163 results about "Soil properties" patented technology

The invention discloses a soil attribute intelligent prediction method and system based on a multi-dimensional dynamic scale, and relates to the technical field of soil prediction.The method comprises the steps that remote sensing images, terrain factors, meteorological factors and soil actual measurement sample data are collected and stored in a multi-source raster data bin in a unified mode; preprocessing the multi-source data, and constructing raster data in a unified format; combining terrain difference, land utilization and climate fluctuation, dynamically dividing a spatial scale, a time scale, a terrain layering scale and a land utilization pattern scale, and constructing a multi-dimensional dynamic scale feature expression vector; carrying out soil attribute modeling and training based on a multi-task deep neural network model; and applying the model to a non-actually-measured area, and outputting a prediction result and a spatial distribution map layer. The system comprises a multi-source raster data construction and management module, a multi-dimensional dynamic scale feature construction module and a soil attribute modeling and prediction module. The method can be used for forestry management and protection, resource management, ecological monitoring, resource evaluation and other scenes.

The invention discloses a power grid tower footing area vegetation restoration method based on biological source humic acid and application of the power grid tower footing area vegetation restoration method, and belongs to the technical field of ecological restoration and soil treatment. The technology aims at solving the problems of soil erosion and loss caused by environmental disturbance conditions such as vegetation damage in power grid construction, and the technical scheme mainly comprises the steps of adopting a soil improvement technology based on HFA or combining the HFA with other bio-fertilizers for use, and configuring a formula for plants suitable for planting and a vegetation management strategy. The method mainly comprises the following steps: measuring various physical and chemical factors of a soil sample around a tower footing, comparing the physical and chemical factors with an average (normal) value of local soil, and formulating the HFA use amount and concentration according to the results; investigating site conditions such as local weather, terrain, soil properties and the like, native plants and suitable plants, and formulating a plant planting formula and a comprehensive vegetation management scheme capable of iteratively growing in different seasons. According to the method, the vegetation restoration speed and environmental protection are both considered, and vegetation restoration and ecological environment improvement can be rapidly achieved.

The invention discloses a loess collapsibility evaluation method and system based on a geophysical prospecting test technology, and relates to the field of land exploration, and the method comprises the steps: laying regular detection grids in a to-be-evaluated loess site, and constructing a site geographic coordinate system; collecting Rayleigh wave signals in real time, inverting a transverse wave velocity profile, and collecting apparent resistivity data; a shallow soil sample is drilled, soil property parameters are measured, and a model is constructed according to the mapping relation between the field geophysical prospecting parameters and the soil property parameters; inputting the acquired data into the wave velocity-water content correlation model and the resistivity-dry density correlation model to generate a water content distribution field and a dry density distribution field; and calculating the collapsibility of loess in each detection grid based on a geophysical prospecting response equation of the collapsibility coefficient, outputting a collapsibility coefficient contour cloud picture, and judging the collapsibility grade of each grid and the distribution range of collapsed loess. The method has the advantages that the collapsibility distribution field and the contour cloud picture are generated through accurate non-intrusive data acquisition and model analysis, and a scientific basis is provided for engineering construction.

The invention relates to a soil microorganism recovery index processing method and system and electronic equipment. The method comprises the following steps: collecting a soil sample in a gradient sample area, and measuring soil microbiological indexes and soil attributes; taking the soil microorganism indexes as a mother sequence, taking the soil attributes as subsequences, calculating correlation coefficients and correlation degrees between the subsequences and the mother sequence, and determining key soil attributes influencing soil microorganism recovery; determining a weight value of the key soil attribute; based on the numerical values of the key soil attributes in the original ecological reference area and the damaged unrepaired area, combining the weight values of the key soil attributes, and adopting an improved soil restoration index model to calculate and obtain a soil microorganism restoration index; the technical problem that in existing mining area ecological restoration evaluation, an original ecological system is not used as a benchmark, and the soil microorganism restoration degree cannot be quantitatively represented is solved, and the technical effect of achieving objective, comparable and quantifiable accurate evaluation of the soil ecological function restoration degree is achieved.

