Soil monitoring sampling and processing device and method

Abstract

The application relates to the field of soil detection, in particular to a soil quality monitoring sampling treatment device and method, which comprises a probe rod main body in a sectional sleeve structure, is formed by longitudinally screwing a plurality of monitoring units which can be detached and correspond to specific soil depths, and is provided with a conical drill bit at the bottom; a leaching monitoring module is integrated in the probe rod main body and comprises a leaching solution injection system, a collector and a sensor array; the injection system is connected with a top injection interface through a pipeline; the collector is arranged in the monitoring unit; and the sensor array is arranged on the outer wall; a soil gas sampling module is also integrated therein and comprises a gas sampling head, a vacuum pump system and the like; the sampling head is connected with a valve group through a pipeline, and then connected with a vacuum pump and a detection unit; a control and data processing module comprises a plurality of components; the sectional sleeve structure forms a sealed cavity, and vertical stability and data independence are ensured. The application has the effect of solving the common technical problems of insufficient data representativeness and systematic defects under complex field conditions.

Description

Technical Field

[0001] This application relates to the field of soil testing, and in particular to a soil monitoring sampling and processing device and method. Background Technology

[0002] Soil is a vital material foundation for human survival, and its environmental condition directly impacts ecological security and agricultural product quality. In soil environmental research, in-situ leaching experiments are a crucial method for analyzing the vertical migration patterns of pollutants in soil under irrigation or rainfall conditions, providing significant guidance for farmland pollution control and land improvement. However, existing leaching experiments are mostly limited to indoor simulations of disturbed soil columns, making it difficult to accurately reflect the structural characteristics and seepage processes of in-situ soil in the field. Although some field leaching devices can collect samples, they generally lack the ability to simultaneously monitor the multi-level physical states (such as bulk density and moisture content) and chemical components of the soil profile, resulting in an inability to systematically analyze the dynamic migration mechanisms of pollutants in heterogeneous soil layers.

[0003] In the field of soil gas research, accurate in-situ gas sampling is a prerequisite for analyzing CO2, O2, and volatile organic compounds. Current soil gas sampling methods primarily employ direct borehole drilling or indirect measurement using sealed soil. The former is susceptible to interference from gas contamination during drilling, while the latter suffers from significant errors due to soil adsorption. Existing technologies have improved sampling accuracy through single-point extraction structures, but their single-tube, single-point design struggles to meet the multidimensional characterization needs of soil gases under spatially heterogeneous conditions. Furthermore, cross-contamination issues arising from vacuum shut-off backflow and residual gas in the pipeline are prominent. In addition, prolonged pre-extraction to eliminate interfering gases can disrupt the microenvironment surrounding the sampling point, while the pipeline memory effect further reduces data reliability during intermittent, multi-point sampling.

[0004] On the other hand, existing soil gas sampling and detection systems are usually separate. During sample transfer and storage, errors may be introduced due to changes in temperature and pressure or adsorption losses, and real-time verification of the sampling process is not possible. More importantly, soil gas dynamics are driven by environmental factors (such as air pressure, temperature, and humidity) and fluctuate over time. Traditional single or multiple averaging sampling methods are unable to capture their instantaneous changes, and the mean calculation is easily affected by extreme values, thus masking the true dynamic patterns. Summary of the Invention

[0005] To address the common technical challenges of insufficient data representativeness and systematic deficiencies under complex field conditions, this application provides a soil monitoring sampling and processing device and method.

[0006] This application provides a soil monitoring sampling and processing device and method, which adopts the following technical solution: A soil monitoring sampling and processing device and method, comprising: The probe body is a segmented casing structure. The probe body is composed of multiple detachable monitoring units connected longitudinally by threads. Each monitoring unit corresponds to a specific soil depth. A tapered drill bit is provided at the bottom of the probe body. The leaching monitoring module, integrated into the probe body, includes a leaching solution injection system, a leaching solution collector, and a sensor array. The leaching solution injection system is connected to the injection port at the top of the probe body via an injection pipeline. The leaching solution collector is located inside each of the monitoring units, and the sensor array is located on the outer wall of each of the monitoring units. The soil gas sampling module, integrated into the probe body, includes multiple gas sampling heads, a vacuum pump system, a valve group, and a gas detection unit. The gas sampling heads are disposed in each of the monitoring units. The gas sampling heads are connected to the valve group through sampling pipelines. The valve group is connected to the vacuum pump system and the gas detection unit. The control and data processing module includes a microcontroller, a data storage unit, a wireless transmission module, and a power supply. The microcontroller is electrically connected to the components of the leaching monitoring module and the soil gas sampling module. The segmented sleeve structure forms a sealed cavity through threaded connections, ensuring the vertical stability of each monitoring unit in the soil and the independence of data acquisition.

[0007] By adopting the above technical solutions, the segmented sleeve structure of the probe body, combined with the threaded connection, can flexibly adjust the depth configuration of each monitoring unit according to monitoring needs, adapting to different soil profile research scenarios. The threaded engagement forms a sealed cavity, effectively blocking external soil disturbance and ensuring the vertical stability of each monitoring unit. This avoids monitoring data deviations caused by probe tilting or displacement. The detachable design facilitates quick assembly and subsequent maintenance during field operations, reducing equipment wear and tear costs. In the leaching monitoring module, the injection system injects simulated leaching solution into the soil surface through the top interface. Combined with the collectors inside each monitoring unit, leachate at different depths is collected synchronously. The external wall sensor array monitors liquid phase parameters such as humidity, temperature, and pH in real time, accurately tracking the vertical migration path and rate of pollutants or tracers in the soil. The soil gas sampling module has multiple gas sampling heads distributed in each monitoring unit. Through the coordinated control of the valve group and vacuum pump system, soil gas at different depths can be collected sequentially or synchronously, avoiding cross-contamination of pipelines and gas backflow problems. The gas detection unit analyzes gas phase components such as CO2, O2, and VOCs in real time. The microcontroller of the control and data processing module uniformly schedules the operation of each module, realizing the automatic acquisition, storage, and wireless transmission of monitoring parameters. This not only improves the automation level of field operations, but also meets the needs of real-time monitoring and multi-location data sharing through cloud or host computer remote access functions.

[0008] Preferably, the solution injection system includes a storage tank, a peristaltic pump, and an injection pipeline, wherein the storage tank is connected to the injection interface via the peristaltic pump; The leachate collector includes a porous ceramic head, a filter membrane, and a micro-liquid pump. The porous ceramic head is fitted with the filter membrane, and the micro-liquid pump is connected to an external container via a hose. The leaching solution injection system and leaching solution collector work together to simulate natural rainfall or irrigation conditions, enabling in-situ reproduction of the soil leaching process.

