69 results about "Soil volume" patented technology

The invention discloses a soil water and salt dynamic monitoring and quality evaluation method based on multispectral remote sensing, and relates to the field of geological monitoring, and the method comprises the steps: carrying out the scattering deviation correction and roughness correction of an observation spectrum through a satellite remote sensing image, an unmanned aerial vehicle multispectral image, a ground sample and meteorological driving data; the soil intrinsic reflectivity, the vegetation coverage component and the salt crusting component are obtained; a water-salt inversion model is established by combining thermal infrared and red edge wave band information, and multi-temporal soil volumetric moisture content and surface salinity index are inverted; by introducing meteorological conditions and vegetation dynamic characteristics, a water-salt coupling partial differential equation and a graph space-time constraint model are constructed, and continuous space-time distribution of soil water content and salinity is obtained; extracting salinity, moisture, vegetation response and soil health indexes, establishing a soil quality comprehensive evaluation model, and outputting high-risk plaques and a treatment priority sequence. The method realizes dynamic monitoring and quality grading evaluation of soil water and salt, and is suitable for saline-alkali soil treatment and ecological restoration.

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 discloses an intelligent irrigation dynamic regulation and control method and system based on multi-source data. The method comprises the steps that the daily total water demand volume is calculated; acquiring the volume moisture content of the soil of the surface layer and the main root system layer in real time through an array sensor, and calculating the real-time infiltration gradient between the surface layer and the main root system layer; and executing a pulse irrigation process formed by alternation of irrigation pulses and infiltration waiting pulses, stopping water supply when the volumetric water content of the surface layer reaches a first preset threshold value, starting next water supply when the real-time infiltration gradient is lower than a second preset threshold value, and stopping water supply until the accumulated irrigation amount reaches the daily total required water volume or deep layer leakage is monitored. The system is used for executing the method. According to the method, the soil internal infiltration gradient serves as the physical basis of pulse start and stop, efficient conveying of water to deep soil is achieved, the contradiction that surface runoff and deep root system water shortage coexist is solved, and the water utilization rate is increased.

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 field of data analysis, in particular to a farmland soil compaction diagnosis method based on multi-source sensor data, and the method comprises the steps: carrying out the gradient energy feature construction and phase alignment cross-correlation evaluation of soil resistance depth curve data, and obtaining a gradient energy phase locking factor; carrying out rheological consistency coupling evaluation on the morphological characteristics of the soil resistance depth curve and the soil volume moisture content to obtain a rheological morphological coupling factor; performing joint correction on the basic Euclidean distance to obtain an adaptive similarity distance and executing clustering iteration; spatial modeling and prescription mapping are carried out on a clustering result and sampling point position information, so that a soil compaction accurate diagnostic graph is obtained, and a differentiated subsoiling operation instruction is generated; the method solves the problem that the existing Euclidean distance easily causes the characteristic dislocation of the compaction layer and the deformation of the rheological strength under the condition of farmland micro-topography fluctuation and water content difference to cause the distortion of the clustering partition.

This invention provides a method and tool for applying soil to fruit trees in holes. The method includes the following steps: S1, acquiring a tool for applying soil to fruit trees in holes; S2, based on the tool, performing a constant soil volume transport control scheme determination step for each fruit tree, wherein the constant soil volume transport control scheme determination step includes: S21, acquiring tool parameter information of the tool for applying soil to fruit trees in holes; S22, preset the feed speed V of the tool for drilling soil in holes. y and volume per unit time V 体 S23, Based on tool parameter information and feed rate V y Volume per unit time V 体 S2. Obtain the rotational speed V of the fruit tree hole-applying tool at each feed time t; S3. Based on the control scheme obtained in step S2, control the rotational speed V of the fruit tree hole-applying tool at each feed time t to achieve constant soil volume delivery for fruit tree hole application. This invention uses a dynamic balance method for soil delivery volume to effectively prevent problems such as drilling process jamming and untimely soil delivery, thereby improving drilling efficiency and fertilization effect.