The invention discloses a soil attribute high-precision mapping method and system for optimizing the sampling number by fusing an air-ground imaging hyperspectral technology, and belongs to the technical field of soil monitoring. The method comprises the following steps: collecting and preprocessing a regional unmanned aerial vehicle hyperspectral image; collecting a sample point soil sample and obtaining ground imaging hyperspectral data of the sample point soil sample; screening and optimizing a sample point subset based on ground imaging hyperspectral data, measuring the available phosphorus content and training a prediction model; segmenting and extracting a soil region in the unmanned aerial vehicle image by combining a vegetation index and a maximum between-cluster variance method; and carrying out wave band alignment and reflectivity correction on the ground imaging hyperspectrum and the unmanned aerial vehicle soil spectrum, complementing corrected unmanned aerial vehicle hyperspectral data, and inputting the corrected unmanned aerial vehicle hyperspectral data into a soil available phosphorus prediction model to carry out inversion mapping. The problems that ground imaging data coverage is insufficient and unmanned aerial vehicle data is easily affected by the environment are solved, and key technical support is provided for intelligent agriculture and accurate soil nutrient management.

The invention relates to the technical field of slope reinforcement, and provides a micro pile combination reinforcement method for a highway expansive soil slope, which comprises the following steps: when the current stability safety coefficient, the current uplift bearing capacity, the current shear strength and the current flexural bearing capacity all meet the corresponding preset conditions, taking the current design size parameter as the final design size parameter; and according to the final design size parameters, the grouting amount of each hole in a first pile of the steel pipe pile assembly and the grouting amount of each hole in a second pile of the cast-in-place pile assembly are determined, and the steel pipe pile assembly is constructed on the slope bottom face of the expansive soil slope according to the grouting amount of each hole in the first pile. And then a cast-in-place pile assembly is constructed on the slope face of the expansive soil slope according to the grouting amount of each hole in the second pile. According to the method, the influence of the expansive soil property on design and construction of the micro piles is fully considered, interaction and combined arrangement of the micro cast-in-place piles and the micro grouting steel pipe piles are integrated, the safety and reliability of slope reinforcement are guaranteed, material waste caused by excessive conservative is avoided, and operability is high.

The invention belongs to the technical field of shield tunnel construction, and discloses a shield tunnel deformation overrun correction pile group and a correction method. The correcting method comprises the following steps that (1) a high-pressure jet grouting method is adopted, grouting is conducted on a soil layer outside a single segment with deformation exceeding the limit to form a pile column on the outer circle face of the segment, the grouting pressure in the grouting process acts on the segment through the soil layer outside the segment, and therefore correcting pressure for correcting deformation of the segment with deformation exceeding the limit is generated; the correction pressure acting on the duct piece is adjusted by adjusting the grouting pressure and / or the slurry return pressure; and (2) the step (1) is repeated till correction of all the segments, with deformation exceeding the limit, of the shield tunnel is completed. The radial piles are formed on the outer side of the tunnel through the high-pressure jet grouting technology, the soil property around the tunnel is improved, meanwhile, the size of the correction force is controlled by controlling the slurry return pressure in the jet grouting process, accurate correction of the deformation over-limit shield tunnel is achieved, and the operation safety of the shield tunnel is effectively guaranteed.

The invention relates to an automatic control system and method for the ground angle of a rake lip of a trailing suction hopper dredger, the system comprises a rake arm / rake head hydraulic cylinder sensor, a data collecting and processing unit and monitoring software, and the rake arm / rake head hydraulic cylinder sensor is used for obtaining rake arm posture and rake lip hydraulic cylinder stroke information; the data collecting and processing unit is used for collecting sensor data, calculating the actual value of the current ground angle of the rake lip in real time, judging the deviation between the actual value and the current target ground angle, and if the deviation exceeds a preset tolerance threshold value, generating a rake lip angle control output signal and transmitting the rake lip angle control output signal to the rake lip angle hydraulic executing mechanism. The current ground angle of the rake lip is adjusted to be the target ground angle in real time; and the monitoring software is used for visually displaying the system state and supporting parameter configuration and remote access. Under the conditions of different construction areas, different digging depths and different soil properties, the rake lip is always kept within a set angle range, so that the rake head can break soil more favorably, and the construction efficiency and the operation stability of a ship are effectively improved.