[0009] By adopting the above technical solutions, the peristaltic pump can precisely control the leachate injection flow rate, making it highly matched with the intensity of natural rainfall or irrigation water flow, avoiding uneven soil infiltration caused by flow fluctuations, and restoring the authenticity of the initial experimental conditions. The modular design of the storage tank supports the loading of different types of simulated liquids, flexibly adapting to diverse research scenarios. In the leachate collector, the porous ceramic head simulates the pore structure of the soil surface, allowing the injected leachate to permeate evenly into the soil, replicating the spatial distribution characteristics of natural infiltration. The filter membrane effectively intercepts soil particles from entering the pipeline, preventing blockage and ensuring the purity of the collected leachate. The quantitative extraction function of the micro-liquid pump can achieve precise collection of leachate from different depths, avoiding sample cross-mixing.

[0010] Preferably, the gas sampling head includes a stainless steel tube and a gas permeable membrane, the gas permeable membrane covering the gas inlet end of the stainless steel tube; The vacuum pump system includes a main vacuum pump, a buffer tank, and a pressure sensor. The buffer tank is connected to the main vacuum pump and the pressure sensor via a pipeline. The gas-permeable membrane is made of hydrophobic and breathable material to prevent soil particles and liquid water from entering the sampling pipeline, while ensuring the free passage of gas molecules.

[0011] By adopting the above technical solution, the stainless steel tube of the gas sampling head provides rigid support to adapt to the mechanical stress of complex soil environments in the field. The hydrophobic and breathable membrane covering the air inlet is the core protective structure. Its hydrophobic properties can effectively prevent soil particles from entering the pipeline with the airflow, avoiding blockage or sample contamination. Its breathable properties allow gas molecules to pass freely, ensuring efficient collection of the target gas. In the vacuum pump system, the main vacuum pump provides stable pumping power, and the buffer tank balances the pressure fluctuations in the pipeline through volume adjustment, reducing the backflow phenomenon caused by sudden changes in the pumping rate and avoiding cross-contamination of soil gases at different depths. The pressure sensor monitors the pipeline pressure in real time, providing feedback signals to the microcontroller to dynamically adjust the vacuum pump power and ensure the consistency of sampling pressure of each monitoring unit.

[0012] Preferably, the valve group is an array of solenoid valves, and each solenoid valve independently controls the on / off state of one of the gas sampling heads; The gas detection unit includes a CO2 sensor, an O2 sensor, and a VOCs sensor, and the gas detection unit is connected to the microcontroller via a circuit. The solenoid valve array is programmed and controlled by the microcontroller to achieve sequential collection and automatic switching of gases from each soil layer, thus avoiding cross-contamination.

[0013] By adopting the above technical solution, each valve in the solenoid valve array independently corresponds to a gas sampling head, and the sequential on / off control is implemented by microcontroller programming, ensuring that only a single soil layer sampling channel is open at the same time, thus blocking the mixing and residue of gases at different depths in the pipeline from the hardware level; the CO2, O2, and VOCs sensors of the gas detection unit are directly connected to the microcontroller, and the collected gas composition data can be anchored to the corresponding soil layer in real time, ensuring the depth resolution of the data. This not only eliminates the human error caused by traditional manual switching of sampling heads, but also improves the repeatability and consistency of monitoring through standardized acquisition process. The automatic switching function supports multi-soil layer cyclic acquisition, which greatly shortens the sampling cycle and enables the device to efficiently adapt to the diverse needs of complex soil profiles.

[0014] Preferably, the microcontroller has a built-in analysis and prediction algorithm, and the wireless transmission module supports 4G / 5G communication protocols; The analysis and prediction algorithm is based on time series data and machine learning models and is used to predict the migration trend of soil pollutants and the variation pattern of gas concentration.

[0015] By adopting the above technical solutions, the analysis and prediction algorithm based on time series data and machine learning models can deeply explore the patterns of changes in liquid and gas phase parameters collected in real time over time. It can not only calculate the current soil condition indicators in real time, but also learn complex nonlinear relationships through model training to accurately predict the vertical migration trend of pollutants or the fluctuation pattern of gas concentration in the future. This provides a forward-looking basis for pollution diffusion early warning and remediation plan formulation. The 4G / 5G communication protocol supported by the wireless transmission module enables the monitoring data and prediction results processed by the microcontroller to be uploaded to the host computer or cloud platform in real time. Users can grasp the dynamics of soil environment in multiple regions without being stationed on-site, realizing centralized monitoring and data sharing across regions and multiple sites.

[0016] A method for using a soil monitoring sampling and processing device includes the following steps: S1. Device deployment: Vertically insert the probe body into the soil monitoring point to ensure that each monitoring unit reaches the target depth, connect the power supply and start the self-test program; S2. Start the leaching experiment: Set the leaching parameters through the control terminal and start the leaching solution injection system to inject the leaching solution into the soil surface at a constant flow rate. S3. Real-time monitoring and sampling: Soil parameters are continuously monitored through a sensor array, leachate is collected from each deep layer through a leachate collector, and gas sampling and real-time detection are carried out by sequentially activating each gas sampling head through a soil gas sampling module. S4. Data Processing and Prediction: Collect and analyze data through the control and data processing module, and predict changes in soil condition based on the built-in algorithm; S5. Equipment maintenance: Clean or replace the filter membrane and sensor regularly, and perform on-site calibration.

[0017] By adopting the above technical solutions, the precise insertion and self-checking procedure of the probe body in S1 ensures that each monitoring unit strictly corresponds to the target depth, avoiding data distortion caused by depth deviation, laying the foundation for subsequent stratified analysis. The self-checking function simultaneously verifies the initial state of the equipment, reducing the failure rate in field operations. The constant flow leaching injection in S2 accurately simulates the hydrodynamic characteristics of natural rainfall or irrigation, making the leaching process closer to the actual soil environment and improving the reliability of experimental results. The multi-parameter synchronous monitoring and stratified sampling in S3 acquires soil temperature, humidity, pH, and other liquid phase parameters in real time through a sensor array, in conjunction with leaching... The solution collector acquires leachate from different depths and simultaneously completes the sequential opening and detection of the gas sampling head, achieving temporal and spatial synchronization of liquid-gas data. This solves the problem of correlation analysis bias caused by misaligned sampling timing in traditional methods. The data processing and prediction function of S4 integrates multi-source data in real time through the control and data processing modules, and quickly outputs migration trend and concentration change prediction results based on the built-in algorithm. The regular maintenance and calibration of S5, through cleaning and replacing filter membranes and sensors and on-site calibration, effectively eliminates measurement errors caused by equipment aging or contamination during long-term operation, ensuring the continuity and accuracy of monitoring data.