The invention provides a sponge city construction full-permeable road rainwater collection system mechanism, and relates to the field of road construction, the sponge city construction full-permeable road rainwater collection system mechanism comprises a support bottom plate, a collection cylinder and a mounting support rod, the support bottom plate is in a square frame shape, four corners of the support bottom plate are provided with four connecting cavities with outward openings, and the positions of the connecting cavities are symmetrical. The rainwater is collected through the collecting groove, the rainwater is guided to flow into the closed cavity through the guide groove, at the moment, a part of the rainwater downwards falls into the soil in the filling space through the guide hole to achieve the absorbing and supporting effects, and after the rainwater is absorbed, the soil in the filling space is expanded in volume and complements each other to achieve the supporting effect; in rainy days, earthquakes and other special disasters, if the outer wall of the filling cavity is broken, the foam joint mixture stored in the filling cavity flows outwards into soil gaps in the filling space and the collecting cavity, and the effects of reinforcement and stabilization are achieved through the foam joint mixture.

The invention discloses a soil moisture content prediction system, which relates to the technical field of soil monitoring and comprises a small-core processor module, a large-core processor module and a sensor module, the large-core processor module is deployed with a large language model and a visual model; the sensor module collects environmental parameter data of a target soil area in real time; the small-core processor module stores the environment parameter data collected in real time to a local cache; the large-core processor module is used for synchronizing locally cached environment parameter data to a memory of the large-core processor module when the large-core processor module is powered on, the sensor module is controlled to collect an environment image, and the visual model analyzes the environment image to obtain image analysis text content; the large language model predicts the soil volumetric water content in a future set time period according to the input information; the input information comprises the image analysis text content and the environment parameter data at the corresponding moment. According to the invention, system power consumption can be reduced, and high-computing-power data analysis and timely prediction of soil volumetric water content can be realized.

The invention provides a shield muck improvement method for a water-rich coarse-particle stratum, and relates to the technical field of shield muck improvement, and the method comprises the following steps: calculating the volume Vs of a soil body cut by a cutter head of a shield tunneling machine in unit time according to the excavation diameter D and the tunneling speed v of the shield tunneling machine and the loose coefficient K of the coarse-particle stratum; calculating the flow q of the calcium-based clay mineral-sodium silicate mixed slurry in unit time by combining Vs with the injection ratio KIR; according to the preset volume ratio M of the calcium-based clay mineral slurry to the sodium silicate solution and the number N and q of the mixing containers, the flow qK and qG of the two raw materials in the single mixing container in unit time are calculated; starting a shield tunneling machine, pumping the two raw materials into a mixing container according to qK and qG by a pumping device to prepare mixed slurry, and injecting the mixed slurry into a soil bin to be mixed with shield muck. The mixed slurry mixes the shield muck with underground water by virtue of good bonding capacity, improves the plastic flow state of the muck, reduces the permeability, and avoids spewing and stagnant discharge of the muck, so that the stability of a tunnel face is guaranteed.

The invention provides a farmland nitrogen loss monitoring method and system based on multi-source data, and the method comprises the following steps: obtaining multi-source time sequence data of a target region; performing inversion to obtain the soil volumetric water content of each field parcel in the farmland parcel vector data; simulating to obtain the surface runoff and leakage of each field parcel in the farmland parcel vector data; constructing a nitrogen loss estimation model, and inputting the soil volumetric water content, the surface runoff and the leakage of each field in the farmland plot vector data into the nitrogen loss estimation model to obtain a nitrogen loss load corresponding to each field in the farmland plot vector data; and performing nitrogen loss risk monitoring on the field parcels in the target area according to the nitrogen loss load. Therefore, by applying the technical scheme of the application, the monitoring efficiency and the monitoring accuracy of the nitrogen loss of the farmland plot can be effectively improved.

This invention relates to the field of underground engineering construction monitoring technology, and provides a method and system for in-situ volume inversion of shield tunnel excavated soil based on multiphase material balance. The method includes: acquiring three-dimensional point cloud data of the excavated soil surface and the conveyor belt speed; for each moment, projecting the three-dimensional point cloud data onto a direction perpendicular to the conveyor belt reference plane, and calculating the effective area of ​​the cross-section using the polygon area formula; within the time period of one tunneling ring, calculating the integral of the product of the effective area of ​​the cross-section and the conveyor belt speed at each moment to obtain the cumulative loose volume; and using a multiphase material balance correction model, inverting the cumulative loose volume into the in-situ soil volume. This eliminates the influence of soil conditioner and accurately inverts the true in-situ soil volume.