The present invention discloses a method for improving the prediction accuracy of soil iron oxide based on an amplified hyperspectral dataset. The method comprises the following steps: amplifying the hyperspectral dataset and performing multiple fractional-order differential transformations on the original hyperspectral spectrum using a fractional-order differential algorithm; then combining the fractional-order differential spectra with the original spectrum to form different amplified hyperspectral databases to amplify the amount of original spectral data; establishing a 1D-CNN neural network model for each of the different amplified hyperspectral databases, where the independent variable is the hyperspectral reflectance value and the dependent variable is the soil iron oxide content; and selecting the optimal 1D-CNN model based on the models established for the different amplified databases. The present invention effectively solves the problem of low accuracy of deep learning models under small sample conditions, improves the applicability and effectiveness of deep learning models to a certain extent, effectively improves the existing prediction accuracy of soil iron oxide based on hyperspectral data, and provides new methods and ideas for hyperspectral prediction research of other soil properties.

The invention relates to a road construction project supervision construction real-time state monitoring method and system based on big data. The method comprises the following steps: analyzing multi-source monitoring data to obtain a field matrix set and an adjacent set; feature parameters are extracted based on the field matrix set, and clustering processing is carried out on the feature parameters to obtain a soil property partition set; performing initial risk calculation according to the set, calculating a risk propagation coefficient based on the set and an adjacent set, and constructing a dynamic risk field in combination with an initial risk calculation result; and evaluating the dynamic risk field to obtain a comprehensive evaluation result, and generating a corresponding control instruction according to the result. According to the method, the real-time performance of road construction project supervision construction state monitoring, the accuracy of risk assessment and the refinement level of construction management and control can be improved through data structural processing, soil property partition accurate division, dynamic risk field construction and the like.

The invention discloses a stiff composite pile construction detection method based on a quantum technology and an electromagnetic geophysical prospecting method, which comprises the following steps of: constructing a peripheral cement soil pile and a core pile, and doping an electromagnetic sensitive material into a cement soil curing agent; a quantum gravity gradiometer and an electromagnetic induction instrument which are integrated on construction equipment are used for collecting gravitational field and electromagnetic field data of a construction area in real time in the whole process of cement soil stirring and core pile pressing-in; the density, the water content distribution and the uniformity of the cement soil are inversed and regulated in real time, and an unfavorable geologic body is identified; dynamically adjusting construction parameters based on cement soil properties and geological conditions obtained by inversion, and performing targeted reinforcement on a bearing stratum; the pile end stress bubble formation and the pile-soil interaction effect are verified; and based on the multi-source data acquired in the whole process, generating a digital quality file of the single pile for quality acceptance. The method can realize a construction process, namely a detection process, a single pile, namely a sensor, and a global data driving decision.

The invention discloses a negative pressure screw anchor horizontal ultimate bearing capacity prediction method, and relates to the technical field of geotechnical engineering, and the method comprises the following steps: generating a construction resistance energy feature vector by using penetration time sequence data, inverting a soil body improvement factor through an energy-soil property mapping model, and correcting undisturbed soil parameters; and calculating and superposing the resistance of each subitem based on the correction parameter and the geometric parameter to obtain a predicted value. The method is used for solving the problem that an existing prediction method neglects the influence of construction disturbance on soil parameter remodeling, and consequently the bearing capacity prediction precision is insufficient.

