate equipment health degree parameters; the pipe network optimization module optimizes pipe network topology and generates an adjusting instruction; the multi-source data fusion module generates fusion evaluation indexes by using an evidence theory, an entropy weight method and the like; and the intelligent execution module generates an execution control instruction accordingly. All the modules cooperate to achieve precise irrigation, and the utilization efficiency of water resources and the intelligent level of farmland management are improved.

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

The invention discloses a multi-objective optimization water resource allocation scheduling method, which combines an LSTM-Prophet hybrid prediction model with an attention mechanism, synchronously captures climate periodicity, policy regulation sensitivity and industrial development tendency characteristics in water demand prediction, and improves water demand prediction precision through a genetic algorithm. Through an improved NSGA-III algorithm and a PSO collaborative optimization mechanism, the convergence problem of a high-dimensional target space is effectively solved in combination with a chaotic mapping technology, and the multi-target optimization efficiency is improved by 40% in cooperation with a dynamic weight adjustment strategy of deep reinforcement learning. And multi-scenario simulation verification of a scheduling scheme is realized by utilizing deep coupling of a digital twin system and a three-dimensional GIS, and a real-time feedback correction mechanism of a Markov decision process is realized. A finally constructed entropy weight-TOPSIS multi-dimensional evaluation system is combined with AR visualization and intelligent contract traceability technologies, and a Pareto optimal solution giving consideration to social fair, economic benefits and ecological integrity is provided for decision makers.

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 relates to the technical field of intelligent control, and discloses a water conservancy water resource dynamic scheduling method and system based on big data, and the method comprises the steps: collecting the collected real-time hydrological data, meteorological data and water demand data into multi-source real-time water conservancy data of a water conservancy region; based on a long-term dependency relationship in historical water resource scheduling data, determining a water consumption characteristic and a water resource space-time distribution rule; adaptively distributing water utilization priority weights of water resources to obtain water resource supply and demand conditions; mapping the water resource supply and demand condition to a scheduling rule base of historical water resource scheduling data to obtain a preliminary water resource scheduling scheme; the preliminary water resource scheduling scheme is corrected in real time in combination with the multi-source real-time water conservancy data, and a target water resource scheduling scheme is obtained; responding to the target water resource scheduling scheme, obtaining difference information between an actual response effect and an expected effect, and dynamically adjusting facility operation parameters according to the difference information; according to the invention, the efficiency of dynamic scheduling of water resources can be improved.

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 present application relates to the technical field of air conditioners, and particularly relates to an air conditioner control method and device, a multi-connected air conditioner and a storage medium, the present application determines the target heat recovery mode of the multi-connected air conditioner by judging the water tank temperature of the hot water tank, the heating energy demand and the total energy demand of each air conditioner indoor unit obtained when the multi-connected air conditioner simultaneously exists refrigeration and heating water demand, and then adjusts the communication state of the reversing device and the throttling element according to the target heat recovery mode, so as to achieve the purpose of simultaneously operating refrigeration and heating water by one heat pump system, and heat the water tank by the waste heat of air conditioner refrigeration, thereby avoiding the technical problem that the heating and heating water in the prior art multi-connected air conditioner are not simultaneously performed, and improving the use experience of the user.

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 present disclosure relates to an intelligent water precise irrigation control system and method for cultivation of fruit vegetables in solar greenhouses. The system includes: an information acquisition module for acquiring information by means of sensors, the acquired information including at least one of soil information, ground environment information, irrigation device use process information, and crop information; a water demand prediction module for inputting the acquired information into a deep neural network to predict water demand of fruit vegetables; and an irrigation control module for forming a control instruction according to the predicted water demand, so as to irrigate periodically and quantitatively. In this way, irrigation time and irrigation amount can be decided automatically according to growth conditions and environmental parameters in the whole process. Intelligent irrigation can be achieved with high working efficiency and accuracy, and the water-saving, quality-improved and efficiency-improved production of fruit vegetables can be achieved.

The invention relates to the field of direct drinking water of a fusion calculation model, and discloses a double-membrane mixing direct drinking water system and an operation method.The method comprises the steps that online data of a water supply end and a water quality monitoring end are collected for cleaning and time alignment, and a basic working condition data set is formed; the method comprises the following steps: establishing an operation characteristic model comprising water demand prediction, raw water quality prediction and membrane flux characteristic sub-models, calculating double-membrane target water yield and water quality indexes based on the model to generate a control parameter set, evaluating membrane pollution to generate an online cleaning task queue, performing joint simulation to generate a pressure stability control instruction set, and dynamically correcting the model. The conversion from passive response to active pre-judgment of the double-membrane mixing direct drinking water system is realized, and the operation stability, the water quality guarantee capability and the water-saving and energy-saving effects are improved.

