116 results about "Water potential" patented technology

The invention discloses an intelligent farmland irrigation decision-making method based on digital twinning, and the method comprises the following steps: S1, collecting multi-source data of a farmland environment, and generating a time sequence farmland environment data set; s2, constructing a farmland digital twinborn model, and updating node and edge attribute information in real time; s3, constructing a time sequence diagram based on the updated twinborn model, and inputting the time sequence diagram to a time sequence diagram neural network; s4, optimizing structural parameters of the neural network of the time sequence diagram by applying a red-mouth blue-magpie optimization algorithm; s5, predicting the future soil water potential and the crop water demand trend by using the optimized network; s6, generating an irrigation control instruction according to the prediction result in combination with water resource supply; and S7, executing irrigation, monitoring the humidity of the land parcel and the crop state in real time, and updating the farmland digital twinborn model. According to the invention, by fusing the digital twinning, the time sequence diagram neural network and the Red-billed-blue-magpie optimization algorithm, accurate prediction and intelligent irrigation control of the future water demand trend of the farmland are realized, and the water resource utilization efficiency and the crop yield are significantly improved.

The invention relates to the technical field of intelligent control, and discloses a water-saving fertilization variable control method suitable for sandy soil, and the method comprises the steps: obtaining collection data based on a sensor; and establishing and updating an infiltration-storage-leaching loss prediction model of the sandy soil according to the collected data, performing state estimation on soil moisture and nutrient states, and calculating root layer moisture deviation, fertilizer concentration deviation and deep seepage risk. And executing model predictive control in the rolling time domain to obtain a control result. And executing water-saving fertilization operation according to the control result. In the execution process, the soil volume moisture content, the soil water potential, the soil conductivity and shallow layer leakage observation data are fused, the prediction model is corrected, the control result is dynamically adjusted according to the correction result, and when the environment wind speed exceeds a set threshold value, the spray irrigation parameters are corrected. The fine level of control is improved, deep layer leakage can be inhibited under the sandy soil condition, water and fertilizer balance of a root layer is guaranteed, and external disturbance is coped with.

The invention belongs to the technical field of agriculture, particularly relates to a cranberry water demand dynamic sensing system and a method thereof, and aims to solve the problems that an existing traditional irrigation method is often based on a fixed time table or simple soil humidity measurement, the actual water demand condition of cranberries cannot be timely and accurately reflected, and insufficient irrigation or excessive irrigation is easily caused. In order to solve the problems that in the prior art, water resources are wasted, and the growth and yield of cranberries are possibly influenced, the invention provides the following scheme: the system comprises a monitoring module, a control module and a display module, wherein the monitoring module comprises stem flow rate, leaf water potential, soil water content at different depths and positions, air temperature and humidity, illumination intensity and wind speed data; according to the cranberry water demand monitoring system, accurate monitoring, real-time evaluation and scientific prediction of the cranberry water demand condition can be achieved, then a reasonable irrigation decision and environment regulation and control are guided, and the irrigation efficiency and the water resource utilization efficiency are improved.

The invention relates to the field of intelligent irrigation, and discloses an intelligent irrigation system and method for a crop root system, and the system comprises a root zone sensing module which is used for collecting soil environment parameters through multi-mode soil sensor arrays disposed at soil layers of different depths, generating a sensing matrix, and transmitting the sensing matrix to a root zone sensing module; the sensing matrix is used for representing water potential, pH value, nutrient concentration and temperature information in each soil layer; and the root system density analysis module is connected with the root zone sensing module, and is used for constructing a root system density weight matrix based on root system space distribution information obtained by underground computed tomography, and multiplying the sensing matrix by the root system density weight matrix element by element to generate a root zone state vector. Accurate generation of regulation and control signals is achieved, the micro-fluidic execution module can adjust the irrigation flow and the fertilization proportion in real time according to the actual requirements of the root zone, and therefore it is guaranteed that the rhizosphere environment is always close to the optimal physiological interval.

