249 results about "Evapotranspiration" patented technology

The invention relates to the technical field of automatic irrigation control, in particular to a multi-sensor fusion agricultural precise irrigation system which comprises a leaf area analysis module, an environment evaluation module, a task arrangement module, an execution regulation and control module and a feedback regulation module. According to the method, the crop leaf area index is introduced to be compared with the growth stage target value, the dynamic expression of the group moisture demand is realized, the environmental evapotranspiration influence factor is generated in combination with illumination and temperature disturbance parameters, the timeliness of water demand driving force identification is enhanced, and the task execution sequence is judged by adopting regional water pressure disturbance data; a multi-region irrigation resource allocation process is optimized, a water quantity and pressure difference double-factor adjustment mechanism is utilized, the rationality and response accuracy of time length allocation are improved, water supply state analysis and task target deviation comparison are performed, dynamic supplementary irrigation regulation and control are realized, the closed-loop capability and supplementary irrigation accuracy of irrigation period control are improved, and the irrigation period control efficiency is improved. And the stable allocation capability and the irrigation response efficiency of the irrigation system under the influence of multiple variables are enhanced.

The invention discloses a cold region SWAT model construction method considering a glacier melting process. A calculation method comprises the following steps: step 1, obtaining corrected rainfall data; corrected air temperature data are obtained; evapotranspiration correction data is obtained; actually measured runoff is obtained; 2, obtaining a plurality of sub-basin boundaries and spatial distribution of each sub-basin glacier; 3, calculating the glacier melting amount of each sub-drainage basin in the research time period by adopting a day-to-day factor method to obtain the day-by-day glacier melting amount of each sub-drainage basin; step 4, performing double-element parameter calibration based on the actually measured runoff data and the evapotranspiration correction data to obtain parameters suitable for the watershed hydrological process; and 5, calculating to obtain the relative contribution rate of the glacier melting process to runoff and evapotranspiration. The simulation precision of hydrological elements such as runoff of the cold region hydrological model is improved, and a scientific basis can be provided for sustainable utilization and planning of water resources of a local drainage basin.

The invention relates to the technical field of agricultural irrigation, and particularly discloses a farmland irrigation control method and system, and the method comprises the steps: constructing a multi-sensor fusion monitoring network, and collecting soil, weather and plant physiological data in real time; transmitting data to an edge computing node through LoRa wireless communication; utilizing a lightweight neural network model deployed by edge computing nodes to calculate and predict crop water demand and accurate irrigation volume in combination with evapotranspiration; the irrigation strategy is executed through the intelligent irrigation execution system; and remote monitoring and abnormity alarm are realized by means of a remote monitoring and management platform based on WebGIS. Precise and intelligent management of farmland irrigation is realized, the utilization rate of water resources and fertilizers can be effectively improved, irrigation abnormity can be timely handled, the labor management cost is reduced, and the growth requirements of crops are guaranteed.

The invention provides a daily scale drought and flood sharp turn predictable index construction method and system, and relates to the technical field of drought and flood sharp turn prediction.The method comprises the steps that according to weather forecast data, an early-stage accumulated rainfall and evapotranspiration difference index is calculated and converted into a standardized index SAPEI; determining the optimal window size of the waterlogging period window and the drought period window; calculating a drought period average index and a waterlogging period average index; and judging whether a drought and flood sudden turning event occurs, and calculating the drought and flood sudden turning intensity and the drought and flood sudden turning speed. According to the method, by constructing a multi-dimensional index system, different change characteristics of drought and flood sudden change events in the aspects of conversion intensity and speed are reflected, and the characteristic that drought-to-flood is asymmetric in the time scale can be fully considered; the SAPEI is used as basic data, so that the ground moisture state instead of the rainfall condition can be better reflected; the sizes of T and U are calculated according to the drought and flood period window corresponding to the maximum value of T instead of fixing the size of the window, so that the method is suitable for the nationwide range.