The utility model relates to the technical field of hydraulic engineering, in particular to a foundation detection device for hydraulic engineering, which comprises a bottom plate and a sampling device, the upper surface of the bottom plate is fixedly connected with an assembly frame, the upper surface of the assembly frame is fixedly connected with a servo motor, the driving end of the servo motor is fixedly connected with a pneumatic rod, and the lower surface of the pneumatic rod is fixedly connected with a ground drilling rod. The lower surface of the bottom plate is rotatably connected with a round wheel, the sampling device is arranged on the surface of the bottom plate, the sampling device comprises a cylinder, and the cylinder is fixedly connected with the bottom plate. According to the utility model, when the earth drilling rod drills underground and then resets, the soft hairs timely scrape off the adhered soil, so that the sample collection is more complete, and the soil leakage loss is reduced; the original stratum information of the sample is retained to the maximum extent, reliable materials are provided for accurate analysis of the soil property of the foundation of the water conservancy project, the collected sample can be quickly and properly stored, the sample is prevented from being interfered by the external environment, the sample state is kept stable, and the subsequent long-time and high-precision detection requirement is met.

The present application relates to the technical field of ecological restoration, in particular to a new ecological substrate for ecological restoration of river bank slope and its preparation method and application. The raw materials of the new ecological substrate include planting soil, basalt fiber, nano-silicon dioxide and cement. The preparation method comprises the following steps: taking the planting soil, crushing, air-drying and then passing through a 2mm sieve; mixing and stirring the sieved planting soil, basalt fiber, nano-silicon dioxide and cement to obtain a solid mixture, then adding water to the solid mixture until the water content is 18.5-19.5%, and stirring uniformly to obtain the new ecological substrate. The new ecological substrate can greatly improve the strength of the soil, improve the toughness of the soil and enhance the anti-cracking property of the soil body, reduce the dependence on cement, and reduce carbon emissions. On the other hand, the substrate has a certain gain effect on plant growth, which can significantly promote the adjustment of soil properties and hydrological environment, and also has a positive effect on carbon sequestration.

This invention provides a method and apparatus for collecting earthworm burrow wall soil. The method includes collecting raw soil, adjusting the particle composition of the raw soil to obtain culture soil. A mesh screen is laid in a culture pot, and the culture soil is placed inside the mesh screen. Earthworms are placed in the culture soil, and the culture pot is placed in an incubator. The environmental parameters in the incubator are adjusted to allow the earthworms to construct burrows within the culture soil. A preset time is checked; if so, the culture soil is removed, and the burrow wall soil is peeled off. The culture soil balances plasticity and permeability to meet the needs of earthworm growth and burrow building during long-term cultivation. By adjusting the temperature, humidity, and light intensity in the incubator, the earthworms can fully construct burrows while maintaining stable burrow wall soil properties. A hard, pointed spoon is used to precisely peel off the burrow wall soil, ensuring that the burrow wall soil sample is free from cross-contamination and structurally intact.

The application discloses a soil property data layered database construction method, which comprises the following steps: collecting soil monitoring data and related data of a preset area, and preprocessing the soil monitoring data and the related data; calculating water and soil loss risk contribution degree depth weight based on soil erosion mechanism, acquiring texture continuity clustering weight according to continuous runs, judging and obtaining loss risk factors by parallel multi-conflict and conflict resolution through the water and soil loss risk contribution degree depth weight and the texture continuity clustering weight; calculating texture transfer entropy of different depths, determining that the current depth is a mutation point when the texture transfer entropy of two continuous depth points is greater than a mutation threshold, and adaptively optimizing layer section boundaries according to the mutation point to obtain layer section adjustment boundaries; and constructing a three-region interactive soil property data layered database according to the loss risk factors and the layer section adjustment boundaries, and outputting a target database.

The invention provides a soil organic carbon estimation method and device and electronic equipment, and the method comprises the steps: obtaining the site information of a target site; the site information comprises soil properties, environment data, vegetation data, position information and land utilization data of the target site; calling an initial physical model, and performing inversion to obtain an estimated value of a key parameter of the initial physical model based on the site information of the target site in the observation year; constructing a key parameter estimator, and performing training fine tuning on the key parameter estimator; and embedding the trained key parameter estimator into the initial physical model to obtain a physical and data hybrid driven soil organic carbon simulation model. According to the invention, the unification of model precision and interpretability is realized, and the problem of poor soil organic carbon estimation effect in the prior art is solved.