The invention relates to the technical field of environment monitoring, in particular to an intelligent digital rural environment monitoring system and method based on big data, and the system comprises a layered water potential collection module, a gradient reverse correction module, a path inversion modeling module and a multi-dimensional diffusion modeling module, and the layered water potential collection module calculates and generates rural soil environment monitoring data; the rural soil environment monitoring data comprises layered soil water potential distribution, soil water content gradient and a soil conductivity characteristic value, and the soil water potential abnormal flow data comprises a vertical water potential difference value, an abnormal water flow direction vector and a water flow intensity grade; the moisture permeation path distribution diagram comprises a permeation path distribution structure, a soil water potential accumulation interval and a water flow propagation direction identifier, and the diffusion boundary space model comprises a pollutant diffusion boundary range, a moisture transverse migration region and multi-dimensional diffusion rate distribution. According to the scheme, the abnormal distribution range, the duration time and the development trend are quantitatively described, and the research and judgment accuracy of the abnormal penetration and diffusion process is improved.

The invention discloses an in-situ biomineralizable mineral-PHA water-based seed coating based on microphase separation and soil water potential response and a preparation method and application thereof, and belongs to the technical field of green coatings, the in-situ biomineralizable mineral-PHA water-based seed coating comprises a structural mineral skeleton, a PHA and resin composite matrix and a pore-forming disintegrating agent. According to the invention, a resin enrichment layer and island microphase structure is innovatively constructed, and the contradiction between poor wear resistance and difficult disintegration of a bio-based material is effectively solved. Compared with the prior art, the wear-resistant and dust-reducing coating has the advantages that the wear-resistant and dust-reducing performance far better than that of the traditional PHA coating is realized by utilizing an interface enhancement effect under the condition of equal or even lower polymer dosage; meanwhile, the coating is endowed with a sensitive soil water potential response'switch ', so that dry-state tough seed protection and wet-state rapid disintegration are ensured, and germination is not hindered. Organic components of the composition can be biodegraded in aerobic soil, inorganic components are natural minerals, the environmental compatibility is good, the composition has the advantages of high performance and low cost, and an excellent seed treatment scheme is provided for green agriculture.

The invention relates to a tide level obtaining method and system based on an OWC wave energy conversion device. The method comprises the following steps: constructing an energy loss prediction model in the air chamber; acquiring field incident wave energy, reflected wave energy, water potential energy increment, kinetic energy increment and pneumatic output energy at the current time period; inputting incident wave energy and reflected wave energy into the model to obtain predicted energy loss; and the tide level variation is solved based on the energy conservation relational expression, and the current tide level is calculated. The system comprises an energy loss prediction module, a wave energy acquisition module, a water body energy acquisition module, a pneumatic output acquisition module, an energy loss calculation module, a tide energy solving module and a tide level calculation module, which cooperatively realize the method. According to the scheme, an external tide gauge station is not needed, the local sea area tide level can be inversed in situ, at high frequency and with high precision, the method is suitable for an OWC-breakwater fusion scene, and cooperative operation of a port and ocean energy is supported.

The invention relates to the technical field of intelligent management of landscaping, in particular to an intelligent management method and system for irrigating landscaping plants, and the method comprises the following steps: 1, carrying out multi-dimensional data collection and dynamic modeling: collecting plant physiological data through a stem flow sensor, a leaf water potential sensor and a high-definition camera, the method comprises the following steps: acquiring environment and soil data through a meteorological station array and a soil sensor, and constructing a digital twinborn model containing a plant growth stage-water demand curve based on historical data; 2, water demand prediction and intelligent decision making: inputting real-time data into an LSTM neural network model to predict the water demand of the plant in the future 1-3 days, generating a dynamic irrigation scheme in combination with weather forecast data, and optimizing the irrigation amount and the time period according to the plant type, the growth stage and the soil partition; the water demand state is directly sensed through plant physiological signals, dynamic regulation and control are combined with a prediction model, water is saved by 50% or above compared with traditional regular irrigation, and the soil water accumulation rate is reduced to 5% or below.

The invention discloses a monitoring and analyzing system for root systems of plant slope protection in a mining area. According to the method, morphological enhancement and deep learning technologies are creatively fused through the root system image recognition unit, and the problem that the root system microstructure is difficult to capture in a complex soil background in a traditional method is effectively solved. The unit is based on a multi-scale feature fusion algorithm, can automatically extract key morphological parameters such as root system topology fractal dimensions and the like, remarkably improves the fine root recognition rate, and enables slope protection plant type selection and layout to better fit actual geological conditions. The root growth prediction unit integrates an environmental constraint model and biological rhythm characteristics, realizes accurate prediction of a root extension trend by dynamically coupling parameters such as soil water potential and nutrient concentration, helps managers to plan a reseeding scheme in advance, and avoids the risk of slope instability caused by lagging of root development.