The invention discloses a modularized distributed cold region hydrothermal coupling hydrological model which comprises the following steps: S1, dividing a drainage basin into a plurality of grids, and preparing a file required by a confluence process; s2, preparing driving data and grid feature description data of each grid; s3, calculating an energy balance process of the soil and vegetation surfaces by using an energy balance module; s4, calculating an evapotranspiration process by using an evapotranspiration module; s5, calculating an ice and snow melting process by using an ice and snow melting water module and adopting a degree-day factor method; s6, calculating soil moisture infiltration and an internal hydrothermal transmission process by utilizing a soil hydrothermal transmission and infiltration module; s7, calculating the runoff volume by using a runoff production calculation and confluence module; and S8, evaluating the simulation performance of the model through the model evaluation index. The device has a flexible modular structure, can automatically adjust the time step length, improves the simulation capability of the runoff process in the cold region, and can provide scientific guidance for water resource management in the river source region.

The invention relates to a crop irrigation demand prediction method based on an intelligent integrated prefabricated pump station, and belongs to the technical field of artificial intelligence. The method comprises the following steps: collecting a crop image in a prefabricated pump station irrigation scene, obtaining auxiliary data, calculating a daily accumulated reference evapotranspiration value, and obtaining a time-synchronized multi-modal data set; labeling and dividing the multi-modal data set; constructing an irrigation demand prediction model, wherein the irrigation demand prediction model comprises a spectral reflectivity enhancement module, a double-flow separation convolution module, a cross gating fusion module, a region sensitive pyramid module and a coupling prediction head module; inputting data in the divided training set into the model, and training the model through weighted total loss to obtain a trained model; inputting a to-be-detected image into the trained model to obtain a soil water content and transpiration prediction result; and performing irrigation decision based on the soil water content and transpiration prediction result. The accuracy of irrigation prediction can be improved.

The invention discloses a flood lake wetland heat flux simulation method in a watershed hydrological model, and relates to the technical field of heat flux simulation, and the method comprises the following steps: dispersing a watershed space into a slope river channel and a lake wetland, simulating the water movement of a slope river channel unit, and simulating the water movement of the lake wetland; the method comprises the following steps: simulating surface energy exchange for a lake wetland unit on the basis of simulating a hydrological process, simulating land hydrology and lake inflow runoff of a sub-basin by adopting a grid-based distributed hydrological model, respectively dividing simulation grid units for a slope river channel and a lake wetland, establishing evapotranspiration, infiltration and surface runoff models, and establishing an evapotranspiration, infiltration and surface runoff model; a two-dimensional shallow water equation is used for processing slope confluence, a one-dimensional hydrodynamic model is used for calculating river channel confluence, a lake water quantity balance model is established for calculating the lake water level, the lake submerging process is simulated, and the lake wetland distributed heat flux process is simulated. And the technical blank of flooding wetland hydrothermal simulation is filled.

The invention provides a drought and flood sudden turning event identification method, device and system, and relates to the technical field of water resource management, and the method comprises the steps: determining a research region and time period, collecting rainfall, sunshine duration, wind speed, pressure, humidity and air temperature data, carrying out the linear difference of vacant data, and carrying out the data preprocessing; constructing a rainfall difference comparison index for judging the sudden change degree of the drought and flood sudden change event; calculating a standardized rainfall evapotranspiration index for judging and identifying drought and flood events; establishing a grading standard of drought and flood events, and classifying the severity of the identified drought and flood events; and combining the rainfall difference comparison index with a standardized rainfall evapotranspiration index to construct a drought and flood sudden turning index for analyzing the sudden turning intensity. According to the method, the influence of rainfall intensity change on the flood disaster event is fully considered, and the occurrence process and severity level of the drought and flood sudden change event can be effectively and accurately identified.