[0018] Preferably, in step S1, the device deployment specifically includes the following steps: Select the insertion location based on soil monitoring needs; The probe body is inserted into the soil using a conical drill bit; The depth interval was adjusted to 20cm to 40cm. After insertion, the sensor readings of each monitoring unit are verified by the microcontroller; The depth intervals are dynamically adjusted based on soil profile characteristics and monitoring targets to match the physicochemical properties of different soil layers.

[0019] By adopting the above technical solution, the insertion location is selected according to the soil monitoring needs, ensuring that the probe body covers the key soil profile of the target study area, avoiding resource waste caused by blind placement; the conical drill bit is inserted into the soil, utilizing its soil-breaking advantage to reduce mechanical disturbance to the original soil structure, preserving the in-situ environment to the greatest extent, so that subsequent monitoring data more accurately reflects the soil characteristics under natural conditions; the depth interval is adjusted to a dynamic range of 20cm to 40cm, which can be used to verify the sensor readings of each monitoring unit after insertion through a microcontroller, enabling immediate troubleshooting of sensor failures or signal anomalies caused by transportation vibration, soil compression, or installation deviations, avoiding invalid data due to equipment failure during subsequent monitoring.

[0020] Preferably, in step S2, initiating the leaching experiment specifically includes the following steps: Set the leachate type to simulate rainfall or irrigation water, and inject the leachate with a peristaltic pump at a flow rate of 10 mL / min to 50 mL / min; The leaching experiment lasted for a preset period, and soil moisture changes were recorded in real time using a sensor array. The type and flow rate of the leaching solution are set based on actual environmental conditions to simulate the impact of different rainfall intensities or irrigation patterns on the soil.

[0021] By adopting the above technical solution, the leaching solution type is set to simulate rainfall or irrigation water, covering the two main sources of infiltration commonly found in the natural environment. The former can reproduce the scouring effect of rainfall of different intensities on the soil, while the latter can simulate agricultural irrigation or artificial water replenishment scenarios, making the experimental conditions more in line with actual application needs. The peristaltic pump injects water at a flow rate of 10 mL / min to 50 mL / min, which accurately corresponds to the typical infiltration rate range in nature, avoiding simulation deviations caused by fixed flow rates. The duration of the preset cycle, combined with the sensor array to record changes in soil moisture in real time, can observe the migration of pollutants caused by rapid water infiltration on a short time scale, as well as capture the lag effect of water retention and slow release of pollutants on a long time scale, fully presenting the temporal dynamic characteristics of the leaching process. Setting the leaching solution type and flow rate based on actual environmental conditions allows the experimental results to be directly transferred to scenarios such as pollution risk assessment and agricultural non-point source pollution control in similar soils or climate zones, solving the problem of insufficient universality of conclusions in traditional simulation experiments due to conditions being out of touch with reality.

[0022] Preferably, in step S3, the real-time monitoring and sampling specifically includes the following steps: The sensor array collects soil moisture, temperature, pH, and conductivity data at a preset frequency; The leachate collector activates a micro-liquid pump at specific time points to collect leachate samples; The soil gas sampling module uses a microcontroller to control the valve group to open each sampling point in sequence. The vacuum pump system pumps gas at a pumping rate of 0.5 L / min to 1 L / min. After each sampling point is pumped, the valve is immediately closed. A brief pre-evacuation is performed before gas sampling, lasting 30 to 60 seconds. The pre-extraction process removes residual gas from the pipeline, and pressure changes are monitored by a pressure sensor to ensure that the microenvironment at the sampling point is not disturbed.

[0023] By adopting the above technical solutions, the sensor array collects soil moisture, temperature, pH, and conductivity data at a preset frequency, ensuring dynamic tracking of soil state changes in a short period of time. The reasonable frequency setting balances data volume and storage costs, providing high-temporal-resolution liquid phase parameter support for subsequent migration models. The leachate collector activates a micro-liquid pump at specific time points, precisely corresponding to the key stages of the leaching process. This avoids sample dilution caused by continuous collection throughout the entire cycle, ensuring clear identification of the component characteristics of leachate at different depths and directly reflecting the rate and attenuation law of pollutants migrating vertically with water. In the soil gas sampling module, the microcontroller controls the valve group to sequentially open each sampling point. Combined with the design of immediately closing the valves after vacuum pumping, this prevents cross-residual gas from different depths in the pipeline, ensuring that only soil gas from the target soil layer is obtained in a single sampling. The 30-60 second pre-vacuuming process removes residual gas or air from the previous round in the sampling pipeline, preventing external gas from contaminating the current sample. Pressure sensors synchronously monitor pressure changes, ensuring that the vacuuming process does not disturb the in-situ soil microenvironment.

[0024] Preferably, in step S4, data processing and prediction specifically include the following steps: The microcontroller uses time series analysis algorithms and machine learning models to process real-time data and predict pollutant migration trends or gas concentration fluctuations. The prediction results are output in chart form and sent to the monitoring center via a wireless transmission module. The prediction results, combined with historical data and real-time monitoring values, provide trend analysis and risk warnings for changes in soil condition.

[0025] By adopting the above technical solution, the microcontroller calls time series analysis algorithms and machine learning models to process real-time data. It can capture the short-term fluctuation patterns of liquid and gas phase parameters, and learn long-term evolution trends through models trained on historical data. It breaks through the limitation of traditional offline statistics that can only reflect the current state, and realizes a two-dimensional analysis of the current state and future trends. The prediction results are output intuitively in the form of charts, transforming abstract values ​​into trend curves or risk level indicators, which makes it easy for users to quickly grasp the key nodes of soil state changes. The wireless transmission module synchronizes the results to the monitoring center, supporting centralized viewing across regions and multiple sites and collaborative response among multiple departments, avoiding the information lag caused by traditional on-site data collection.