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 field of data analysis, in particular to a controlled-release nitrogen fertilizer application decision optimization method in combination with soil water content change characteristics, and the method comprises the following steps: obtaining an effective infiltration potential energy optimization factor through field water capacity threshold truncation of a soil volume water content sequence and effective infiltration potential energy time window accumulation difference evaluation; obtaining a water potential lag direction optimization factor through first-order difference gradient direction consistency and trend amplitude gating coupling evaluation of the soil volume moisture content sequence; the DTW local distance is corrected through the effective infiltration potential energy optimization factor and the water potential lag direction optimization factor; and performing release curve weighted prediction on the optimal matching historical sequence corresponding to the optimized DTW distance to obtain an accurate controlled-release nitrogen fertilizer application decision suggestion so as to solve the problems of historical scene matching distortion and controlled-release nitrogen fertilizer application decision deviation caused by neglecting of an effective cumulative effect and a water potential hysteresis effect in the existing Euclidean distance measurement.

The invention provides a method for simulating and quantifying physical stress of field soil based on field in-situ monitoring and a model. The method comprises the following steps: step 1, acquiring soil bulk density, water content and penetration resistance values under different water potentials; step 2, fitting the transfer equation of each limiting condition by using each measured data in the step 1, and establishing soil transfer equations of four limiting conditions of LLWR; 3, field soil bulk density dynamic measured data are obtained; 4, constructing a field soil bulk density dynamic prediction model in the implementation stage and the expansion and shrinkage stage under the influence of cultivation and rainfall; step 5, acquiring actually measured data of field rainfall and soil water content of the research area; and step 6, obtaining the LLWR range of the research area and the dynamic change of each limiting condition. The method solves the technical problems that in the prior art, seasonal dynamic of soil bulk density, which is a key transmission variable influencing LLWR, is ignored, and it is difficult to accurately estimate dynamic changes of LLWR in seasons and quantify physical stress caused by the LLWR on crop growth.

The invention relates to a dry slope field spring corn fertilization optimization method based on dynamic regulation and control of soil moisture, which comprises the following steps: identifying capillary water paths according to particle size distribution and pore structures of soil at different slope positions before sowing, and regulating capillary communication through tillage intervention, so that the moisture is migrated and converged to a 10-30cm target root layer; preferentially applying soluble fertilizer along the path to realize overlapping of the fertilizer efficiency area and the water holding area; after rainfall or irrigation, fertilization is delayed for 3-5 days based on soil moisture time lag, so that the fertilization time is matched with a water potential stable period and a root system absorption peak value, and zoning and staggered fertilization is implemented according to the slope direction or texture; nutrients pass through a moisture shielding layer and directly reach a target root layer by adopting local moisture conducting and film breaking or vertical fertilizer injection; setting a moisture threshold value, triggering fertilization amount redistribution when the moisture threshold value is lower than the threshold value, performing supplementary fertilization on a water-deficient area by adopting a moisture-absorbing slow-release material or adjusting a dosage form, and performing slow-release sealing control treatment on an easy-to-lose area; after harvesting, the layer sealing and soil moisture conservation of a plough layer structure are kept, and continuous and feedforward regulation of cross-season water and fertilizer regulation is achieved.

The invention belongs to the technical field of crop irrigation control, and particularly discloses a multi-modal water-saving sprinkling irrigation system based on the Internet of Things, which comprises a data acquisition module, a stress analysis module connected with the data acquisition module, a sprinkling irrigation control module connected with the stress analysis module and a fault processing module connected with the sprinkling irrigation control module, the embedded stem micro-change sensor and the thermal infrared imager are cooperated to monitor the physiological dynamic state of crops in a multi-mode manner, the occurrence of water stress can be accurately identified in an early stage, a capillary pulse spray irrigation mode is automatically started when the water stress is identified, and on-demand, accurate, small-flow and high-frequency water supply is realized; the timeliness and physiological suitability of irrigation response are remarkably improved, the appropriate water potential of the root zone can be effectively maintained, efficient absorption and utilization of water are promoted, waste of water resources is reduced, and meanwhile normal physiological metabolism of crops is guaranteed.

