85 results about "Water potential" patented technology

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 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 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 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.

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 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.

The present application relates to the field of agricultural engineering, and discloses a self-adaptive water supply system for corn greenhouse planting, which comprises an environment monitoring module for monitoring air temperature, air humidity, light intensity and concentration in the greenhouse; a growth monitoring module for monitoring corn leaf surface temperature and plant height; a soil monitoring module for monitoring soil temperature, soil moisture content and soil water potential; a root system analysis module for monitoring corn root system distribution depth and root system vigor index; and a control module connected with the environment monitoring module, the crop growth monitoring module, the soil monitoring module and the root system analysis module, for calculating irrigation water requirement according to the corn growth stage, soil moisture condition and root system distribution depth. The present application monitors corn root system distribution depth in real time through the root system analysis module, and introduces a root depth correction coefficient when calculating irrigation water requirement, so as to match water supply with the actual distribution area of root system, thereby improving water use efficiency.

The application provides a crop high-resistance variety intelligent breeding system and method based on multi-modal phenotype big data. The method comprises the following steps: synchronously acquiring a phenotype physiological sequence of a to-be-selected group in a field habitat and a micro-meteorological sequence including a photosynthetically active radiation flux; monitoring the photosynthetically active radiation flux, when the flux decreases and crosses a preset limit, interrupting a collection operation performed according to the phenotype physiological sequence, and resuming the collection operation after the light returns to be stable; during a stress period, when it is determined that the group approaches a physiological lethal critical point, starting drip irrigation, and connecting a water potential probe array, when a shallow probe reading jumps and a deep layer maintains an extremely dry reading, cutting off the drip irrigation, and constructing a shallow wet area by relying on the infiltration lag characteristics; and screening a target variety in combination with accumulated drought survival days and the phenotype physiological sequence. The application effectively avoids misjudgment caused by light fluctuation, and guarantees the objectivity and continuity of evaluation data on the premise of maintaining a deep layer forced boundary.

This invention relates to the field of smart agriculture technology, specifically to a decision-making system and method for Gastrodia elata cultivation under forest cover based on ecological simulation. The system includes: a data acquisition module for collecting environmental monitoring signals from the target cultivation area and historical growth data of the target plants; and a niche assessment module for calculating the niche suitability index of each planting unit based on the differences in microclimate characteristics between adjacent planting units within the target cultivation area, in response to the environmental monitoring signals. This invention generates a niche suitability index by calculating the microclimate characteristic difference sequence between adjacent planting units, enabling precise location of specific coordinates of environmental deviations during the decision-making process. This allows the system to identify areas of sudden changes in local temperature and humidity gradients or abnormal soil water potential, improving the accuracy of environmental perception from the plot level to the planting unit level, and providing a reliable data foundation for subsequent differentiated regulation.

An acquisition method of a crop drought condition, wherein the acquisition method is completed based on an instrument or a sensor, and the acquisition method comprises: training an operation model related to acquisition of a predetermined crop drought condition according to data collected by the instrument or the sensor, wherein the operation model comprises at least one of the following: a dry-wet edge model, a water content inversion model, a water potential acquisition model, and a drought condition acquisition model, and the following operation steps are sequentially executed by the operation model: acquisition of a water content sensitive index based on data collected by the sensor; inversion of predetermined soil water content and predetermined crop water content through the water content sensitive index; acquisition of water potential through the soil water content and the predetermined crop water content; acquisition of hydraulic transport resistance through the water potential; and obtaining of the drought condition of the predetermined crop through the hydraulic transport resistance.

The application provides a soil humidity detection method and system, soil water potential of each horizontal sampling point is determined through soil moisture of each horizontal sampling point, the attenuation rate of humidity diffusion in the horizontal scale in the target soil region is determined through all soil water potentials and soil moisture tension in the horizontal scale in the target soil region; the settlement coefficient of moisture in the target soil region is determined through soil moisture of each vertical sampling point, the penetration distribution of humidity in the depth scale in the target soil region is determined according to the settlement coefficient; the attenuation rate of humidity diffusion in the horizontal scale and the penetration distribution in the depth scale are fused in scale, and the diffusion gradient of humidity in the spatial scale in the target soil region is obtained; the target soil region is detected in confidence humidity based on the diffusion gradient of humidity, and the confidence humidity value of the target soil region is obtained; the application can realize multi-scale spatial detection of soil humidity, thereby increasing the credible range of soil humidity detection.