[0026] In summary, this application includes at least one of the following beneficial technical effects: 1. The segmented sleeve structure of the probe body, combined with threaded connections, allows for flexible adjustment of the depth configuration of each monitoring unit according to monitoring needs, adapting to different soil profile research scenarios. The threaded engagement forms a sealed cavity, effectively blocking external soil disturbance and ensuring the vertical stability of each monitoring unit. This avoids data deviations caused by probe tilting or displacement. The detachable design facilitates quick assembly during field operations and subsequent maintenance, reducing equipment wear and tear costs. In the leaching monitoring module, the injection system injects simulated leachate into the soil surface through the top interface. Combined with the collectors inside each monitoring unit, leachate at different depths is collected synchronously. The external sensor array monitors humidity, temperature, and other parameters in real time. Liquid phase parameters such as pH are used to accurately track the vertical migration path and rate of pollutants or tracers in the soil. The multi-gas sampling head of the soil gas sampling module is distributed in each monitoring unit. Through the coordinated control of valve groups and vacuum pump system, soil gas at different depths can be collected sequentially or synchronously, avoiding cross-contamination of pipelines and gas backflow problems. The gas detection unit analyzes gas phase components such as CO2, O2, and VOCs in real time. The microcontroller of the control and data processing module uniformly schedules the operation of each module, realizing the automatic acquisition, storage, and wireless transmission of monitoring parameters. This not only improves the automation level of field operations, but also meets the needs of real-time monitoring and multi-location data sharing through cloud or host computer remote access functions.

[0027] 2. The precise insertion and self-checking procedure of the probe body in S1 ensures that each monitoring unit strictly corresponds to the target depth, avoiding data distortion caused by depth deviation and laying the foundation for subsequent stratified analysis. The self-checking function simultaneously verifies the initial state of the equipment, reducing the failure rate during field operations. S2's constant flow leaching injection accurately simulates the hydrodynamic characteristics of natural rainfall or irrigation, making the leaching process closer to the actual soil environment and improving the reliability of experimental results. S3's multi-parameter synchronous monitoring and stratified sampling acquire real-time liquid phase parameters such as soil temperature, humidity, and pH through a sensor array, in conjunction with leaching solution collection. The instrument acquires leachate at different depths and simultaneously completes the sequential opening and detection of gas sampling heads, achieving dual temporal and spatial synchronization of liquid-gas data. This solves the problem of correlation analysis bias caused by misaligned sampling timing in traditional methods. The data processing and prediction function of S4 integrates multi-source data in real time through the control and data processing modules, and quickly outputs migration trend and concentration change prediction results based on built-in algorithms. The regular maintenance and calibration of S5, through cleaning and replacing filter membranes and sensors and on-site calibration, effectively eliminates measurement errors caused by equipment aging or contamination during long-term operation, ensuring the continuity and accuracy of monitoring data. Attached Figure Description

[0028] Figure 1 This is a structural flowchart of the soil monitoring sampling and processing device in the embodiments of this application; Figure 2 This is a flowchart illustrating the steps of using the soil monitoring sampling and processing device in the embodiments of this application.

[0029] Reference numerals: 1. Probe body; 11. Monitoring unit; 12. Conical drill bit; 2. Leaching monitoring module; 21. Leaching solution injection system; 211. Storage tank; 212. Peristaltic pump; 22. Leaching solution collector; 221. Porous ceramic head; 222. Filter membrane; 223. Micro pump; 23. Sensor array; 24. Injection pipeline; 3. Soil gas sampling module; 31. Gas sampling head; 311. Stainless steel pipe; 312. Gas permeable membrane; 32. Vacuum pump system; 321. Main vacuum pump; 322. Buffer tank; 323. Pressure sensor; 33. Valve assembly; 331. CO2 sensor; 332. O2 sensor; 333. VOCs sensor; 34. Gas detection unit; 35. Sampling pipeline; 4. Control and data processing module; 41. Microcontroller; 42. Data storage unit; 43. Wireless transmission module; 44. Power supply. Detailed Implementation

[0030] The following is in conjunction with the appendix Figure 1-2 This application will be described in further detail.

[0031] This application discloses a soil monitoring sampling and processing device and method. (Refer to...) Figure 1The soil monitoring sampling and processing device includes a probe body 1, a leaching monitoring module 2 integrated into the probe body 1, a soil gas sampling module 3 integrated into the probe body 1, and a control and data processing module 4. The segmented sleeve structure forms a sealed cavity through threaded connection to ensure the vertical stability of each monitoring unit 11 in the soil and the independence of data acquisition.

[0032] The probe body 1 is composed of multiple detachable monitoring units 11 connected longitudinally by threads. Each monitoring unit 11 corresponds to a specific soil depth. A conical drill bit 12 is provided at the bottom of the probe body 1. The segmented casing structure of the probe body 1, combined with the threaded connection, can flexibly adjust the depth configuration of each monitoring unit 11 according to monitoring needs, adapting to different soil profile research scenarios. Furthermore, the threaded engagement forms a sealed cavity, effectively blocking external soil disturbance and ensuring the vertical stability of each monitoring unit 11, avoiding monitoring data deviations caused by probe tilting or displacement.

[0033] The leaching monitoring module 2 includes a leaching solution injection system 21, a leaching solution collector 22, and a sensor array 23. The leaching solution injection system 21 is connected to the injection interface at the top of the probe body 1 through an injection pipe 24. The leaching solution collector 22 is located inside each monitoring unit 11, and the sensor array 23 is located on the outer wall of each monitoring unit 11. In the leaching monitoring module 2, the injection system injects simulated leaching solution into the soil surface through the top interface. Combined with the collector inside each monitoring unit 11, leachate at different depths is collected synchronously. With the help of the sensor array 23 on the outer wall, liquid phase parameters such as humidity, temperature, and pH are monitored in real time, realizing a closed-loop process of injection-permeation-collection-monitoring. It can accurately track the vertical migration path and rate of pollutants or tracers in the soil.

[0034] The leachate injection system 21 includes a storage tank 211, a peristaltic pump 212, and an injection pipeline 24. The storage tank 211 is connected to the injection interface via the peristaltic pump 212. The leachate collector 22 includes a porous ceramic head 221, a filter membrane 222, and a micro-liquid pump 223. The porous ceramic head 221 works in conjunction with the filter membrane 222, and the micro-liquid pump 223 is connected to an external container via a hose. The leachate injection system 21 and the leachate collector 22 work together to simulate natural rainfall or irrigation conditions, achieving in-situ reproduction of the soil leaching process. The application of the peristaltic pump 212 can precisely control the leachate injection flow rate, making it highly matched with the water flow intensity of natural rainfall or irrigation, avoiding uneven soil infiltration caused by flow fluctuations, and restoring the authenticity of the initial experimental conditions. The modular design of the storage tank 211 supports the loading of different types of simulated liquids, flexibly adapting to diverse research scenarios. The simulated liquids can be acid rain, fertilizer solutions, or pollutant tracers.