The invention relates to the technical field of water resource scheduling, and discloses an intelligent water resource configuration and scheduling system and method, and the system comprises a data collection module which is used for collecting the related data of water resources in real time, including but not limited to the water level of a water source, the water quality, the meteorological data, the water demand of a user, and the like; the data processing and analysis module is used for cleaning and integrating the collected data by using a big data processing technology, and carrying out demand prediction and water resource supply and demand matching through an artificial intelligence algorithm; a scheduling decision module, an execution module and a feedback mechanism module. Multi-dimensional data such as water sources and weather are collected in real time, data processing and demand prediction are carried out through the artificial intelligence technology, and it is ensured that water resource scheduling can cope with rapidly-changed demand and supply conditions; through an optimization algorithm and a scheduling decision model, the water resource utilization efficiency is maximized, and the problems of excessive water pumping, resource waste and the like are avoided.

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 provides a water resource optimization scheduling method and system, computer equipment and a storage medium, and belongs to the field of water resource optimization scheduling, and the method comprises the steps: obtaining the local water supply amount, the department water demand amount and the water demand interval of each water receiving area; under the common constraint of the three parameters, the calculated economic output corresponding to the water resource input, the ecological service value of the water area, the water satisfaction quantitative result and the carbon emission in the water transfer process are used as optimization indexes, and the monthly scale is used as a time unit; according to an optimization result, a monthly water resource scheduling scheme is generated through iteration in sequence, and an annual water resource scheduling scheme is formed through integration; and determining a scheduling scheme with the optimal comprehensive benefit from the annual water resource scheduling schemes as a final water resource scheduling scheme. According to the method, the ecological benefit and social benefit of water transfer in the water transfer system can be coordinated, the ecological service value of a water area is remarkably improved and the carbon emission is reduced while the water demand of a water receiving area is ensured, and the comprehensive optimization of water resource scheduling is realized.

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 discloses an ecological bank protection intelligent irrigation control system and method based on multi-source data fusion, and relates to the field of irrigation control. Soil moisture content data is collected in real time, meteorological and vegetation growth information is combined, an irrigation strategy is dynamically adjusted through a prediction model, and accurate matching of vegetation water demand and water supply is ensured; meanwhile, sonar echoes are used for constructing underwater digital twin bodies, the state of a fish nest channel is monitored in real time through image recognition, when blockage is detected, the system immediately triggers a cleaning mechanism and synchronously optimizes an irrigation threshold value, and it is avoided that vegetation irrigation is affected due to the fact that water quality is affected by blockage; in the cleaning process, the main operation machine efficiently dredges the channel through rotary cleaning and water flow scouring, and the cleaning effect is verified in real time by means of digital twin bodies; in addition, the system further guarantees the irrigation continuity by presetting the cleaning time limit and a standby water source switching mechanism, effectively prevents the risk of bank slope instability, and remarkably improves the durability and ecological stability of the bank protection structure.

The utility model provides a double-water-outlet faucet structure. A first water pipe and a second water pipe which are independent are arranged in a stand column of the double-water-outlet faucet structure. The lower fixed connector is located at the axial upper end of the stand column, a first annular water channel on the peripheral side of the lower fixed connector is communicated with a first water pipe, the lower movable connector is rotationally arranged outside in a sleeving mode and provided with a first water outlet nozzle, the lower movable connector is sleeved with the lower rotary arm, an inner first water outlet channel is connected with the first water outlet nozzle, and a lower water outlet is formed in the tail end of the lower rotary arm. A second annular water channel on the peripheral side of the upper rotating arm is communicated with a second water pipe, the upper movable connector is arranged outside in a sleeved mode and provided with a second water outlet nozzle, the upper rotating arm is arranged outside in a sleeved mode, a second water outlet channel inside the upper rotating arm is connected with the second water outlet nozzle, and an upper water outlet is formed in the tail end of the upper rotating arm. Diversified water use requirements are met, water use convenience and flexibility are improved, the defect that installation is limited in places can be overcome, and the application range of faucet products is widened.

A gate linkage control method and device and a series water supply and power generation system are provided. The method comprises the following steps of: acquiring a water demand and current water level information of the series water supply and power generation system, the current water level information at least comprising current riverway water level information and current water diversion trunk canal water level information; determining a gate opening degree control strategy of a first water diversion gate and a second water diversion gate according to the water demand and the current water level information of the series water supply and power generation system; and carrying out linkage control on the first water diversion gate and the second water diversion gate according to the gate opening degree control strategy.