The invention relates to the technical field of ecology and hydrology, in particular to a terrestrial ecosystem water carbon flux estimation method considering water balance constraint, which comprises the following steps: estimating leaf scale photosynthetic rate and stomatal conductance by utilizing a photosynthesis model; the leaf scale photosynthetic rate and the stomatal conductance are upscaled into canopy vegetation total primary productivity and canopy conductance to construct an evapotranspiration model to estimate evapotranspiration data; constructing a water balance model according to the evapotranspiration data so as to estimate the available water amount of the soil; constructing a soil moisture stress function according to the available water amount of the soil so as to constrain the estimation process of the photosynthesis model and the evapotranspiration model; and acquiring historical water-carbon flux data and historical remote sensing observation data of a long sequence daily scale, and calibrating the model to obtain a water-balance-constraint-considered water-carbon flux estimation model of the terrestrial ecosystem capable of estimating the water-carbon flux data. Therefore, the problems that an existing water carbon flux prediction frame is difficult to adapt to climate changes, low in prediction accuracy and the like are solved.

The invention provides a three-dimensional triple configuration potential evapotranspiration fusion method and system considering neighborhood space-time non-stationary errors, and relates to the technical field of potential evapotranspiration estimation. The method comprises the following steps: obtaining a potential evapotranspiration observation value of a target watershed meteorological station and three sets of independent potential evapotranspiration data sets, and unifying temporal-spatial resolution; calculating a Gaussian kernel function matched with the predetermined space-time window, and performing data standardization by using the kernel function; constructing a variance calculation model of the three-dimensional triple configuration error, and obtaining a variance of an error of neighborhood dimension spatio-temporal information contained in each data set under a predetermined spatio-temporal window; and constructing a data fusion model based on a least square framework, determining an optimal fusion weight and realizing fusion of the multi-source potential evapotranspiration data. According to the method, the problems that local space-time non-stationary errors exist during fusion of the potential evapotranspiration data and the fusion precision is influenced by the scale effect of the space-time window are solved, and the precision of the potential evapotranspiration fusion data is effectively improved.

The invention discloses a vegetation vulnerability constraint estimation method and system under dry-heat composite stress. The vegetation vulnerability constraint estimation method comprises the following steps: 1, acquiring observed vegetation total primary productivity data, meteorological data and similar meteorological data of each lattice point in a global climate mode; 2, determining a standardized rainfall evapotranspiration index time scale of each lattice point and determining dominant stress types of different lattice points in growing seasons; 3, respectively constructing two-dimensional Copula models of corresponding dominant stress and total primary productivity, and determining a stress threshold value corresponding to induced vegetation loss; 4, calculating future estimation of dominant stress based on a climate mode, and constructing an emergence constraint model; 5, correcting a future estimated mean value and uncertainty of the dry heat stress index based on the emergence constraint relation; and 6, inputting the corrected mean value and uncertainty range of the future dry heat stress indexes into a Copula model, and calculating a corresponding loss probability. According to the method, the response difference of different vegetation ecosystems to dry heat stress is considered while the prediction accuracy of the drought heat waves and the compound events thereof is improved.

An early warning method for debris flow disaster in a small watershed, and a disaster reduction method for debris flows in a small watershed is disclosed. An early warning method for debris flow disaster in a small watershed is provided, in which parameters of a hydrological model are calibrated by rainfall, evaporation and runoff data of the watershed based on water balance of the watershed, and an early monitoring and warning scheme for debris flows, which takes water storage in the watershed as a core monitoring and evaluation indicator, is established. The GR4J hydrological model is improved by taking into account a watershed area, specific yield of an aquifer and several geological parameters, as well as an evapotranspiration effect of vegetation. A disaster reduction method by means of regulation of a drainage channel can provide a basis for mathematical model simulation studies of disaster reduction in small watersheds.