[0035] In the leachate collector 22, the porous ceramic head 221 simulates the pore structure of the soil surface, allowing the injected leachate to permeate evenly into the soil, replicating the spatial distribution characteristics of natural infiltration. The filter membrane 222 effectively intercepts soil particles from entering the pipeline, preventing blockage and ensuring the purity of the collected leachate. The quantitative extraction function of the micro-pump 223 enables precise collection of leachate from different depths, avoiding cross-mixing of samples. When both work together, the experimental data more closely resemble the actual pollutant migration or nutrient transport processes in the field, providing more accurate in-situ data support for the study of soil solute transport patterns and pollution risk assessment, and solving the problem of biased conclusions caused by uneven injection and incomplete collection in traditional simulation experiments.

[0036] The soil gas sampling module 3 includes multiple gas sampling heads 31, a vacuum pump system 32, a valve group 33, and a gas detection unit 34. The gas sampling heads 31 are located in each monitoring unit 11 and are connected to the valve group 33 via sampling pipes 35. The valve group 33 is connected to the vacuum pump system 32 and the gas detection unit 34. With multiple gas sampling heads 31 distributed across each monitoring unit 11, the soil gas sampling module 3 can sequentially or synchronously collect soil gas from different depths through the coordinated control of the valve group 33 and the vacuum pump system 32, avoiding cross-contamination of pipelines and problems with gas backflow. The gas detection unit 34 analyzes gaseous components such as CO2, O2, and VOCs in real time, providing direct data support for studying the exchange of substances at the soil-atmosphere interface.

[0037] The gas sampling head 31 includes a stainless steel tube 311 and a gas-permeable membrane 312, with the membrane covering the inlet end of the tube. The vacuum pump system 32 includes a main vacuum pump 321, a buffer tank 322, and a pressure sensor 323, with the buffer tank 322 connected to the main vacuum pump 321 and the pressure sensor 323 via a pipe. The gas-permeable membrane 312 is made of a hydrophobic and breathable material to prevent soil particles and liquid water from entering the sampling pipeline 35, while ensuring the free passage of gas molecules. The stainless steel tube 311 of the gas sampling head 31 provides rigid support to withstand the mechanical stress of complex soil environments in the field. The hydrophobic and breathable membrane covering the inlet end is the core protective structure; its hydrophobic properties effectively block soil particles from entering the pipeline with the airflow, preventing blockage or sample contamination, while its breathability allows gas molecules to pass freely, ensuring efficient collection of target gases (such as CO2 and VOCs).

[0038] In the vacuum pump system 32, the main vacuum pump 321 provides stable pumping power, while the buffer tank 322 balances pressure fluctuations within the pipeline through volume regulation, reducing backflow caused by sudden changes in pumping rate and preventing cross-contamination of soil gas at different depths. The pressure sensor 323 monitors the pipeline pressure in real time, providing feedback signals to the microcontroller 41 to dynamically adjust the vacuum pump power and ensure consistent sampling pressure across all monitoring units 11. When these two systems work together, they solve the pipeline failure problem caused by soil particles or liquid water intrusion in traditional sampling heads, and improve the repeatability and representativeness of gas collection through stable pressure control. This allows the obtained soil gas data to more accurately reflect the material exchange process at the in-situ soil-atmosphere interface, providing reliable basic data support for subsequent gas composition analysis and migration pattern research.

[0039] The control and data processing module 4 includes a microcontroller 41, a data storage unit 42, a wireless transmission module 43, and a power supply 44. The microcontroller 41 is electrically connected to the components of the leaching monitoring module 2 and the soil gas sampling module 3. The microcontroller 41 of the control and data processing module 4 centrally schedules the operation of each module, realizing the automatic acquisition, storage, and wireless transmission of monitoring parameters. This improves the automation level of field operations and, through cloud or host computer remote access, meets the needs of real-time monitoring and multi-location data sharing. Valve group 33 is an array of solenoid valves, each of which independently controls the on / off state of a gas sampling head 31. Gas detection unit 34 includes a CO2 sensor 331, an O2 sensor 332, and a VOCs sensor 333, and is connected to microcontroller 41 via circuitry. The solenoid valve array is programmed and controlled by microcontroller 41 to achieve sequential sampling and automatic switching of gases from different soil layers, avoiding cross-contamination. Each valve in the solenoid valve array independently corresponds to a gas sampling head 31, and the microcontroller 41 programs sequential on / off control to ensure that only a single soil layer's sampling channel is open at any given time, thus preventing the mixing and residue of gases from different depths in the pipeline at a hardware level.

[0040] The CO2, O2, and VOCs sensors 333 of the gas detection unit 34 are directly connected to the microcontroller 41. The collected gas composition data can be anchored to the corresponding soil layer in real time, ensuring the depth resolution of the data. This eliminates the human error caused by traditional manual switching of sampling heads and improves the repeatability and consistency of monitoring through standardized acquisition procedures. That is, whether for long-term in-situ monitoring or short-term simulation experiments, it can provide accurate single-soil-layer gas data for the study of soil-atmosphere interface material exchange. At the same time, the automatic switching function supports multi-soil-layer cyclic acquisition, which significantly shortens the sampling cycle and enables the device to efficiently adapt to the diverse needs of complex soil profiles, providing reliable basic data support for subsequent gas migration pattern analysis or pollution risk assessment.

[0041] The microcontroller 41 incorporates an analysis and prediction algorithm, while the wireless transmission module 43 supports 4G / 5G communication protocols. The analysis and prediction algorithm, based on time-series data and machine learning models, is used to predict soil pollutant migration trends and gas concentration variations. Specifically, the analysis and prediction algorithm based on time-series data and machine learning models can deeply analyze the patterns of real-time liquid and gas phase parameters over time. It can not only calculate current soil condition indicators in real time but also learn complex nonlinear relationships through model training, accurately predicting the vertical migration trend of pollutants or gas concentration fluctuations over a future period, providing a forward-looking basis for pollution diffusion early warning and remediation plan development. The gas phase parameters include pollutant concentration, temperature, humidity, and gas composition, while the soil condition indicators include migration flux and correlation coefficients.

[0042] The wireless transmission module 43 supports 4G / 5G communication protocols, establishing a complete data channel from on-site monitoring to cloud storage and remote access. This allows monitoring data and prediction results processed by the microcontroller 41 to be uploaded to a host computer or cloud platform in real time. Users can monitor the dynamics of soil environments in multiple regions without being stationed on-site, achieving centralized monitoring and data sharing across regions and multiple sites. This reduces the cost of manual intervention and, through the embedded prediction function, upgrades monitoring from post-event recording to pre-event prediction, effectively solving the problems of lagging data application and insufficient guidance in traditional soil monitoring.

[0043] Reference Figure 2 A method for using a soil monitoring sampling and processing device includes the following steps: S1. Device deployment: Insert the probe body 1 vertically into the soil monitoring point, ensure that each monitoring unit 11 reaches the target depth, connect the power supply 44 and start the self-test program.

