7 results about "Water productivity" patented technology

This application discloses a method, apparatus, equipment, medium, and product for predicting regional crop water productivity, relating to the field of smart agriculture. The method includes inputting historical and future climate data into an ecosystem process model to obtain simulated net primary productivity and simulated evapotranspiration for historical and future times; using a bias mapping method based on the simulated evapotranspiration, actual evapotranspiration, and simulated evapotranspiration for future times to obtain predicted evapotranspiration for future times; training multiple machine learning models based on the simulated net primary productivity, agricultural management data, and grain yield per unit area for historical times to obtain a crop yield prediction model; obtaining the predicted grain yield per unit area for future times based on the crop yield prediction model; and obtaining the regional crop water productivity based on the predicted evapotranspiration and the predicted grain yield per unit area for future times. This application can achieve high-precision, high spatiotemporal resolution, and high-reliability prediction of regional crop water productivity.

The present application relates to a kind of water culture crop biomass prediction methods based on stage-specific feedback evapotranspiration calculation, comprising the following steps: according to growth day or accumulated temperature, water culture crop growth is divided into three stages;For current growth stage, calculate stress factor and regulate the weight corresponding to each stage stress factor;Multiply basic crop coefficient, canopy coverage, reference evapotranspiration and stress factor and corresponding weight, calculate stage-specific evapotranspiration;Multiply water productivity adjustment value, the ratio of stage-specific evapotranspiration and reference evapotranspiration and environmental stress factor and corresponding weight, predict biomass increment, obtain water culture crop biomass prediction value;Using ensemble Kalman filter, integrated assimilation canopy coverage and biomass prediction value, carry out sustained biomass prediction in the whole growth cycle of water culture crop.Compared with prior art, the present application has the advantages of biomass prediction accuracy.

The invention provides a straw returning effect evaluation model construction method, system and device and a medium, and belongs to the field of intelligent agriculture, and the method comprises the steps: obtaining meteorological data, soil data, field management data, crop yield data and crop moisture productivity of a training region; effect quantity indexes of the crop yield and the crop moisture productivity are calculated based on Meta analysis, and response variables of the crop yield and the crop moisture productivity of the to-be-evaluated region are obtained; performing data enhancement on the response variables based on an SMOTE method to obtain a synthetic sample of the crop yield and the crop moisture productivity; the meteorological data, the soil data and the field management data serve as input features of a machine learning model, the response variables and the synthetic samples serve as target variables of the machine learning model to optimize hyper-parameters, and a trained straw returning effect evaluation model is obtained. According to the method, the complex interaction effect of climate-soil-management measures can be accurately described, so that the accuracy and generalization ability of an evaluation result are improved.

The application belongs to the field of dryland agricultural water-saving technology, and provides a dryland agricultural water-saving equivalent calculation method, which comprises the following steps WP ave S1, calculating the average water productivity of a research area under the condition of the same type of soil and traditional management Y a S2, obtaining the actual crop yield of the research area after the target water-saving technology is used ET a S3, calculating the theoretical evapotranspiration of the crop yield according to the average water productivity and the actual crop yield WP ave S4, calculating the dryland agricultural water-saving equivalent after the water-saving technology is used by subtracting the actual crop evapotranspiration from the theoretical evapotranspiration and performing unit conversion Y a Y a ET Theo ET Theo ET ET a W sav The dryland agricultural water-saving equivalent calculation method provided by the application breaks the technical deficiency that the dryland rain-fed agriculture cannot calculate the physical water-saving amount for the first time, so that the water-saving technology can be converted into an intuitive and physical water-saving equivalent. The application fills the long-term blank of lacking direct water amount index in the field.​​​​​

The application discloses a kind of precision irrigation decision-making methods based on soil-crop-environment information, it is related to agricultural irrigation technical field, including the following steps: calculating the irrigation quota that plan wet layer contains, calculating crop cumulative water consumption and deciding irrigation date;The application is through depth fusion multi-source information, dynamic threshold optimization and intelligent feedback mechanism, according to crop root system distribution dynamic adjustment plan wet layer depth changes irrigation quota, through crop-environment data calculation crop actual water consumption, and consider future weather forecast, can effectively avoid the soil moisture deep seepage and nitrate nitrogen leaching loss after irrigation occurs rainfall, significantly improve crop yield and water and fertilizer utilization efficiency, simultaneously by fully considering soil characteristics, crop water consumption characteristics and environmental information formulate can according to environmental and crop demand change dynamic irrigation system, can significantly improve crop yield and water productivity.

The invention relates to a hydroponic crop biomass prediction method based on stage specificity feedback evapotranspiration calculation. The hydroponic crop biomass prediction method comprises the following steps that hydroponic crop growth is divided into three stages according to the number of growth days or accumulated temperature; stress factors are calculated for the current growth stage, and weights corresponding to the stress factors in all the stages are regulated and controlled; multiplying the basic crop coefficient, the canopy coverage rate, the reference evapotranspiration, the stress factor and the corresponding weight, and calculating stage-specific evapotranspiration; multiplying the moisture productivity adjustment value, the ratio of the stage specific evapotranspiration to the reference evapotranspiration, the environmental stress factor and the corresponding weight, and predicting the biomass increment to obtain a hydroponic crop biomass prediction value; and performing continuous biomass prediction in the whole growth cycle of the hydroponic crops by adopting ensemble Kalman filtering and assimilating the canopy coverage rate and the biomass prediction value in a combined manner. Compared with the prior art, the method has the advantages of accurate biomass prediction and the like.

The invention provides a water resource optimization decision-making method for multi-objective two-stage opportunity constrained programming, and belongs to the field of agricultural water resource optimization configuration, and the method comprises the steps: collecting basic data; selecting a typical hydrological year; generating a localized AquaCrop model, and simulating the growth process of crops in different hydrological scenes; on the basis of a localized AquaCrop model, constructing a rice secondary moisture production function under different hydrological year scenes; constructing a random multi-target two-stage opportunity constrained programming water distribution model; setting the boundary of the water distribution model; and carrying out deterministic equivalent transformation and model solution on the chance constraint. According to the method, rainfall randomness and water supply and demand uncertainty can be handled under the condition of future climate change, and multi-target conflicts such as net economic benefits, crop water productivity and water supply and demand matching satisfaction are coordinated; the irrigation strategy generated through optimization reduces the underground water exploitation amount on the premise of controlling the water supply risk, and the water utilization efficiency of an irrigation area is improved.