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

The invention relates to the technical field of bamboo forest ecological environment monitoring, in particular to a bamboo forest ecological environment collaborative observation method based on multi-source Internet of Things sensing, and the method comprises the steps: synchronously collecting a multi-source collaborative observation parameter set of a bamboo forest slope through an Internet of Things sensor network, and then constructing a point-surface scale fusion bamboo forest moisture dynamic model; correcting evapotranspiration point cluster data by using a random forest gradient lifting algorithm to generate terrain weighted evapotranspiration, aggregating runoff data according to terrain weight to obtain a total amount of runoff sub-regions, then executing dynamic water balance constraint calculation, optimizing infiltration capacity in combination with a variation assimilation algorithm, redistributing infiltration capacity space proportion according to soil hydraulic conductivity when a residual error exceeds a threshold value, and calculating the total amount of the runoff sub-regions. Finally, according to the residual space distribution thermodynamic diagram, the evapotranspiration point cluster is migrated to the micro-topography representative area, and observation network adaptive optimization is achieved, the problems that in the prior art, the data scale is disjointed, the observation precision is insufficient, and the network is difficult to adapt to change are solved, and the bamboo forest ecological observation precision and reliability are improved.

The invention discloses a drainage farmland underground water burial depth prediction method and system, and belongs to the technical field of agricultural prediction. Obtaining daily actual evapotranspiration, lateral displacement and groundwater burial depth prediction values through physical process model simulation; determining an actual absolute error of a daily groundwater burial depth predicted value output by the physical model, determining a daily moisture balance intermediate variable, taking the daily moisture balance intermediate variable and the groundwater burial depth predicted value as input variables, and performing training according to the corresponding actual absolute error to obtain an absolute error prediction network; according to the absolute error prediction network, the predicted value of the absolute error is obtained and serves as the correction amount, the groundwater burial depth predicted value obtained through physical process model simulation is corrected, the corrected groundwater burial depth predicted value is obtained, and the method can more accurately and reliably simulate GWD dynamic changes under different drainage conditions.

The invention discloses a rainfall type landslide early warning method based on multi-source environment threshold and nonlinear fusion. The method comprises the following steps: constructing a landslide disaster-inducing factor set; introducing soil humidity, vegetation indexes and evapotranspiration, and calculating a threshold parameter corresponding to the rainfall type landslide event to obtain an environment threshold point set; according to the landslide disaster-inducing factor set, constructing and training a landslide susceptibility model based on progressive learning; adopting a double-layer nonlinear fusion model based on multi-source data fusion and quality perception gating, and combining a landslide susceptibility model to obtain comprehensive risk probability distribution; and performing graded early warning based on the comprehensive risk probability distribution to complete rainfall type landslide early warning. According to the method, on the basis of traditional rainfall parameters, early-stage disaster-pregnant environment factors are introduced, and a multi-source environment threshold value is formed; fuzzy logic reasoning is adopted to realize nonlinear fusion of the threshold information and the landslide susceptibility base map; and dynamically reflecting a regional environmental condition evolution process in combination with an annual iterative updated susceptibility layer, and realizing finer and more adaptive space grading early warning.

The invention discloses an irrigation method and system based on a crop growth model, and relates to the technical field of farmland irrigation, and the method comprises the steps: training a growth model based on a time sequence neural network through employing the obtained historical meteorological data, the crop growth process data of a corresponding time period, and the moisture state of a soil root zone; calculating the actual evapotranspiration of the crops by combining the actual moisture state of the soil and the moisture stress coefficient predicted by the growth model, and determining the irrigation amount according to the water deficit and the root depth by combining the current moisture state of the root zone with the stage target moisture content. And the irrigation frequency adaptive to the current environmental condition is calculated by using the meteorological prediction data and the actual evapotranspiration. According to the invention, by introducing the crop growth model based on time sequence modeling, correlation learning among meteorological conditions, soil moisture dynamic changes and crop moisture stress states is realized, so that irrigation decisions can reflect periodic physiological needs of crops on the basis of real-time data.

The invention discloses a comprehensive evaluation method for drought resistance of corn varieties, which relates to the technical field of corn variety evaluation, and comprises the following steps: obtaining multi-temporal multi-band reflection spectrum data under the condition of continuous drought of corn, and performing structure coupling modeling on the spectrum data in combination with the structural characteristics of corn leaf epidermis wax, so as to obtain the drought resistance of the corn varieties; constructing a time sequence curve capable of representing the dynamic change of leaf wax distribution as a dynamic spectrum monitoring baseline; differential analysis between continuous time points is carried out based on the dynamic spectrum monitoring base line, spectrum abrupt change points caused by leaf wax migration are identified, and space consistency inspection is combined. According to the method, a dynamic spectrum monitoring baseline and an energy migration fingerprint are constructed, wax migration interference is accurately identified, a spectrum stability hypothesis is broken through, high precision, self-adaption and consistency of evapotranspiration rate inversion under a drought condition are realized through multi-level correction and a closed-loop updating strategy, and scientificity and comparability of drought resistance evaluation are improved.

