194 results about "Evapotranspiration" patented technology

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 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 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 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 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 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 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.

The invention relates to the technical field of underground water simulation, in particular to an underground water numerical simulation method coupled with vegetation ecology. The method realizes bidirectional coupling between groundwater and vegetation ecology through iteration, and specifically comprises the following steps: inverting vegetation coverage based on groundwater burial depth; inversion of actual evapotranspiration is carried out based on underground water burial depth and vegetation coverage; and finally, updating the net supply amount of the groundwater model based on evapotranspiration until convergence. According to the method, a statistical function relation is established to replace a complex physical model, and drainage and overflow cell water levels are corrected in iteration to ensure calculation stability.

The invention discloses a method for quantifying the influence of vegetation change on regional rainfall and a related device, and the method comprises the steps: carrying out the evapotranspiration simulation of a target region through a remote sensing evapotranspiration model according to meteorological driving data and vegetation and land utilization data, and obtaining an evapotranspiration data set under different vegetation utilization scenes; performing monthly scale correction on the water vapor tracking input data through the evapotranspiration data set to obtain a corrected water vapor tracking input data set; the meteorological driving data and the corrected water vapor tracking input data set are adopted to drive the water vapor tracking model to perform forward tracking, and water vapor tracking results under different vegetation utilization scenes are output; and quantitatively analyzing the downwind rainfall influence of the vegetation change on the target area through the water vapor tracking results under different vegetation utilization scenes. According to the invention, based on the water vapor source-sink relationship of the region, the evapotranspiration change caused by the vegetation change is spatially redistributed, the influence on downwind rainfall is tracked, and the quantitative relationship of the influence of the vegetation change on the regional rainfall is revealed.

The invention relates to the field of climate change influence assessment, and discloses a method for quantizing contribution of natural internal variability to drought intensity based on a circulation similarity method, and the method comprises the steps: data collection; evaluating the drought strength based on the difference between the rainfall distance and the potential evapotranspiration distance, and quantifying the relative contribution of rainfall deficit and evapotranspiration demand to the drought strength; based on a circulation similarity method, a regional large-scale atmospheric circulation background is obtained, and contribution of a natural internal variation rate to drought intensity, rainfall deficit and evapotranspiration requirements is evaluated; estimating long-term evolution trends of drought intensity, rainfall deficit and evapotranspiration demands under different carbon emission scenes in the future; the method has the advantages that the natural internal influence mechanism of drought intensity change is defined, the relative contribution of historical and future rainfall deficit and evapotranspiration requirements to the drought intensity is quantified, the reliability of future drought trend estimation is enhanced, theoretical support is provided for making disaster prevention and reduction policies, and the accuracy of drought risk prediction is improved.

The invention provides an arid region salt marsh grassland wetland water supplement regulation and control method and a related device, and the method comprises the steps: determining the ecological water demand and deficiency corresponding to a target region according to the wetland vegetation evapotranspiration, precipitation and underground water-soil water exchange flux of the target region in a target time period, the target area is any area in the salt marsh grassland wetland in the arid area; determining a water quantity adaptive gap corresponding to the target area according to the earth surface water supplementing quantity and the ecological water demand deficit quantity of the target area in the target time period; and performing water supplementing regulation and control on the target area according to the water quantity adaptive gap. According to the accurate evaluation result of the water volume adaptation gap, a refined drip irrigation technology is adopted to carry out ecological water supplementation on the salt marsh grassland wetland, the requirements of plants for water in all stages of the whole life cycle are ensured, and the stability and adaptability of a wetland ecological system are improved; and multi-target collaborative development of hydrological communication, biodiversity improvement, habitat optimization and the like of the wetland ecosystem is realized.

The invention provides a flue-cured tobacco disaster assessment method based on conventional meteorological element calculation, and the method comprises the following steps: S1, collecting meteorological data of a target region, including wind speed, precipitation, environment temperature and air humidity parameters; s2, wind disaster assessment: identifying a wind disaster event by setting a multi-stage wind speed threshold, establishing a continuous wind disaster day number tracking mechanism, triggering basic wind disaster judgment when detecting that the wind speed exceeds the minimum threshold, and determining the wind disaster according to the dynamic association relationship between the wind speed intensity and the continuous day number; when the number of continuous wind disaster days reaches a preset critical value, disaster grade jump calculation is automatically executed; and S3, drought disaster assessment: calculating a crop moisture supply and demand balance index based on an improved evapotranspiration model, setting a dynamic moisture threshold according to different growth periods of the flue-cured tobacco, and activating a progressive disaster upgrading program by monitoring the coupling effect of a moisture deficit index and drought duration in real time when the combination of the moisture deficit index and the drought duration exceeds a staged judgment standard.