The utility model belongs to the technical field of tunnel reinforcement, and particularly relates to a tunnel undercrossing lakebed tunnel face reinforcement structure which comprises a base, an air cylinder fixedly connected to the middle of the top face of the base, a mounting plate fixedly connected to the upper end of the air cylinder, a connecting shaft arranged on the upper side of the mounting plate, and a first arc-shaped plate installed on the connecting shaft. The top of the first arc-shaped plate is movably connected with a plurality of drilling machines, machine shafts of the drilling machines are fixedly connected with drill bits, the rear side of the first arc-shaped plate is provided with a second arc-shaped plate, and the rear side of the second arc-shaped plate is fixedly connected with a plurality of conveying pipes. Then the first arc-shaped plate is rotated to be horizontally arranged towards the front side, the second arc-shaped plate is rotated to be vertically arranged, the upper ends of the conveying pipes are inserted into the corresponding grouting pipes correspondingly, grout is injected into the grouting pipes, the grout can permeate into the soil body, gaps among particles are filled with the grout, the grout is solidified, and the purpose of improving the characters of the soil layer is achieved.

This invention relates to the field of soil attribute prediction technology, and discloses a method and system for predicting soil attributes based on multi-source environmental and remote sensing data. The method includes: acquiring soil environmental and remote sensing image data of a target area, unifying and standardizing the spatiotemporal resolution to generate a standardized dataset; obtaining a feature matrix after fusion and dimensionality reduction, and using random forest and gradient boosting tree to conduct feature analysis and fitness assessment to determine an initial prediction model combination; adjusting weight parameters and feature mapping to form an adaptive prediction model; performing attribute prediction and combining anomaly detection and error correction to generate a prediction dataset; obtaining optimized distribution data through distribution calibration, spatial smoothing, and residual optimization; constructing and validating an attribute distribution map; and finally generating basic data for soil management strategies through confidence interval evaluation and data fusion. This method can solve the problem of insufficient prediction accuracy under complex working conditions.

The invention discloses a big-data-based cadmium accumulation character analysis method for multiflower kidney beans, and relates to the technical field of accumulation character analysis, and the method comprises the steps: collecting soil properties, environment information, multi-year grain cadmium and management records by taking a land parcel as a unit, constructing a land parcel safety index and an environment behavior feature vector, and dividing safety environment types; establishing a cadmium transmission meta-model in each safety environment type, and extracting a cadmium transmission fingerprint of the variety to obtain an inherent hazard baseline of the variety and a management controllable margin; calculating a safety margin, a safety yield, a safety profit and a multi-metal index based on the above results, setting a risk budget, and determining a safety domain and a minimum management adjustment amount; the safety characters are compared with agricultural land soil pollution risk management and control standards and food, green, organic and low-cadmium-accumulation variety guide rules, multi-year planting plans of land parcels, farmers and areas are formed, and safe utilization and income coordination of the multiflower kidney beans are achieved.

The application discloses a full-slope erosion and sediment transport simulation method combining soil properties and land use, collects corresponding erosion and sediment transport basic data of full slopes of beam and valley slopes in a basin, including soil data, terrain data, land use data, vegetation data and water and sediment data; based on the erosion and sediment transport basic data, terrain conditions and land use type boundary conditions, the erosion environment type of the full slope is automatically distinguished, and the initial to-be-optimized parameters affecting the erosion are obtained based on the erosion environment type; the initial to-be-optimized parameters are updated based on the cuckoo search algorithm until the optimal parameters are obtained; the slope combination and slope length in the terrain conditions and the land use type and vegetation coverage combination in the land use type boundary conditions are changed, a plurality of different scenes are obtained, the full-slope sediment production and transport evolution process is simulated based on the different scenes and the optimal parameters, and the slope sediment transport rate under different conditions is obtained.