[0044] The precise insertion and self-testing procedure of the probe body 1 ensures that each monitoring unit 11 strictly corresponds to the target depth, avoiding data distortion caused by depth deviation, laying the foundation for subsequent layered analysis. The self-testing function simultaneously verifies the initial state of the equipment, reducing the failure rate in field operations.

[0045] Specifically, the deployment of the device includes the following steps: The insertion location is selected based on soil monitoring needs.

[0046] The probe body 1 is inserted into the soil using a conical drill bit 12.

[0047] The depth interval was adjusted to 20cm to 40cm.

[0048] After insertion, the sensor readings of each monitoring unit 11 are verified by the microcontroller 41.

[0049] The depth interval is dynamically adjusted based on soil profile characteristics and monitoring targets to match the physicochemical properties of different soil layers.

[0050] The insertion location is selected based on soil monitoring needs, ensuring that the probe body 1 covers key soil profiles (such as pollution plume distribution areas or fertility gradient zones) of the target study area, avoiding resource waste caused by blind sampling. The conical drill bit 12 is inserted into the soil, utilizing its conical structure to minimize mechanical disturbance to the original soil structure, preserving the in-situ environment to the greatest extent possible, and allowing subsequent monitoring data to more accurately reflect the soil characteristics under natural conditions. The depth interval is adjusted to a dynamic range of 20cm to 40cm, which can be flexibly adapted according to the physicochemical properties of the soil profile, including the thickness difference between clay and sand layers and the organic matter content gradient.

[0051] For example, increasing the interval in areas with significant soil differentiation avoids redundant monitoring, while decreasing the interval in homogeneous soil layers captures more refined vertical changes, achieving an optimal balance between monitoring cost and data accuracy. After insertion, the sensor readings of each monitoring unit 11 are verified by the microcontroller 41, enabling immediate troubleshooting of sensor malfunctions or signal anomalies caused by transportation vibration, soil compression, or installation deviations, thus preventing invalid data from being generated during subsequent monitoring. This ensures the stable operation of the monitoring equipment and enhances the data's ability to characterize the vertical features of the soil, laying a reliable field foundation for subsequent leaching experiments and multi-parameter analysis.

[0052] S2. Start the leaching experiment: Set the leaching parameters through the control terminal and start the leaching solution injection system 21 to inject the leaching solution into the soil surface at a constant flow rate.

[0053] Among them, constant flow leaching injection accurately simulates the hydrodynamic characteristics of natural rainfall or irrigation, making the leaching process closer to the actual soil environment and improving the reliability of experimental results.

[0054] Specifically, the steps to initiate a leaching experiment include: Set the leachate type to simulate rainfall or irrigation water, and inject the leachate with a peristaltic pump 212 at a flow rate of 10 mL / min to 50 mL / min.

[0055] The leaching experiment lasted for a preset period, and the soil moisture changes were recorded in real time by the sensor array 23.

[0056] The leaching solution type and flow rate are set based on actual environmental conditions to simulate the impact of different rainfall intensities or irrigation patterns on the soil.

[0057] The leachate type was set to simulate rainfall or irrigation water, covering the two main sources of infiltration commonly found in the natural environment. The former can reproduce the scouring effect of rainfall of different intensities on the soil, while the latter can simulate agricultural irrigation or artificial water replenishment scenarios, making the experimental conditions more in line with actual application needs. The peristaltic pump 212 injects water at a flow rate of 10 mL / min to 50 mL / min, which accurately corresponds to the typical infiltration rate range in nature, avoiding simulation deviations caused by a fixed flow rate.

[0058] The preset cycle duration, combined with the real-time recording of soil moisture changes by the sensor array 23, allows for the observation of pollutant migration caused by rapid water infiltration on short timescales, as well as the capture of the lag effects of water retention and slow pollutant release on long timescales, thus fully presenting the temporal dynamic characteristics of the leaching process. By setting the leaching solution type and flow rate based on actual environmental conditions, the experimental results can be directly applied to pollution risk assessment and agricultural non-point source pollution control in similar soils or climate zones, solving the problem of insufficient universality of conclusions in traditional simulation experiments due to conditions detached from reality. This upgrades the leaching experiment from idealized laboratory simulation to a reproduction of real-world field conditions, providing more reliable experimental data support for the study of soil solute transport patterns.

[0059] S3. Real-time monitoring and sampling: Soil parameters are continuously monitored through sensor array 23, leachate is collected from each deep layer through leachate collector 22, and gas sampling and real-time detection are carried out by sequentially activating each gas sampling head 31 through soil gas sampling module 3.

[0060] Among them, the multi-parameter synchronous monitoring and stratified sampling of S3 acquires liquid phase parameters such as soil temperature, humidity and pH in real time through sensor array 23, and collects leachate at different depths with leachate collector 22, and simultaneously completes the sequential opening and detection of gas sampling head 31, realizing the time and space dual synchronization of liquid-gas data, and solving the problem of correlation analysis deviation caused by sampling time sequence misalignment in traditional methods.

[0061] The specific steps involved in real-time monitoring and sampling are as follows: The sensor array 23 collects soil moisture, temperature, pH and conductivity data at a preset frequency.

[0062] The leachate collector 22 starts the micro liquid pump 223 at a specific time point to collect the leachate sample.

[0063] The soil gas sampling module 3 controls the valve group 33 to open each sampling point sequentially through the microcontroller 41. The vacuum pump system 32 pumps gas at a pumping rate of 0.5 L / min to 1 L / min. After each sampling point is pumped, the valve is immediately closed.

[0064] A brief pre-evacuation is performed before gas sampling, lasting 30 to 60 seconds.

[0065] The pre-extraction process removes residual gas from the pipeline, while pressure changes are monitored by pressure sensor 323 to ensure that the microenvironment at the sampling point is not disturbed.

[0066] Sensor array 23 collects soil moisture, temperature, pH, and conductivity data at a preset frequency, ensuring dynamic tracking of soil condition changes over a short period while balancing data volume and storage costs through reasonable frequency settings, providing high temporal resolution liquid phase parameter support for subsequent migration models. Leachate collector 22 activates micro-liquid pump 223 at specific time points, precisely corresponding to key stages of the leaching process, avoiding sample dilution caused by continuous collection throughout the entire cycle, ensuring clear identification of the component characteristics of leachate at different depths, and directly reflecting the rate and attenuation law of pollutants migrating vertically with water.