The invention relates to a system and a method for synergistically and accurately collecting required and consumed water of crops. A wireless transceiver is mounted at the top of the upper water supply pipe, a soil surface water content sensor and a soil deep water content sensor are mounted on the lower water supply pipe, and a buried irrigation pipe is communicated with the lower water supply pipe between the soil surface water content sensor and the soil deep water content sensor; a crop bottom-layer temperature and humidity sensor and a crop top-layer temperature and humidity sensor are mounted on the upper water supply pipe, and the upper water supply pipe between the crop bottom-layer temperature and humidity sensor and the crop top-layer temperature and humidity sensor is communicated with a stem and leaf irrigation pipe; the water demand is more accurately obtained, comprehensive control is implemented, and corresponding buried irrigation or spray irrigation is started according to different water demand values during irrigation operation, so that the purpose of optimal water saving is achieved.

The invention provides a water chamber mining area underground water resource allocation and decision analysis method, and relates to the technical field of mining area water resource management and intelligent decision, and the method comprises the steps: obtaining the perception data of a set region in a mine; constructing a steady-state seepage flow field of the mine goaf; constructing a water resource bearing capacity evaluation model; constructing water demand models of different areas of the mine; obtaining allocation demand distribution vectors and allocation demand sequences of different areas of the mine according to the water demand model; determining a priority allocation vector of each mine area by combining the allocation priorities of different areas of the mine; constructing a multi-objective optimization model, and calculating the multi-objective optimization model based on a pre-selected optimization algorithm to obtain an optimal water resource allocation strategy; and based on the optimal water resource allocation strategy, the water storage and drainage equipment is controlled to act, and the models or parameters are corrected according to execution result data. According to the scheme, dynamic correction and real-time response of the allocation strategy are realized, and accurate supply and scheduling optimization of underground water resources in the water-chamber-filled mining area are ensured.

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 discloses a long-distance water-salt dynamic regulation and control method and device, a medium and a product, and relates to the technical field of ecological management, and the method comprises the steps: periodically obtaining monitoring data through a real-time monitoring network; determining the opening degree of a flow valve based on a partial pressure technology according to the water pressure and flow data of each node of the water delivery pipe network, and dynamically adjusting the water pressure and flow of each shunt branch in the water delivery pipe network according to the opening degree of the flow valve; according to the water content of the artificial soil layer, a water supplementing strategy is determined based on a vegetation water demand model; according to the salinity value of the artificial soil layer, on the basis of a salinity accumulation risk model, salt control closed-loop control based on a high salinity water active suction band-off mechanism is carried out; according to the invention, dynamic, accurate and closed-loop management of moisture and salinity can be realized.

The invention discloses a mining area water resource optimal configuration method, which comprises the following steps: acquiring related data of mining area water resources, including water resources at a water supply end and water use sources at a water demand end; giving a water supply quality sequence and a water supply priority, and determining a graded and quality-divided water distribution rule according to the water supply quality sequence and the water supply priority; constructing a mining area water resource optimal configuration model; solving the mining area water resource optimal configuration model by using a multi-objective genetic algorithm to obtain a Pareto solution, namely an optimal configuration scheme of water resources; a mining area water resource optimal configuration model is constructed, an economic target is directly associated with water supply economic benefits, an environment target focuses on mine water displacement, and a fair target is measured by means of a Gini coefficient, so that consideration on constraint conditions is more comprehensive compared with the prior art; the feasibility and stability of a model solving result in practical application can be ensured, and the technical problem that the comprehensive utilization efficiency of water resources in a mining area is not high in the prior art is solved.

The invention relates to the technical field of water demand prediction, in particular to a crop water demand prediction method and system based on the agricultural Internet of Things, and is applied to accurate moisture management in complex soil structures such as terraces. And in combination with the dynamic weight of interlayer moisture migration, the moisture absorption matrix is updated in real time. Through time sequence sliding and cosine similarity calculation, a moisture retention time matrix is dynamically corrected, and accurate distribution of soil moisture is ensured. A graph theory algorithm is introduced to construct a directed graph model of a water flow path, an interference matrix is generated in combination with binary masks, matching of water absorption and water retention time is optimized, and the irrigation efficiency and the water resource utilization rate are improved. The irrigation strategy can be dynamically adjusted according to the moisture state between the soil layers, moisture waste is avoided, and the accuracy of crop growth moisture supply is improved.