The invention relates to the technical field of fruit and vegetable cultivation, and provides a water chestnut fertilization influence analysis method based on principal component analysis, which comprises the following steps: setting a plurality of field trials for different nitrogen, phosphorus and potassium fertilization level treatment; measuring plant growth indexes, yield indexes, corm quality indexes and soil physicochemical property indexes of the treated water chestnuts; performing principal component analysis on the measured multiple indexes, and extracting principal components of which the characteristic values are greater than 1; calculating comprehensive scores of the processing according to the scores of the principal components and sorting the comprehensive scores; according to the comprehensive score, evaluating the comprehensive influence of different fertilization treatments on the growth, yield, quality and soil properties of the water chestnuts, and screening out an optimal fertilization combination. According to the method, the matching of medium-low nitrogen and phosphorus and medium-high potassium is clear, so that high yield and high quality are guaranteed, soil acidification can be effectively relieved, excessive consumption of nutrients is avoided, synergism of fertilizer saving, efficiency improvement, soil health and quality improvement is realized, and data support and quantitative decision basis are provided for scientific fertilization of the water chestnuts.

The application discloses a kind of fusions of multi-source data and its spatial autocorrelation soil property spatial prediction method, the environmental variable of target area is collected;The environmental variable of the target area is respectively input into the linear relationship model of pre-trained soil property data and environmental variable and the nonlinear relationship model of pre-trained soil property data and environmental variable, respectively linear model soil property data prediction value and nonlinear model soil property data prediction value are obtained;Linear model soil property data prediction value and nonlinear model soil property data prediction value are fused using multi-scale geographic normalization weighted fusion model, and the final prediction value of the soil property data of the target area is obtained.The advantages are: the prediction result accuracy is greatly improved compared with the original fused data, and is better than conventional linear and nonlinear fusion method;The spatial autocorrelation of soil property is considered, and the application can maintain good prediction performance in various complex environments.

A soil property estimation device includes: captured image acquisition processor circuitry configured to acquire a captured image that is an image generated by capturing an image of a target region including soil in a state of shear failure caused by excavation of the soil; and soil property estimation processor circuitry configured to extract a failure region caused by the shear failure based on the captured image and to estimate a soil property that is a property of the soil based on the extracted failure region.

The application discloses a kind of soil organic carbon three-dimensional space mapping methods of fusing ground visible near infrared spectrum, it is related to soil property prediction technical field, in the method: based on the range of study area setting sampling point, extracts training set sampling point surface field ground visible near infrared spectrum principal component data, application Kennard-stone algorithm optimization reduces training set sampling point to one fourth, then obtain the field ground visible near infrared spectrum and soil organic carbon data of different depth of sampling point profile, and determine the best triangular grid parameter;Then construct SPDE model and solve using finite element method, make Gaussian Markov random field as spatial random effect, the principal component data of field ground visible near infrared spectrum of different depth of each sampling point profile as environmental covariate, application INLA model is carried out soil organic carbon three-dimensional space prediction, obtain the posterior distribution estimate, and soil organic carbon three-dimensional space mapping is carried out accordingly.The application can quickly obtain field ground visible near infrared spectrum, improve data acquisition efficiency, while fusing field ground visible near infrared spectrum principal component data, improve model prediction accuracy.

The invention discloses an intelligent prediction method for the remediation efficiency of acid-base obstacle soil based on machine learning. The intelligent prediction method mainly comprises the steps of subcritical carbon material directional preparation, soil acid-base obstacle simulation, remediation control and prediction model construction. The subcritical carbon material directional preparation comprises temperature setting, temperature rising, pressure stabilizing and cooling processes, the soil acid-base obstacle simulation comprises acidified soil simulation and salinized soil simulation, remediation control is carried out in the simulated acid-base obstacle soil, a comprehensive database containing subcritical carbon material parameters, soil properties and remediation effects is established, and the subcritical carbon material remediation method is applied to soil remediation. The model construction comprises subcritical carbon material classification, soil data acquisition, machine learning prediction and a restoration scheme generation module. The method overcomes the defects that a traditional method depends on experience trial and error and is low in precision and single in scheme, intelligent prediction of the remediation efficiency of the acid-base obstacle soil is achieved, and a scientific basis is provided for soil remediation engineering.