This invention relates to the field of data analysis, and more particularly to a method for assessing farmland soil quality based on multi-source sensor information fusion. The method includes: constructing gradient energy features and performing phase-aligned cross-correlation assessment on soil resistance depth curve data to obtain a gradient energy phase-locking factor; performing rheological consistency coupling assessment on the morphological features of the soil resistance depth curve and soil volumetric water content to obtain a rheological morphology coupling factor; jointly correcting the basic Euclidean distance to obtain an adaptive similarity distance and performing clustering iterations; and performing spatial modeling and prescription mapping on the clustering results and sampling point location information to obtain a precise soil compaction diagnostic map and generate differentiated deep loosening operation instructions. This addresses the problem that existing Euclidean distances easily cause misalignment of compaction layer features and distortion of rheological intensity under farmland micro-topographic undulations and water content differences, leading to distorted clustering partitions.

The present application relates to the technical field of composite material nondestructive testing and structure health monitoring, in particular to a new energy composite material micro-crack testing method based on ultrasonic echo; comprising: obtaining the time sequence ultrasonic echo signal of the target composite material in a continuous time period, and synchronously obtaining the soil volume water content and soil temperature; extracting the echo attenuation coefficient under different soil volume water contents, and analyzing the water saturation degree of micro-cracks; combining the soil humidity change curve and the water saturation degree change curve to calculate the capillary water absorption response coefficient; inputting the water machine coupling degradation prediction model to calculate the material degradation rate and the residual strength reduction coefficient; combining the future meteorological prediction data to extrapolate the water-sensitive micro-crack risk index, and obtaining the dynamic warning of the remaining safe life; the present application realizes the improvement from single static detection to the identification of the internal medium state of cracks.

This invention discloses an irrigation index prediction method based on meteorological data and field capacity, belonging to the field of smart agriculture technology. The method includes collecting real-time meteorological data, real-time soil volumetric water content data, soil matrix potential data, and future precipitation forecast data, and performing quality control and time alignment processing to obtain a multi-source dataset. Based on the real-time meteorological data, a reference crop evapotranspiration is calculated, and combined with the crop coefficient, the actual water requirement of the crop is obtained. Based on the real-time soil volumetric water content data and the static parameter value of field capacity, a water stress coefficient is calculated, and combined with future precipitation forecast data, a basic irrigation demand index is obtained. This invention uses the Shuttleworth-Wallace model to separate evapotranspiration and, based on multi-period rolling water balance calculation and risk decision rules, generates an irrigation index that integrates crop evapotranspiration, water deficit, and effective precipitation, achieving online calibration of soil parameters and optimization of irrigation decisions.

This utility model relates to a peanut inter-row tiller and hilling machine, belonging to the field of agricultural machinery technology. The technical solution is as follows: a hydraulic cylinder support is provided between the front beam and rear crossbeam of the frame. A hydraulic cylinder is mounted on the hydraulic cylinder support. Hydraulic cylinder mounting seats at both ends of the hydraulic cylinder are connected to the hydraulic cylinder support and the end support, respectively. The hydraulic cylinder drives the telescopic sleeve structure to extend and retract. The lower part of the hilling device mounting seat is hinged to the support arm via support arm bolts. Hilling wheels are located at the rear of the two hilling wheel mounting plates. The hilling wheels are arranged at an angle to the furrow line, with the two hilling wheels tilting in opposite directions, forming a V-shape with their openings facing rearward. The beneficial effects of this utility model are: the hilling height and soil volume can be adjusted according to the furrow width, ensuring that the peanut pegging reaches the soil during the flowering period, improving the peanut pegging rate and fruiting rate; the height of the hilling mechanism automatically adjusts according to the shape of the furrow, allowing for convenient adjustment of the hilling height and adaptation to the furrow width.

This application relates to the field of data processing technology, specifically to a method and system for efficiently detecting soil moisture content in sugarcane fields. The method includes: acquiring sampling point data and historical water consumption data from multiple sampling points in a sugarcane field area; clustering the multiple sampling points based on the sampling point data of each sampling point to obtain multiple sampling point clusters; determining the depth attenuation coefficient of each sampling point cluster based on the root density, soil dielectric constant, and historical water consumption data of the sampling points contained within each cluster; performing spatial interpolation processing on the soil volumetric water content of the sampling points contained within each cluster based on the depth attenuation coefficient of each sampling point cluster to obtain the whole-field moisture content distribution data of the sugarcane field area; and determining the total moisture content within the middle soil depth range based on the whole-field moisture content distribution data. This method can obtain accurate quantitative total moisture content within the middle soil depth range.