[0067] In the soil gas sampling module 3, the microcontroller 41 controls the valve group 33 to sequentially open each sampling point. Combined with the design of the vacuum pump system 32 immediately closing the valves after evacuation, this hardware-level design prevents cross-residual gas from different depths within the pipeline, ensuring that each sampling only acquires soil gas from the target soil layer. The 30-60 second pre-evacuation process removes residual gas or air from the previous sampling cycle within the sampling pipeline 35, preventing contamination of the current sample by external gases. The pressure sensor 323 synchronously monitors pressure changes, ensuring that the evacuation process does not disturb the in-situ soil microenvironment. This achieves precise temporal and spatial matching of liquid and gas phase parameters, solving the data distortion problems caused by cross-contamination or improper pretreatment in traditional sampling. Furthermore, standardized temporal control improves the repeatability of monitoring, providing a high-fidelity in-situ data foundation for research on soil-atmosphere-liquid phase interaction mechanisms.

[0068] S4. Data Processing and Prediction: Data is collected and analyzed through the control and data processing module 4, and soil condition changes are predicted based on the built-in algorithm.

[0069] Among them, the data processing and prediction function integrates multi-source data in real time through the control and data processing module 4, and quickly outputs migration trend and concentration change prediction results based on the built-in algorithm, providing an immediate basis for pollution early warning or remediation plan adjustment.

[0070] In S4, data processing and prediction specifically include the following steps: The microcontroller 41 uses time series analysis algorithms and machine learning models to process real-time data and predict pollutant migration trends or gas concentration fluctuations.

[0071] The prediction results are output in the form of charts and sent to the monitoring center via wireless transmission module 43.

[0072] The prediction results, combined with historical data and real-time monitoring values, provide trend analysis and risk warnings for changes in soil condition.

[0073] The microcontroller 41 calls time series analysis algorithms and machine learning models to process real-time data. It can capture the short-term fluctuation patterns of liquid and gas phase parameters, and learn the long-term evolution trend through models trained on historical data. It breaks through the limitation of traditional offline statistics that can only reflect the current state and realizes the dual-dimensional analysis of the current state and future trend. Among them, the gas phase parameters are pollutant concentration, temperature and humidity, and the short-term fluctuation pattern is the infiltration peak caused by rainfall.

[0074] The prediction results are displayed intuitively in chart form, transforming abstract numerical values ​​into trend curves or risk level indicators, allowing users to quickly grasp key nodes in soil condition changes, such as a sudden increase in pollutant migration rate or gas concentration approaching thresholds. The wireless transmission module 43 synchronizes the results to the monitoring center, supporting centralized viewing across regions and multiple sites, as well as collaborative responses from multiple departments, avoiding information delays caused by traditional on-site data collection. Comprehensive analysis combining historical monitoring values ​​and real-time data not only predicts pollution diffusion paths or abnormal gas fluctuations but also provides quantitative evidence for adjusting remediation plans or issuing ecological risk warnings, achieving closed-loop management of monitoring, analysis, early warning, and intervention. This addresses the core issues of low data application value and insufficient guidance in traditional soil monitoring.

[0075] S5. Equipment maintenance: Clean or replace filter membrane 222 and sensors regularly, and perform on-site calibration.

[0076] Regular maintenance and calibration, through cleaning and replacing filter membrane 222, sensors, and on-site calibration, effectively eliminate measurement errors caused by equipment aging or contamination during long-term operation, ensuring the continuity and accuracy of monitoring data.

[0077] The implementation principle of this application embodiment is as follows: The segmented sleeve structure of the probe body 1, combined with the threaded connection, allows for flexible adjustment of the depth configuration of each monitoring unit 11 according to monitoring needs, adapting to different soil profile research scenarios. Furthermore, the threaded engagement forms a sealed cavity, effectively blocking external soil disturbance and ensuring the vertical stability of each monitoring unit 11, avoiding data deviations caused by probe tilting or displacement. The detachable design facilitates rapid assembly and subsequent maintenance during field operations, reducing equipment wear and tear costs. In the leaching monitoring module 2, the injection system injects simulated leaching solution into the soil surface through the top interface. Combined with the collectors inside each monitoring unit 11, leachate at different depths is collected synchronously, and the external wall sensor array 23 monitors humidity in real time. Liquid phase parameters such as temperature and pH are used to accurately track the vertical migration path and rate of pollutants or tracers in the soil. The multi-gas sampling head 31 of the soil gas sampling module 3 is distributed in each monitoring unit 11. Through the coordinated control of the valve group 33 and the vacuum pump system 32, soil gas at different depths can be collected sequentially or synchronously, avoiding cross-contamination of pipelines and gas backflow problems. The gas detection unit 34 analyzes gas phase components such as CO2, O2, and VOCs in real time. The microcontroller 41 of the control and data processing module 4 uniformly schedules the operation of each module to realize the automatic acquisition, storage and wireless transmission of monitoring parameters. This not only improves the automation level of field operations, but also meets the needs of real-time monitoring and multi-location data sharing through cloud or host computer remote access functions.

[0078] The precise insertion and self-checking procedure of the probe body 1 in S1 ensures that each monitoring unit 11 strictly corresponds to the target depth, avoiding data distortion caused by depth deviation and laying the foundation for subsequent stratified analysis. The self-checking function simultaneously verifies the initial state of the equipment, reducing the failure rate during field operations. The constant flow leaching injection in S2 accurately simulates the hydrodynamic characteristics of natural rainfall or irrigation, making the leaching process closer to the actual soil environment and improving the reliability of experimental results. The multi-parameter synchronous monitoring and stratified sampling in S3 acquires real-time liquid phase parameters such as soil temperature, humidity, and pH through the sensor array 23, in conjunction with the leaching solution collector 22. By acquiring leachate at different depths and simultaneously opening and detecting the gas sampling head 31, the system achieves temporal and spatial synchronization of liquid-gas data, solving the correlation analysis bias problem caused by misaligned sampling timing in traditional methods. The data processing and prediction function of S4 integrates multi-source data in real time through the control and data processing module 4, and quickly outputs migration trend and concentration change prediction results based on the built-in algorithm. The regular maintenance and calibration of S5, through cleaning and replacing the filter membrane 222, sensors, and on-site calibration, effectively eliminates measurement errors caused by equipment aging or contamination during long-term operation, ensuring the continuity and accuracy of monitoring data.