The invention relates to the technical field of soil environment treatment, and discloses a modifier for soil mineralization, salt fixation and plant growth promotion in facility agriculture and application. The modifier comprises the following components: an iron-based mineralizer, a calcium-based mineralizer and a basic resource material and / or a water-retaining porous material. The components of the modifier are mixed with to-be-remediated soil for soil remediation. According to the modifier provided by the invention, the LDH-like natural mineral phase is naturally formed in situ in the soil by supplementing the deficient elements (iron base, calcium base and the like) for forming minerals in the soil, so that the in-situ mineralization fixation ('ion exchange-electrostatic adsorption-lattice embedding 'three-stage fixation path) of salt-based ions is completed, and the natural mineralization rule of the soil is met; the soil salt-based ions are directly and accurately fixed, the soil salinity is reduced, and the soil property is improved.

To realize a soil property determination technique that is more accurate and simpler.SOLUTION: A soil property determination device 1 comprises a sample container 11, a stirring unit 10, and a control unit 20. The sample container 11 accommodates a sample formed by aggregating soil to be subjected to soil property determination. The stirring unit 10 stirs the sample accommodated in the sample container 11. The control unit 20 controls the stirring unit 10 on the basis of control parameters for the stirring unit 10, and acquires a response of the sample to stirring on the basis of the control parameters. The control unit 20 determines a soil property of the sample on the basis of the response of the sample to stirring.SELECTED DRAWING: Figure 1

The invention discloses a water conservation evaluation system and method based on ecological protection engineering, and relates to the technical field of water conservation evaluation, the system comprises an information acquisition module, an analysis and calculation module, an evaluation module and a database, grid division is performed on a monitoring drainage basin to obtain drainage basin units, and monitoring moments are set; the rainfall, land utilization type, potential evapotranspiration and soil attribute information of each drainage basin unit are collected at each monitoring moment, the monitoring drainage basin is divided into a marked area and each ecological engineering area, the water conservation amount of each drainage basin unit is calculated according to monitored data for the marked area, and the water conservation amount of each ecological engineering protection area is calculated according to the monitored data for each ecological engineering protection area. According to the method, the influence of each ecological protection project on soil is analyzed, the water conservation amount of each drainage basin unit is calculated according to the analysis result, and the change characteristics of the water conservation amount are obtained through Sen + M-K trend analysis, so that the calculation accuracy and effectiveness of the monitoring drainage basin water conservation amount are guaranteed, the calculation cost is reduced, and the ecological protection project can be monitored for a long time.

Sensor device (1) for in-situ soil analysis, comprising: a sensor assembly comprising one or more sensors that are individually or cumulatively configured for the simultaneous in-situ measurement of an absorption spectrum in a spectral range NIR-VIS-UV extending from NIR to UV and of at least one of the following soil properties of a soil to be analyzed (11) and for the provision of corresponding respective measurement data: (a) Impedance spectrum (b) temperature (c) acidic or basic character; wherein the distance defined between any two sensors of the sensor assembly with respect to their respective measuring quantity sensors does not exceed a value of 10 cm, wherein the sensor assembly for in-situ acquisition of an absorption spectrum of the soil to be analyzed (11) includes an absorption spectrometer assembly (5) which has: at least two MEMS absorption spectrometers (26a, 26b) whose spectral coverage differs at least for partial regions of the electromagnetic spectrum, so that cumulatively an absorption spectrum of the soil (11) to be analyzed can be acquired by the entirety of the MEMS absorption spectrometers (26a, 26b), which has components in the NIR, VIS and UV regions, wherein the absorption spectrometer assembly (5) further comprises a movable shutter device (28) configured to temporarily retract an aperture into a spatial region defined between the absorption spectrometers and the measurement surface, wherein a calibration reference (29) for calibrating at least one of the absorption spectrometers is arranged on the side of the aperture facing the absorption spectrometers.