In the present invention, a controller determines a first pass target excavation depth on the basis of the end position for the excavation, the target soil volume, and the excavation distance. The controller executes a first pass excavation by moving a work machine to the first pass target excavation depth. The controller acquires the actual volume of soil excavated in the first pass. The controller corrects the target soil volume on the basis of the actual volume of soil. The controller determines a second pass target excavation depth on the basis of the corrected target soil volume. The controller executes a second pass excavation by moving the work machine to the second pass target excavation depth.

The invention relates to the technical field of soil physical property determination, and provides a flow-controllable variable-angle type soil moisture infiltration rate determination system and method.The system comprises a variable-angle supporting assembly (200) and a test column (300) used for controlling the rotation positioning angle, the test column (300) is a uniformly-distributed split type column body, and the variable-angle supporting assembly (200) is connected with the variable-angle supporting assembly (200). The closed connection part of the split type column body is sealed with test soil through a gasket (303); the top end of the test column (300) is connected with a flexible water supply assembly (400), the double-control visual compactor (100) is further included, and the compactor (100) is used for synchronously controlling the soil volume and the soil stress when the test soil in the test column (300) is compacted. According to the invention, the marginal effect is eliminated, undisturbed sampling is facilitated, the device is suitable for various angles, the flow can be accurately controlled, meanwhile, visual constant volume filling is realized by utilizing mechanical stress feedback, and high-precision measurement of the hydraulic characteristics of the soil of the Philip infiltration model is corrected based on compaction stress parameters.

This invention discloses a soil volumetric water content (VWC) measurement system based on LoRa-RSSI and a drone. The system comprises several underground LoRa nodes for collecting environmental monitoring data; a host computer embedded in the soil; and an aerial node carried by a small drone. Combining IoUT technology, this invention designs an innovative system for soil VWC measurement based on LoRa received signal strength and a drone. The system utilizes the changes in LoRa-RSSI between the soil's internal transmitter and the drone's aerial receiver during the drone's angular rotation. Combined with a Long Short-Term Memory (LSTM) network, it collects differential LoRa-RSSI values ​​and uses a deep learning (DL) algorithm to calculate soil VWC, achieving relatively accurate soil VWC data. This invention eliminates the need for depth measurement of VWC data, utilizes soft sensors to measure soil VWC, and offers low cost, high efficiency, and small measurement error, providing a novel approach for soil VWC measurement design.

The application discloses a kind of soil water salt dynamic monitoring and quality evaluation method based on multispectral remote sensing, it is related to geological monitoring field, the method includes by satellite remote sensing image, unmanned aerial vehicle multispectral image, ground sample and meteorological driving data, scattering correction and roughness correction are carried out to observation spectrum, obtain soil intrinsic reflectivity, vegetation cover component and salt crust component;Water salt inversion model is established in combination with thermal infrared and red edge band information, and multi-time phase soil volume moisture content and surface salt index are inverted;By introducing meteorological conditions and vegetation dynamic characteristics, water salt coupling partial differential equation and graph time and space constraint model are constructed, and the continuous time and space distribution of soil moisture content and salt is obtained;Salinity, water, vegetation response and soil health index are extracted, and soil quality comprehensive evaluation model is established, and high-risk patch and management priority order are output.The method realizes the dynamic monitoring and quality classification evaluation of soil water salt, and is suitable for saline-alkali soil management and ecological restoration.

The application discloses a kind of based on multi-source data fusion and machine learning's soil porosity in-situ detection method, comprising: soil porosity in-situ detection machine learning model is deployed in the industrial computer of soil porosity in-situ detection device, and soil sample to be measured is collected;Using time domain reflection sensor probe insertion obtains the soil volume water content, soil temperature and volume conductivity of nearby soil;Data acquisition module acquires the layered image of internal horizontal section of soil sample to be measured and the change curve of soil resistance;Data processing module processes data, respectively obtains image feature, the average value of volume conductivity and soil resistance at standard temperature 25 DEG C;Soil volume water content and obtained data are used as the characteristic data of soil sample to be measured, and the characteristic data is substituted into the trained soil porosity in-situ detection machine learning model, and the soil porosity of soil sample to be measured is calculated.The method can quickly detect soil porosity, and detection efficiency is fast, cost is low, and detection precision is high.