The invention discloses an integrated cultivation management system and method for codonopsis pilosula nnannf, and belongs to the technical field of cultivation management, and the method specifically comprises the following steps: collecting leaf reflection spectrum data and measuring internode length and leaf thickness in the early stage of row closing, calculating a saponin accumulation potential index, and dividing a land parcel into a high potential area and a low potential area according to the index; a phenolic acid substance rhizosphere is covered with a green light filtering light conversion film, and a low-potential area is covered with a light conversion film for increasing the proportion of an easily mineralized nitrogen source and enhancing red light transmission; monitoring the water potential of leaves in a high-potential area in a root system expansion period and implementing progressive moisture control, and determining an optimal harvesting period by monitoring a root system chromatic value and xylem hardness before harvesting; according to the method, a complete technical system from early diagnosis to differentiated management is constructed, and collaborative improvement of the quality and the yield of the codonopsis pilosula nnannf is achieved.

The application relates to the technical field of data processing, and discloses a garden landscape intelligent planning method based on digital twinning. The method acquires three-dimensional geological profile data of a planning area, establishes an underground soil porosity and saturation tensor field, and divides the underground space into a multi-scale hexahedral microenvironment grid; root system morphological parameters of a candidate plant community are acquired, and a plant physiological feature library containing a root system water absorption rate curve and a nutrient absorption spectrum is constructed; a spatial mapping topological relationship between an aboveground plant three-dimensional canopy model and the underground grid is established, and water potential gradient changes of the microenvironment grid under different aboveground layout schemes are calculated. The application quantitatively constrains the surface layout and the dynamic distribution of underground soil water and fertilizer, solves the problem that the surface layout is disconnected from the underground ecological carrying capacity in the prior art, leading to plant decline, and improves the ecological stability of the digital twinning planning scheme.

This invention discloses a numerical analysis method for fluid-structure interaction (FSI) of unsaturated slopes under free drainage conditions, belonging to the field of numerical analysis technology for slope engineering. The method includes: constructing an unsaturated multi-source parameter model of the slope region; building a dynamic boundary model with hysteresis response and gradual release characteristics based on boundary element water content, water potential gradient, and rainfall input information; jointly updating the internal water content gradient, local structural changes, and permeability coefficient field of the slope; correcting the seepage direction through a path enhancement factor; and identifying local preferential flow channels and seepage concentration areas. Iterative solutions are then obtained through adaptive time step adjustment, residual convergence control, and anomaly element correction strategies. This method improves the physical consistency of the free drainage boundary description, enhances the ability to identify preferential flow channels and local seepage concentration areas, and improves the computational stability and engineering applicability of FSI analysis of unsaturated slopes.

The invention discloses a saline-alkali soil crop stem xylem water potential prediction method and related equipment. The method comprises the following steps: optimizing parameters of a nonlinear Arp algorithm by using a cloud migration optimization algorithm, and constructing the cloud migration optimization algorithm and the nonlinear Arp algorithm into an overall cloud migration optimization-nonlinear Arp algorithm; training a crop stem xylem water potential model constructed by a cloud migration optimization-nonlinear Arp algorithm based on the collected stem xylem water potential data set, and optimizing an input factor by using an SHAP interpreter; and performing saline-alkali soil crop stem xylem water potential prediction based on the trained crop stem xylem water potential model. The problems that a traditional soil moisture or soil water potential measuring method can only measure the soil matrix potential, it is difficult to measure the superimposed water potential of the osmotic potential and the matrix potential, and it is more difficult to accurately measure the physiological drought occurrence time of crops can be solved.

The invention particularly relates to a method for determining a drainage key growth stage of farmland crops in a plain area, which relates to the technical field of farmland water management, and comprises the following steps: for each sampling moment, carrying out series superposition on canopy transpiration resistance and soil-root system interface resistance obtained by calculating soil water potential time sequence data; according to the method, micrometeorology and root zone soil water potential time sequence data are integrated, canopy transpiration resistance is calculated based on the energy balance principle, soil-root system interface resistance is connected in series and superposed to obtain the total transmission resistance of an SPAC system, then resistance abnormal events are analyzed and recognized through continuous wavelet transform multiple time scales, and quantitative scoring is achieved in combination with growth stage division. Through standardized processing, scientific threshold setting and a comprehensive scoring mechanism, the waterlogging risk difference of each growth stage can be accurately captured, the key drainage time period and the risk level are determined, accurate data support is provided for farmland drainage regulation and control, and water resource waste caused by blind drainage and crop output reduction caused by untimely drainage are avoided.