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

The invention relates to the technical field of intelligent agriculture, and discloses a traditional Chinese medicine organic planting management method based on big data analysis. A space coordinate system is established in a planting area, regular partitioning is carried out, a unique land parcel identifier is formed, a soil humidity sensor is arranged in the center of each land parcel, meteorological observation points are matched to continuously collect air temperature, wind speed and illumination, and an evapotranspiration potential index is generated through sliding window statistics and normalization. The system performs dynamic balance prediction and state correction according to the soil moisture content, the irrigation volume and the evapotranspiration loss, extracts a reference evapotranspiration rate by using an unirrigated sample, determines a threshold interval and a real-time deviation in combination with a historical quantile, and smoothly improves the stability through a sliding window. The threshold value is updated hour by hour within a feasible range, irrigation is triggered when the water content is lower than the threshold value, and the irrigation amount is limited within a reasonable range through depth and flow conversion. Structured logs are generated in the whole process, and irrigation whole-process trace reserving is achieved.

The utility model discloses a weighing lysimeter which comprises a weighing lysimeter main body, a lysimeter data acquisition control device and a drainage device, and the weighing lysimeter main body and the drainage device are respectively connected with the lysimeter data acquisition control device; the drainage device comprises a box body, a water collecting groove is formed in the bottom of the box body, a water suction pump is arranged on one side of the water collecting groove, an inlet of the water suction pump is communicated with the water collecting groove, an outlet of the water suction pump is connected with a liquid conveying pipe, and the liquid conveying pipe extends out from the upper end of the box body. Water permeating out of the weighing lysimeter body is received through the liquid collecting box, and a one-way valve is arranged at the upper end of the liquid collecting box. According to the utility model, the seepage water in the soil is monitored, so that the water seepage data of the soil can be measured, and the measurement of the evapotranspiration of the soil is improved; and when the collected water in the drainage device reaches a certain value or is manually involved, the accumulated water can be automatically pumped out, and the change of the underground water level is accurately controlled.

The application discloses a kind of regional type's water source conservation function and runoff coefficient's evaluation method, including the following steps: obtaining the optical remote sensing image of the region to be evaluated, soil data, precipitation data and evapotranspiration data, analysis processing;According to the ecological system classification data and soil zoning curve value, the runoff capacity grid of each pixel corresponding to different ecological system types different soil zoning is calculated;Obtain the runoff observation data of the region to be evaluated, combine runoff capacity grid, and the runoff observed is proportionally distributed to each pixel, and the runoff depth of each pixel is obtained;According to precipitation, evapotranspiration and runoff depth, the water source conservation amount and runoff coefficient corresponding to each pixel of the region to be evaluated are obtained.The application relates to the technical field of ecological system water source conservation, and the runoff index and runoff depth of each pixel are calculated by fusing multi-source data, so that the accuracy of evaluating the water source conservation service function and runoff coefficient of the region is improved.

The invention relates to the technical field of agricultural irrigation, in particular to a crop actual evapotranspiration calculation method and device, electronic equipment and a storage medium. Time-space units are established based on objective division rules, and a stable reference cold and hot image element set is constructed for each unit by utilizing historical data; therefore, the pixel selection process depending on subjective experience in a traditional SEBAL model is converted into a standardized and data-driven process, the reference set of the corresponding unit of the day to be calculated is automatically matched and called for calculation during calculation, and deviation caused by artificial subjective judgment and random selection is avoided. Therefore, the calculation result has higher precision, stability and repeatability, meanwhile, the comparability of the calculation results at different time and in different areas is ensured, and the scientificity and reliability of agricultural water management are remarkably improved.

The application provides a kind of method and device for high-cold arid coal mine area vegetation damage repair, it is related to mine vegetation technical field, the present application is divided into sub-region to coal mine area, the water content monitoring is carried out to each sub-region, the meteorological data of meteorological station is combined, to analyze the evapotranspiration of each sub-region, combined with evapotranspiration, rainfall, vegetation water absorption, to analyze whether the water content of sub-region meets the requirement of plant growth, and output irrigation index reflecting the current demand irrigation degree of sub-region, while also image shooting and multispectral data acquisition are carried out to sub-region, generate greening evaluation index for reflecting the growth condition of sub-region vegetation, combined with greening evaluation index and irrigation index analysis, obtain sub-region repair index, finally output sub-region repair priority area, priority is carried out targeted vegetation damage repair to repair priority area, greatly improve repair efficiency.

The invention discloses a regional groundwater supply simulation method based on a rainfall intensity dynamic response mechanism. The method comprises the following steps: firstly, collecting and preprocessing data of a research area; then simulating a rainfall redistribution process; calculating surface runoff production and initial infiltration; calculating dynamic infiltration response based on rainfall intensity; calculating actual evapotranspiration; and finally outputting the groundwater replenishment amount. According to the method, the key technical problem that underground water supply under high-intensity rainfall is systematically underestimated due to the fact that an existing regional underground water supply simulation method is insufficient in rainfall intensity dynamic response and ignores a rapid deep seepage mechanism induced by high-intensity rainfall is solved.