The invention discloses a cotton under-mulch drip irrigation intelligent regulation and control method based on soil moisture dynamic feedback, and relates to the technical field of agricultural irrigation, the method comprises the following specific steps: soil moisture data acquisition: in a cotton planting field, arranging a soil moisture sensor, the method comprises the following steps: collecting soil volumetric water content data of different depths of root zones in different growth periods of cotton in real time, and transmitting the collected data to a data processing unit; according to the method, a growth period weight dynamic distribution mechanism is introduced, an analytic hierarchy process is utilized to determine the weight ratio of each input factor in different growth periods, a dynamic feedback model is constructed in combination with multi-dimensional data collected in real time, the growth characteristics and water demand characteristics of cotton in different growth periods are accurately matched, accurate prediction of the soil moisture change trend is realized, and the method has good application prospects. And the pertinence, accuracy and intelligent level of drip irrigation regulation and control are improved.

The application relates to the technical field of saline-alkali soil improvement, and discloses a salt content dynamic prediction and regulation method for crop stress-resistant cultivation soil in saline-alkali soil, which predicts the soil salt content of the saline-alkali soil through a target soil salt content prediction model (including a ConvLSTM encoder, a physical constraint feature extraction layer and a Transformer encoder) to obtain a target soil conductivity prediction value and a target soil volume water content prediction value; then, the target soil conductivity prediction value, the target soil volume water content prediction value, a current soil volume water content and a preset salt content threshold are taken as inputs, a multi-objective optimization algorithm is used to solve a multi-objective optimization model which takes minimizing the soil conductivity exceeding value and the irrigation water consumption of the saline-alkali soil as a target and is constrained by the total daily irrigation amount and the dynamic soil volume water content, a target irrigation strategy is obtained, and the saline-alkali soil is irrigated; thus, a closed loop from prediction to regulation can be realized, and the saline-alkali soil management effect is improved.

The invention relates to the technical field of data processing, and discloses a soil thermal diffusion and moisture content collaborative inversion method based on distributed optical fiber temperature sensing, which comprises the following steps: S1, acquiring multi-layer soil temperature gradient data acquired by a distributed optical fiber temperature measurement system; s2, based on the multi-layer soil temperature gradient data, establishing a semi-empirical relation model between the soil temperature and the soil thermal diffusion coefficient; and S3, on the basis of a heat conduction mechanism, constructing a function relationship between the soil thermal diffusion coefficient and the soil volume moisture content. A distributed optical fiber temperature measurement system is used for obtaining multi-layer ground temperature data with sub-meter resolution, and the observation scale of the distributed optical fiber temperature measurement system effectively makes up the blank between a point sensor and a remote sensing technology. Finally, soil volume moisture content distribution information with high spatial resolution, spatial continuity and multiple depths is successfully obtained, and the core problem of scale mismatching in the prior art is fundamentally solved.

This invention proposes an excavated soil volume measurement system and method that can accurately determine the weight, volume, and specific gravity of excavated soil generated in a slurry pressure balance shield tunneling system at an appropriate time. [Solution] The excavated soil volume measurement system 1 includes a screw conveyor 3 that discharges excavated soil from the chamber 24 of the shield machine 2, a soil pumping pipe 4 connected to the screw conveyor 3, a hopper 5 located outside the shaft into which the excavated soil transported via the soil pumping pipe 4 is fed, a weighing scale 51 that measures the weight of the hopper 5, and a three-dimensional measuring device 8 that measures the shape of the hopper 5 from above.