The invention discloses a method for predicting reservoir inflow and under-dam water resource change trend in a future change environment. The method comprises the steps of obtaining future monthly rainfall data, future monthly temperature data, future monthly evapotranspiration data and future land utilization data based on a GCM climate mode; the future runoff process of the reservoir control section is obtained through simulation in combination with an RCCC-WBM model; based on a data mining technology and an LSTM deep learning coupling model, mining relation characteristics of future reservoir runoff and the under-dam water resource quantity, and obtaining the under-dam water resource quantity by inputting the reservoir runoff; and a nonlinear trend analysis method and the like are adopted to analyze change trend characteristics of water resources under the dam in the future. The method can fully solve the problem of insufficient consideration of climate change and land utilization in the existing method, and can significantly improve the prediction precision of the water resource under the dam in the future.

The invention belongs to the technical field of agricultural cultivation, and particularly relates to a film-mulching shallow-burying drip irrigation planting method. The film mulching, shallow burying and drip irrigation planting method comprises the following steps: a preparation stage before sowing; sowing the seeds; performing irrigation; the soil moisture content of the crop planting area is monitored in real time; meanwhile, the evapotranspiration amount of the crop planting area is monitored in real time; when the monitored soil moisture content is lower than 64%-66% of the field water holding rate before sowing and the evapotranspiration reaches the irrigation requirement standard, an irrigation system is started for drip irrigation. According to the film-mulching shallow-burying drip irrigation planting method, through accurate control over water and fertilizer integration, the water resource utilization rate and the crop yield are remarkably increased, meanwhile, environmental friendliness is achieved, and the labor cost is effectively reduced.

The invention relates to the technical field of resource scheduling, in particular to a wheat irrigation optimization system based on big data, which comprises a leaf index identification module, a water consumption feature reconstruction module, a time period supply and demand pre-judgment module, a decision water distribution generation module and a dynamic duration execution module. According to the method, the continuous change structure is constructed according to the leaf area amplification characteristics in the wheat growth stage, the water demand characteristic dynamic reduction in the crop growth process can be realized, the trend curve is established by pairing the evapotranspiration rate and the leaf area change to identify the water consumption change node, and the accurate time period water demand description can be realized in the growth stage; the evapotranspiration supply trend is established in combination with meteorological prediction data, pre-judgment identification of the water supply and demand state in the future time period is achieved, time period deviation analysis and supply and demand difference judgment are introduced in the actual water distribution process, the scheduling flexibility and the resource matching precision are improved, and the adaptability and high efficiency of field water regulation and control in different growth stages are ensured.

The invention discloses an agricultural disaster prevention-oriented high-temperature drought composite event early warning and identification method, which comprises the following steps of: acquiring lattice meteorological data of a target area, including daily maximum temperature, precipitation and environmental parameters; calculating a standardized rainfall evapotranspiration index SPEI based on the meteorological data, and generating a high-temperature drought composite event lattice point judgment matrix in combination with a preset high-temperature threshold value; performing connectivity analysis on the judged high-temperature and drought composite event lattice points through a spatial clustering algorithm, and screening regions with spatial coverage areas exceeding a set threshold value as high-temperature and drought composite event groups; performing time continuity judgment on the high-temperature drought composite event groups in two continuous days by adopting an overlapping area proportion method; counting the duration time, the space coverage area and the event intensity index of the event group, constructing an early warning criterion and generating early warning information; outputting spatial and temporal distribution characteristics and early warning levels of the composite dry heat events; the method provides a scientific basis for climate analysis and disaster prevention and reduction.