The invention relates to the technical field of intelligent irrigation, and discloses an intelligent irrigation system for a fruit tree planting greenhouse. The system comprises a multi-dimensional data acquisition module, a data fusion processing module, an irrigation decision module and an irrigation control execution module which are connected in sequence. The system obtains a root soil image, a leaf surface temperature distribution map and stem micro-deformation data, and performs multi-dimensional fusion calculation to generate a spatial water potential distribution map capable of representing the overall moisture condition of crops. And calculating specific regional water demand and preferential irrigation sites based on the map, and further driving an execution terminal to realize precise irrigation. According to the method, the physiological water demand signal of the crop can be responded, the spatial difference of water stress can be identified, the limitation that the traditional technology depends on single soil information is overcome, the crossing from environment monitoring to crop body sensing is realized, and the irrigation accuracy and the water resource utilization efficiency are improved.

The application provides a soil vertical water flux monitoring method and system, and belongs to the technical field of soil water monitoring. The method comprises the following steps: collecting multi-layer soil water content and water potential data in real time, calculating soil vertical water flux of each layer by combining soil hydraulic conductivity, and determining soil water balance plane depth by detecting vertical water flux direction change. The upward evapotranspiration flux and downward seepage flux are calculated respectively based on the balance plane. The application can accurately identify the balance plane of vertical water migration direction change, realize synchronous dynamic monitoring of evapotranspiration and seepage, and effectively improve the continuity and accuracy of soil vertical water flux monitoring.

The invention discloses a fertilization method and system for improving CO2 absorption efficiency of greenhouse plants based on an SPAC system. The method comprises the following steps: acquiring moisture information and environment information of the greenhouse plants through a biological environment information acquisition module deployed in a greenhouse; according to the obtained moisture information and environment information, the current leaf water potential and the saturation vapor pressure difference are calculated; calculating the stomatal conductance of the plant by combining the soil water potential and the atmospheric pressure according to the calculated current leaf water potential and saturation vapor pressure difference; and regulating and controlling water and CO2 fertilization of the greenhouse plants according to the stomatal conductance of the plants. By means of the method, under the condition that the evaporation intensity is too high, plant water stress can be weakened, stomatal opening is promoted, stomatal conductivity and mesophyll conductivity are improved, CO2 absorption and utilization are promoted, the photosynthesis efficiency of greenhouse fruits and vegetables can be effectively improved, and plant growth and yield formation are promoted.

The application discloses a kind of based on the growth environment multi-factor comprehensive monitoring method and system of old tree protection, including step (S1) non-invasive perception network construction: in the crown layer area of old tree deployment meteorological monitoring unit, real-time acquisition photosynthetic active radiation intensity PAR and crown layer surface temperature T c ; with trunk as center, soil sensor array is radially laid in root distribution area, and soil volume water content θ and soil water potential are monitored in layers;Micro-invasive thermal diffusion probe is installed at the breast diameter of trunk, and xylem original liquid flow flux SF raw Is continuously measured, and initial liquid flow flux SF raw Calibration is carried out;Foundation interferometric radar is erected outside the protection zone, and three-dimensional spatial distribution point cloud P r Of root is obtained by surface scanning.This application can realize more comprehensive old tree monitoring, and timely find the existing abnormality of old tree environment.

This invention discloses a smart irrigation management system based on soil and crop moisture status identification, belonging to the field of crop moisture status monitoring technology. The system includes: acquiring leaf electrophysiological signal sequences and multi-depth water potential parameters of the rhizosphere microdomain of the target crop; determining the onset time of water stress and its corresponding first characteristic frequency based on the leaf electrophysiological signal sequences; determining the active water-uptake layer and its corresponding second characteristic water potential based on the multi-depth water potential parameters; performing a coupled comparison based on the first characteristic frequency and the second characteristic water potential, and determining whether irrigation triggering conditions are met based on the comparison results. If the irrigation triggering conditions are met, a differentiated irrigation quota is determined for different irrigation areas. This invention determines irrigation triggering conditions by comparing the consistency and degree of deviation between the first and second deviation directions, avoiding premature or late irrigation caused by misjudgment based on a single indicator.

This application discloses a greenhouse water control method and system based on the root zone-plant-atmosphere system. The method includes: acquiring soil water potential, plant water potential, air temperature, and relative humidity information in real time through an information acquisition module; calculating atmospheric water potential based on the acquired air temperature and relative humidity; calculating transpiration pull and water supply power based on the atmospheric water potential, plant water potential, and soil water potential; determining the stomatal aperture of the greenhouse plant based on the ratio of transpiration pull to water supply power; and issuing control commands based on the stomatal aperture and the ratio of transpiration pull to water supply power to achieve water control of the greenhouse plant. The method adopted in this application is simple and efficient. By comprehensively controlling water based on the relative relationship between water supply power and transpiration pull, it can maintain the water supply and demand balance of the root zone-plant-atmosphere system, effectively reduce evaporation and conserve energy, and improve crop photosynthetic capacity, yield, and water use efficiency.