[0079] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A soil monitoring sampling and processing device, characterized in that, include: The probe body (1) is a segmented sleeve structure. The probe body (1) is composed of multiple detachable monitoring units (11) connected longitudinally by threads. Each monitoring unit (11) corresponds to a specific soil depth. The bottom of the probe body (1) is provided with a conical drill bit (12). The leaching monitoring module (2) is integrated into the probe body (1) and includes a leaching solution injection system (21), a leaching solution collector (22) and a sensor array (23). The leaching solution injection system (21) is connected to the injection port at the top of the probe body (1) through an injection pipe (24). The leaching solution collector (22) is disposed inside each of the monitoring units (11), and the sensor array (23) is disposed on the outer wall of each of the monitoring units (11). The soil gas sampling module (3) is integrated into the probe body (1) and includes multiple gas sampling heads (31), a vacuum pump system (32), a valve group (33) and a gas detection unit (34). The gas sampling heads (31) are set in each of the monitoring units (11). The gas sampling heads (31) are connected to the valve group (33) through sampling pipes (35). The valve group (33) is connected to the vacuum pump system (32) and the gas detection unit (34). The control and data processing module (4) includes a microcontroller (41), a data storage unit (42), a wireless transmission module (43), and a power supply (44). The microcontroller (41) is electrically connected to the components of the leaching monitoring module (2) and the soil gas sampling module (3). The segmented sleeve structure forms a sealed cavity through threaded connection, ensuring the vertical stability of each monitoring unit (11) in the soil and the independence of data acquisition.

2. The soil monitoring sampling and processing device according to claim 1, characterized in that, The solution injection system (21) includes a storage tank (211), a peristaltic pump (212) and an injection pipeline (24). The storage tank (211) is connected to the injection interface through the peristaltic pump (212). The leachate collector (22) includes a porous ceramic head (221), a filter membrane (222), and a micro liquid pump (223). The porous ceramic head (221) is fitted with the filter membrane (222), and the micro liquid pump (223) is connected to an external container via a hose. The leaching solution injection system (21) and the leaching solution collector (22) work together to simulate natural rainfall or irrigation conditions and realize the in-situ reproduction of the soil leaching process.

3. The soil monitoring sampling and processing device according to claim 1, characterized in that, The gas sampling head (31) includes a stainless steel tube (311) and a gas permeable membrane (312), the gas permeable membrane (312) covering the air inlet end of the stainless steel tube (311); The vacuum pump system (32) includes a main vacuum pump (321), a buffer tank (322) and a pressure sensor (323), wherein the buffer tank (322) is connected to the main vacuum pump (321) and the pressure sensor (323) through a pipe; The gas permeable membrane (312) is made of hydrophobic and breathable material to prevent soil particles and liquid water from entering the sampling pipe (35) while ensuring the free passage of gas molecules.

4. The soil monitoring sampling and processing device according to claim 1, characterized in that, The valve group (33) is an array of solenoid valves, and each solenoid valve independently controls the on / off state of one of the gas sampling heads (31); The gas detection unit (34) includes a CO2 sensor (331), an O2 sensor (332), and a VOCs sensor (333). The gas detection unit (34) is connected to the microcontroller (41) via a circuit. The solenoid valve array is programmed and controlled by the microcontroller (41) to realize the sequential collection and automatic switching of gases in each soil layer, thus avoiding cross-contamination.

5. The soil monitoring sampling and processing device according to claim 1, characterized in that, The microcontroller (41) has a built-in analysis and prediction algorithm, and the wireless transmission module (43) supports 4G / 5G communication protocols; The analysis and prediction algorithm is based on time series data and machine learning models and is used to predict the migration trend of soil pollutants and the variation pattern of gas concentration.

6. A method for using the soil monitoring sampling and processing device according to any one of claims 1-5, characterized in that, Includes the following steps: S1. Device deployment: Insert the probe body (1) vertically into the soil monitoring point, ensure that each monitoring unit (11) reaches the target depth, connect the power supply (44) and start the self-test program; S2. Start the leaching experiment: Set the leaching parameters through the control terminal and start the leaching solution injection system (21) to inject the leaching solution into the soil surface at a constant flow rate; S3. Real-time monitoring and sampling: Soil parameters are continuously monitored through sensor array (23), leachate is collected from each deep layer through leachate collector (22), and gas sampling and real-time detection are carried out by sequentially opening each gas sampling head (31) through soil gas sampling module (3). S4. Data processing and prediction: Data is collected and analyzed through the control and data processing module (4), and soil state changes are predicted based on the built-in algorithm; S5. Equipment maintenance: Clean or replace the filter membrane (222) and sensors regularly, and perform on-site calibration.

7. The soil monitoring sampling and processing device and method according to claim 6, characterized in that, In step S1, the device deployment specifically includes the following steps: Select the insertion location based on soil monitoring needs; The probe body (1) is inserted into the soil using a conical drill bit (12); The depth interval was adjusted to 20cm to 40cm. After insertion, the sensor readings of each monitoring unit (11) are verified by the microcontroller (41); The depth intervals are dynamically adjusted based on soil profile characteristics and monitoring targets to match the physicochemical properties of different soil layers.

8. The soil monitoring sampling and processing device and method according to claim 6, characterized in that, In step S2, initiating the leaching experiment specifically includes the following steps: The leachate type is set to simulate rainfall or irrigation water, and the peristaltic pump (212) injects the leachate at a flow rate of 10 mL / min to 50 mL / min; The leaching experiment lasted for a preset period, and the soil moisture changes were recorded in real time by a sensor array (23); The type and flow rate of the leaching solution are set based on actual environmental conditions to simulate the impact of different rainfall intensities or irrigation patterns on the soil.

9. The soil monitoring sampling and processing device and method according to claim 6, characterized in that, In step S3, real-time monitoring and sampling specifically include the following steps: The sensor array (23) collects soil moisture, temperature, pH and conductivity data at a preset frequency; The leachate collector (22) starts a micro-liquid pump (223) at a specific time point to collect leachate samples; The soil gas sampling module (3) controls the valve group (33) to open each sampling point in sequence through the microcontroller (41), and the vacuum pump system (32) pumps gas at a pumping rate of 0.5 L / min to 1 L / min. After each sampling point is pumped, the valve is immediately closed. A brief pre-evacuation is performed before gas sampling, lasting 30 to 60 seconds. The pre-extraction process removes residual gas from the pipeline, and at the same time, pressure changes are monitored by a pressure sensor (323) to ensure that the microenvironment at the sampling point is not disturbed.

10. The soil monitoring sampling and processing device and method according to claim 6, characterized in that, In step S4, data processing and prediction specifically include the following steps: The microcontroller (41) uses time series analysis algorithms and machine learning models to process real-time data and predict pollutant migration trends or gas concentration fluctuations; The prediction results are output in the form of charts and sent to the monitoring center via the wireless transmission module (43); The prediction results, combined with historical data and real-time monitoring values, provide trend analysis and risk warnings for changes in soil condition.

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