The invention belongs to the technical field of inter-basin underground water circulation flux estimation, and particularly relates to an infiltration and lateral inflow separated underground water flux remote sensing estimation method and system. The method includes: acquiring a multi-source remote sensing data set of a research area; performing partition correction on evapotranspiration data of different land utilization type areas in the research area; the method comprises the following steps: dividing a research region into equal-area units, identifying a vertical dominant unit and a lateral dominant unit, and further determining a cross-basin underground water exchange zone; and solving a local vertical infiltration amount by using the vertical dominant unit and interpolating to form a background field, establishing a combined equation set which takes the background field as an initial value and takes the dynamic characteristic parameters of the underground water as additional constraints for the lateral dominant unit, solving to obtain an external lateral inflow amount, and further obtaining a cross-basin underground water circulation flux. According to the method, the vertical dominant unit and the lateral dominant unit are identified, and the cross-basin groundwater circulation flux is quantitatively estimated.

The invention relates to the technical field of agricultural automation and intelligent irrigation, in particular to a variable irrigation decision-making system, which comprises a meteorological data acquisition module used for acquiring daily meteorological data of a specified farmland in a first time period from the current time period to the future time period; the soil monitoring module is used for monitoring soil data of a specified farmland in real time; the data processing module is used for obtaining the current soil water content of the specified farmland, the evapotranspiration amount of the specified farmland in each day in the first time period in the future and the soil displacement amount of the specified farmland in each day in the first time period in the future based on the meteorological data of the specified farmland in each day from the current time period in the future and the current soil data of the specified farmland; further acquiring the soil water content of the specified farmland after the first preset time period; the control module is used for determining the current irrigation demand quantity of the specified farmland and sending a first irrigation instruction to the irrigation device corresponding to the specified farmland; the first irrigation instruction is an instruction for irrigating the specified farmland according to the irrigation demand quantity of the specified farmland at the current moment.

The invention relates to the field of urban green land evapotranspiration zoning, in particular to an urban green land surface evapotranspiration zoning method and system based on impedance parameters, and aims to distinguish arbor, shrub and lawn transpiration in an urban green land. The method comprises the following steps: firstly, collecting and preprocessing vegetation morphological parameters, meteorological data, canopy surface temperature, soil heat flux, vegetation transpiration and vortex related flux data; calculating leaf boundary layer impedance and canopy stomatal impedance of each vegetation type by using a backstepping Penman-Monteith formula and an earth surface energy balance equation; determining the proportion of each vegetation type in the flux contribution source area through a flux footprint model, and reversely deducing the total aerodynamic impedance and the total stomatal impedance of the earth surface; solving aerodynamic impedance of each vegetation according to an earth surface energy balance equation and performing fitting correction; and finally, the corrected impedance parameters are substituted into a Penman-Monteith model to calculate the transpiration amount of each vegetation. According to the method, the problem of mismatching between single plant scale data and community scale data is effectively solved, and the evapotranspiration partition calculation precision is improved.

The invention discloses an efficient identification method for a drought and flood sudden turning event. The method comprises the following steps: step 1, calculating a standard evapotranspiration index of a daily scale; step 2, constructing a drought and flood sudden turning event identification method; 3, determining characteristic indexes of drought and flood sudden change events; and 4, calculating a drought and flood sudden turning event intensity index. According to the method, the drought and flood state is judged grid by grid, the false flood phenomenon in the dry season is avoided in event recognition, higher recognition precision is achieved compared with a traditional method, the false flood recognition problem in the dry season is reduced, and the starting and ending time and the conversion direction of drought-to-flood and flood-to-drought events can be accurately recognized; and by determining the characteristic indexes of the drought and flood sudden change event, objective weighting is performed on multiple indexes by adopting an entropy weight method, a drought and flood sudden change intensity index is established, quantitative evaluation of the drought and flood sudden change event is realized, and scientific reference is provided for disaster prevention and reduction.