The invention relates to the technical field of agricultural information and intelligent sensors, and discloses a farmland soil moisture content real-time monitoring method based on multi-sensor fusion. The method comprises the steps that passive sensing nodes integrating water content, temperature, conductivity and water potential sensors are arranged, soil micro-vibration is converted into electric energy through a piezoelectric energy collection module and stored in a super capacitor, and low-power-consumption wide-area synchronous communication is achieved through the narrowband Internet of Things; and the cloud carries out time alignment, abnormity elimination and fusion processing on the multi-source data to generate a soil moisture status field, and outputs an irrigation decision in combination with a crop growth model. According to the invention, high-precision, self-powered and maintenance-free soil moisture content in-situ monitoring and intelligent irrigation closed-loop control are realized.

The application discloses a kind of dry cultivation potato M ridge mechanized planting method, belong to potato planting field, comprising: first, the terrain slope of planting plot is collected, topological skeleton curvature is calculated after filtering, clustering extraction topographic feature point, construct weight matrix to obtain weighted slope, simultaneously obtain seed potato characteristic tensor, combined with soil moisture content, obtain ridge height, fertilization depth and cover thickness;Again, time series data such as leaf water potential, rainfall intensity are synchronously collected, time domain vector and frequency domain matrix are constructed after wavelet decomposition and empirical mode decomposition, generate stress tensor and calculate its Frobenius norm as state machine trigger index;Finally, the index is acquired in real time, when threshold is reached, start three-level regulation, each regulation is provided with boundary constraint;Solve the problem that ridge body parameter in traditional planting is poor in adaptability, water management is fixed and stress regulation is not accurate, etc., improve the scientific and mechanized level of dry cultivation potato planting.

The invention relates to the technical field, in particular to a soil priority flow degree measuring and evaluating method based on an intelligent sensing element, in the method, by extracting the moisture content variable amplitude in a sensing node response sequence and combining the node space angle difference, a marking structure with the sudden change direction is constructed, dynamic spatialization expression of the local water potential is effectively achieved, and the measuring accuracy of the soil priority flow degree is improved. The modeling operation of the node connection relation is combined with the path directivity information, the continuity expression ability of the jump response is improved, the segmentation identification of the path spatial form is realized, and through the scoring mechanism constructed by the amplitude peak value extraction and path frequency statistics, the method has the advantages of high efficiency and high reliability. According to the method, the spatial analysis precision, the time process coherence and the jump path judgment accuracy are integrally improved, so that the identification of the preferential flow path in the soil body has a higher automation level, a standardized and stable judgment result can be formed, and moisture migration risk assessment and resource regulation and control strategy output under multiple scenes are supported.

The present application provides a sand ecological-hydrological process critical threshold identification system and application thereof, comprising a multi-parameter sample collection device, a soil physicochemical index determination module, a vegetation water stress response monitoring module, a critical threshold calculation unit and a steady state transition early warning module; by determining soil aggregate stability index data and soil water characteristic curve data, monitoring vegetation transpiration conductance data and leaf water potential data, using multi-level lag response analysis and dynamic response surface construction method, calculating critical water content threshold value and steady state transition critical point data, accurate identification and dynamic early warning of sand ecological system steady state transition are realized.

This invention relates to the field of environmental monitoring technology, specifically to a smart digital rural environmental monitoring system and method based on big data. The system includes a stratified water potential acquisition module, a gradient inversion correction module, a path inversion modeling module, and a multidimensional diffusion modeling module. The stratified water potential acquisition module calculates and generates rural soil environmental monitoring data. This data includes stratified soil water potential distribution, soil moisture content gradient, and soil electrical conductivity characteristics. Abnormal soil water flow data includes vertical water potential difference, abnormal flow direction vector, and flow intensity level. The water infiltration path distribution map includes the infiltration path distribution structure, soil water potential accumulation intervals, and flow propagation direction indicators. The diffusion boundary space model includes the pollutant diffusion boundary range, water lateral migration area, and multidimensional diffusion rate distribution. This solution quantifies the abnormal distribution range, duration, and development trend, improving the accuracy of judging abnormal infiltration and diffusion processes.