The application discloses a kind of based on remote sensing and ground cooperation's field irrigation water consumption estimation method and device, belong to remote sensing technical field.It includes: obtaining multi-source remote sensing data and extracting optical vegetation index, surface albedo, surface temperature and backscattering coefficient;Obtain meteorological data, soil volume water content measured value and daily actual evapotranspiration measured value;Based on optical vegetation index, surface albedo, surface temperature, meteorological data and daily actual evapotranspiration measured value, construct deep neural network and predict daily actual evapotranspiration estimate value;According to backscattering coefficient, optical vegetation index and soil volume water content measured value, estimate root zone soil water storage change amount;According to daily actual evapotranspiration estimate value, root zone soil water storage change amount and effective precipitation, calculate the total irrigation water consumption estimate value of complete irrigation cycle.The application realizes the irrigation water consumption estimation of high precision of field scale, large range, all-weather continuous without need of canal head metering facility.

The invention discloses a rock-soil cohesive force measuring device and an arching effect calculating method. The rock-soil cohesive force measuring device comprises the following steps: acquiring a columnar soil sample of on-site undisturbed rock-soil; the soil sample is installed in a rock-soil cohesive force direct measuring device, axial tension is applied to the soil sample until the soil sample is broken, the total tension during breaking and friction force generated by a moving part of the device are measured, and the rock-soil cohesive force is directly calculated according to the cross section area of the soil sample; and substituting the directly measured cohesive force, the rock-soil volume weight and the preset safety coefficient into a semispherical soil arch limit radius formula, and calculating to obtain the suggested safe excavation radius of the tunnel vault. When the rock-soil body is a homogeneous medium and the normal stress at the potential slip crack surface is close to zero, the shear strength is degraded into the contribution of pure cohesive force, the device for directly measuring the breaking force of the broken rock-soil sample directly measures the cohesive force of the rock-soil through the relation between the breaking force and the area of the rock-soil sample, and finally a more accurate rock-soil cohesive force value is obtained.

The invention discloses a soil environment quality adjusting system and method for flower planting, and relates to the field of plant irrigation, and the method comprises the steps: dividing a collection region, obtaining basic environment characteristics, layering soil according to the vertical depth, arranging environment sensors, and constructing a reference correlation model of each layer based on environment parameters when no flower exists; calling the model in a planting area, constructing a flower influence model by combining environmental parameters with flowers and layered soil water content, and calculating actual water consumption of each layer by comparing the two models and combining soil volume and volume weight; then analyzing a water consumption time sequence, dividing a stable water consumption section and a transition section in combination with a flower image shot by a camera, and calculating a water consumption coefficient to construct a layered prediction water consumption model; and finally, calling the model according to the to-be-predicted region identifier and the flower variety, calculating the predicted water consumption and alternately irrigating in a layered manner. The water consumption demand can be accurately matched, water resource waste and growth water shortage are avoided, and the growth stability, quality and survival rate of flowers are improved.

The present application relates to the technical field of data prediction, in particular to a swelling soil swelling evaluation model construction method and system, comprising the following steps: collecting wetting and drying cycle data to construct closed state evolution coordinate sequence, using trapezoidal numerical integration algorithm to calculate single cycle hysteresis energy dissipation density, calculating structure damage increment to update structure integrity coefficient, constructing suction stress contribution factor and correcting real-time matrix suction, superimposing to obtain equivalent effective stress, using Lagrange interpolation combined with pore ratio relationship table to calculate pore ratio change and volume expansion rate. In the present application, the structure damage and integrity degradation are quantified by calculating the hysteresis energy dissipation value, the stress state is corrected by constructing the suction stress contribution factor, and the pore ratio change is deduced, thereby establishing a mechanical property prediction system based on energy dissipation and structure evolution, overcoming the limitations of static physical index evaluation, and significantly improving the prediction accuracy and applicability of swelling soil volume deformation.

This invention proposes a method, device, electronic device, and storage medium for estimating soil moisture, relating to the field of soil moisture monitoring technology. The method determines the soil wilting point moisture content of the test area based on soil gravity moisture content test data, and uses the soil dielectric constant corresponding to the wilting point moisture content as a reference soil dielectric constant. Based on ground-penetrating radar images of the test area, the soil dielectric constants at various underground locations in the test area are obtained. Using the reference soil dielectric constant and the soil dielectric constants at various underground locations in the test area, the soil moisture content at each underground location in the test area is estimated. This overcomes the systematic overestimation problem commonly found in existing methods, improving the overall accuracy and robustness of soil volumetric moisture content estimation in key scenarios such as arid, semi-arid regions, and shallow root zones.