The invention discloses an AIoT water and fertilizer integrated regulation and control method and system based on a crop growth dynamic model, and relates to the technical field of water and fertilizer regulation and control, and the method comprises the steps: firstly obtaining multi-dimensional environment parameters and soil characteristics through an AIoT sensing network, and deeply analyzing a restriction mechanism of soil moisture on nutrient effectiveness based on the crop growth dynamic model; and quantifying the nutrient effectiveness coefficient. And then, inputting the coefficient into a water-fertilizer coupling prediction model, and dynamically deducing the actual nutrient absorption amount and the moisture evapotranspiration amount of the crop in a specific water-fertilizer interaction environment, so as to realize digital representation of the physiological demand. And further, in combination with future meteorological information and cost constraints, multi-target collaborative optimization is carried out by using a rolling time domain optimization algorithm, and an optimal regulation and control strategy considering growth requirements and economic benefits is generated and driven to be executed. In this way, quantitative and accurate regulation and control of the water and fertilizer synergistic effect can be achieved, and therefore the resource utilization efficiency and agricultural production economic benefits in the whole growth cycle of crops are greatly improved.

The invention relates to the technical field of ecological restoration, in particular to a vegetation water and soil ecological restoration optimization method and system based on multi-source data fusion, and the method comprises the following steps: obtaining monthly-scale evapotranspiration data, extracting extreme values to construct an interval sequence, screening adaptive vegetation to generate a list, and calculating soil nutrient release and vegetation absorption amount. Determining the maximum planting density and the target planting density, judging the critical point of root layer moisture, and setting a maintenance water replenishing period. According to the method, by matching the evapotranspiration water supply capacity section with the water consumption characteristics of the plants, high coupling of vegetation allocation and regional hydrological conditions is ensured, and the resource bearing reasonability of vegetation allocation is enhanced in combination with a density allocation mechanism of the sustainable nutrient release capacity of the soil in unit area and the plant absorption capacity; the recovery speed and the resource utilization efficiency are effectively balanced, the root layer moisture critical point is calculated according to the soil structure parameters and the rainfall erosion data after information fusion, and the maintenance water supplementing rhythm is optimized to reduce the resource waste and the vegetation stress occurrence probability.

The invention relates to the technical field of forestry data processing, in particular to a landscaping maintenance system and method based on big data, and the system comprises a water potential monitoring module, a block division module, a pruning adjustment module, a man-hour scheduling module and an anomaly recognition module. According to the method, by tracking the consistency of soil moisture fluctuation in real time, accurately analyzing the dynamic influence of the root system type and the soil layer structure on water absorption and combining plant evapotranspiration physiological indexes and meteorological condition differences to finely divide water demand grades, efficient matching of water supply and plant physiological statuses is achieved; the pruning period is dynamically adjusted according to the actual change of plant photosynthesis and tissue expansion, the coordination error between maintenance working hour calculation and geographic path planning is effectively reduced, the continuity and timeliness of illumination change abnormal response recognition are improved, the accuracy and refinement level of garden plant maintenance decision making are remarkably improved, and the method is suitable for popularization and application. And the scientific decision-making capability, the space adaptive capability and the intelligent response level of greening maintenance management are improved.

An irrigation system (1) which allows, in real time and automatically, to measure the flow of water and alert about anomalies in the normal operation of the system, such as the detection of water leaks and / or the non-operation of any of its components, thus optimizing its consumption and facilitating the user experience, wherein the irrigation system comprises at least one water supply means, to supply water to the irrigation system (1); at least one pipe (10) connected at one end to the water supply and extending across the surface to be irrigated; at least one valve (11) arranged in the at least one pipe (10) to control the flow of water through it; at least one sprinkler (12) connected to at least one outlet of the at least one pipe (10); at least one flowmeter (13) to measure the flow of water; at least one control means (14) to control the operation of the irrigation system (1); at least one cable (15) connected to the at least one control means (14) to energize the at least one valve (11); and at least one climatic data storage means (16) which sends at least one evapotranspiration data from the geographical area of the irrigation system operation (1) to at least one control means (14). A method of irrigation control and management.