The invention relates to the technical field of wastewater treatment, in particular to a composite wastewater treatment device based on ionizing radiation, which comprises an ionizing radiation module and an energy recovery module. And the ionization irradiation module is used for performing irradiation treatment on the flowing water body. The flowing water body is waste water flowing downwards along the inner wall of the reactor from the high position in a water film mode. The energy recovery module is arranged at the bottom of the flowing water falling area and used for converting kinetic energy generated by falling of the flowing water into electric energy and conducting energy storage or real-time power supply. The ionizing radiation water treatment and the water potential energy power generation technology are integrated, so that the problems of high energy consumption, complex system, low resource recovery rate and the like generally existing in the existing high-salt organic wastewater treatment technology are solved.

The invention discloses a method for reducing the noon break proportion of citrus stomata based on moisture regulation and control, and particularly relates to the technical field of fruit tree physiological regulation and control. The method comprises the following steps: acquiring a citrus leaf stomatal opening time sequence G (t) and a leaf water potential parameter psi (t), and constructing a stomatal activity response model M1; setting a target noon time period, and calculating a pore closing proportion; establishing a moisture regulation response model M2 according to the soil moisture content and the transpiration rate, and predicting psi (t) changes under different irrigation conditions; inputting the psi (t) output by the M2 into the M1, predicting the influence of different moisture regulation and control strategies on the theta m, and selecting an optimal irrigation scheme to control the target irrigation time, water volume and frequency; dynamic iterative optimization is carried out through theta m actual measurement and a model self-learning mechanism, and accurate moisture management and pore behavior regulation and control are achieved; the method has high adaptability, intellectualization and self-evolution ability, the noon stomata closing proportion can be effectively reduced, and the photosynthetic efficiency and the fruit tree yield are improved.

The invention provides a garden soil humidity monitoring method and system. The method comprises the following steps: determining water potential permeation confidence among soil layers according to soil humidity data in a garden monitoring area and historical soil humidity data of the garden monitoring area; obtaining an interlayer moisture abnormity mark of the garden monitoring area; determining discrete features of soil humidity in the garden monitoring area based on the soil humidity data and a preset humidity value of the garden monitoring area, and determining a fluctuation trend of soil moisture in the garden monitoring area in a preset time period according to the discrete features and all the water potential permeation confidence pairs; and performing early warning analysis on the soil humidity of the garden monitoring area through the fluctuation trend and the interlayer moisture anomaly mark to obtain early warning information of the soil humidity in the garden monitoring area. By adopting the scheme of the invention, the influence of the dynamic process cutting of the soil moisture on the monitoring of the soil humidity in the garden can be reduced.

The application discloses a kind of saline-alkali soil crops stem xylem water potential prediction method and related equipment.The method comprises: using cloud migration optimization algorithm to optimize nonlinear Arp algorithm parameters, and cloud migration optimization algorithm and nonlinear Arp algorithm are constructed into integral cloud migration optimization-nonlinear Arp algorithm;Based on the stem xylem water potential data set collected, the crop stem xylem water potential model constructed by cloud migration optimization-nonlinear Arp algorithm is trained, and SHAP interpreter is used to optimize input factor;Based on the trained crop stem xylem water potential model, the saline-alkali soil crop stem xylem water potential is predicted.It can solve the problem that the traditional soil moisture or soil water potential determination method can only determine soil matric potential, it is difficult to determine the superposition water potential of osmotic potential and matric potential, and it is more difficult to accurately determine the time when crop physiological drought occurs.

The invention provides a sand ecological-hydrological process critical threshold recognition system and application thereof. The sand ecological-hydrological process critical threshold recognition system comprises a multi-parameter sample collection device, a soil physicochemical index measurement module, a vegetation water stress response monitoring module, a critical threshold calculation unit and a steady-state transition early warning module. The method comprises the following steps: measuring soil aggregate stability index data and soil moisture characteristic curve data, monitoring vegetation transpiration conductance data and leaf water potential data, and calculating a critical moisture content threshold value and steady-state transition critical point data by adopting a multi-level lag response analysis and dynamic response curved surface construction method; and accurate identification and dynamic early warning of steady-state transition of the sand ecosystem are realized.