The invention provides a farmland water demand accurate prediction method based on remote sensing data, and the method comprises the steps: firstly, synchronously collecting optical, thermal infrared, microwave remote sensing and ground data, carrying out the time-space alignment based on a dynamic time warping algorithm, and constructing a four-dimensional unified data set; then, an improved asymmetric automatic encoder integrating multi-branch encoding and a space attention mechanism is utilized to generate a deep fusion feature vector; and inputting the feature vector into an STCN-LSTM hybrid model, mining spatial features through multi-scale convolution, capturing a time evolution rule in combination with a bidirectional long short-term memory network, and embedding DSSAT crop physiological parameters to optimize the model weight. And finally, the uncertainty is quantized and predicted through Monte Carlo Dropout, and the error is further reduced by adopting a space-time layering correction strategy. The method breaks through the limitation of a single data source, the prediction error is smaller than 5%, a reliable basis is provided for precise irrigation, and the water resource utilization efficiency is remarkably improved.

The invention discloses a comprehensive evaluation method and device for toughness of a water supply pipe network system and a computer medium. Firstly, hydraulic model parameters of a water supply pipe network are obtained; then, a low-stress scene, a medium-stress scene and a high-stress scene are constructed, the low-stress scene is constructed according to historical water demand data, the medium-stress scene is constructed by superimposing pipeline failure on the basis of the low-stress scene, and the high-stress scene is constructed by superimposing fire working conditions on the basis of the medium-stress scene; according to the hydraulic model parameters of the water supply pipe network, the water supply amount and the water demand amount of the water supply pipe network in a low-stress scene, a medium-stress scene and a high-stress scene are calculated respectively; and finally, according to the water supply amount and the water demand amount of the water supply pipe network in the low-stress scene, the medium-stress scene and the high-stress scene, calculating a plurality of strain indexes for quantifying the toughness of the water supply pipe network system. According to the method, the system toughness of the water supply pipe network is evaluated at low calculation cost through scene simulation of only traversing the single pipe failure and superposing the single-point fire working condition on the basis of the single pipe failure.

The invention belongs to ecological environment engineering, and particularly relates to a river and lake wetland zoning and classifying ecological water demand fine accounting method, which comprises the following steps of S1, performing zoning and classifying on a river and lake wetland of a research area; s2, establishing a space-time coupling hydrodynamic model based on a partition classification relationship; s3, constructing a multi-factor ecological response model, and calculating an ecological suitability index of each partition; s4, establishing a multi-objective optimization model, and performing optimization solution on the ecological water demand of the partition by combining ecological benefits, water balance and process smoothness objectives; and S5, performing robust correction on an optimization result by adopting an uncertainty analysis method to obtain a final ecological water demand distribution result. By establishing a river and lake wetland partition classification spatial database based on digital elevation, river network distribution, land utilization and ecological attribute information, fine description and dynamic association of different ecological functional areas are realized, and the effects of ecological process differentiation characterization and remarkable improvement of water demand accounting precision are obtained.

The invention is suitable for the technical field of intelligent agricultural irrigation, and provides a rice field fertilizer and water intelligent irrigation measurement and control method and system based on multi-source information fusion, and the method comprises the following steps: determining a target fertilizer and water demand through a quantitative relation model of fertilizer and water input and crop growth response according to a rice seedling growth stage; based on an improved D-S evidence theory algorithm, fusing real-time multi-source monitoring data, dynamically evaluating an environment state of a current planting area according to a target fertilizer and water demand quantity, and combining future weather prediction data to generate an irrigation decision result considering crop demands and resource saving; and based on a fuzzy PID control algorithm, fertilizer and water irrigation operation is automatically controlled according to an irrigation decision result. According to the method, the comparison database is established by collecting the requirements of crop characteristics and growth cycles for environmental moisture and nutrients, the irrigation process is comprehensively decided according to the crop growth cycles, weather and other factors, the utilization efficiency of water resources and fertilizer is effectively improved, and the method has a good application effect.

The invention discloses a risk scheduling method for a water resource system, and the method comprises the steps: obtaining regional basic data, constructing a supply and demand pressure field, recognizing causal association, and generating a heterogeneous computational grid and a space-time causal network; based on historical supply and demand sequence data of the heterogeneous computational grid and influence factors identified by a time-space causal network, dynamically determining a water demand truncation threshold by adopting a cascade buffer pool mechanism, and outputting a regulated water demand sequence; generating a hydrological scene set by using the regulated and controlled water demand sequence and adopting a tail conformal optimal transmission method, and simplifying the hydrological scene set into a representative scene subset; and for the representative scene subset, constructing a distributed robust optimization model, and generating a water resource scheduling scheme and a risk assessment report through fairness constraint projection and causal path analysis. According to the method, the space-time pressure can be depicted finely, the extreme requirements are regulated and controlled in a self-adaptive manner, and the scheduling scheme considering the robustness and the fairness is generated under the condition that the tail risk characteristics are reserved.