Single-point soil moisture monitoring method and system

Abstract

The invention relates to a single-point soil moisture monitoring method and system, and belongs to the technical field of agricultural information. According to the invention, after the volumetric water content of each layer of soil in different depth ranges is obtained by using a multi-depth sensor array, the influence of stratum thickness difference, soil bulk density of different layers, crop root depth and soil type on soil moisture is considered; and correcting the volumetric water content of each layer by using at least two of the thickness weight, the volume weight compensation coefficient, the root system regulation factor and the soil type compensation coefficient, calculating the weighted average volumetric water content of the soil based on the corrected volumetric water content data of each layer, and determining the soil moisture according to the weighted average volumetric water content of the soil. The factors influencing the soil moisture are considered in the obtained soil moisture, the soil moisture can be accurately reflected, and the precision of single-point moisture monitoring is improved.

Description

Technical Field

[0001] This invention relates to a single-point soil moisture monitoring method and system, belonging to the field of agricultural information technology. Background Art

[0002] Currently, there are two main types of soil moisture monitoring techniques: regional measurement techniques and single-point measurement techniques. Regional measurement techniques mainly monitor soil moisture in a specific area using methods such as the Cosmic Ray Neutron Method (COSMOS) and remote sensing inversion. This technique has a large spatial coverage area (radius of 300-600 meters), but low vertical resolution (only reflecting the comprehensive value of the top 0-30 cm layer), and is significantly affected by vegetation cover and soil type (error can reach ±15%), resulting in low accuracy and poor reliability of the obtained soil moisture data. Single-point measurement technology mainly uses sensors such as time-domain reflectometry (TDR) and frequency-domain reflectometry (FDR) to measure the volumetric water content (VWC) of soil at different depths, which can improve vertical resolution. However, existing processing methods for single-point data mainly include arithmetic mean method (such as simple mean calculation), fixed weight method (linear weighting), machine learning method (such as random forest regression) and physical model method (such as HYDRUS model coupling). Among them, the arithmetic mean method ignores the difference in soil layer thickness, the fixed weight method cannot adapt to different soil / crop types, the machine learning method requires a large amount of training data, and the physical model method is computationally complex and parameter sensitive.

[0003] Therefore, current single-point soil moisture measurement technologies have various problems in processing single-point soil moisture data, and all of them focus on the measured single-point soil moisture data itself, without considering the influence of the environment such as vegetation. This results in low accuracy of the soil moisture data and an inability to reflect the true soil moisture content in the monitored area. Summary of the Invention

[0004] The purpose of this invention is to provide a single-point soil moisture monitoring method and system to solve the problem of inaccurate single-point soil moisture monitoring measurement results.

[0005] To address the aforementioned technical problems, this invention provides a single-point soil moisture monitoring method, which includes the following steps:

[0006] 1) Use a multi-depth sensor array to obtain the volumetric water content of each layer at different depths in the soil;

[0007] 2) Determine the thickness weight of each layer based on the depth range of each layer, determine the bulk density compensation coefficient of each layer based on the soil bulk density of each layer, determine the root regulation factor of each layer based on the crop growth period index decay model, the distribution depth of crop roots and the depth of each layer, and determine the soil type compensation coefficient of each layer based on the soil type to which the depth of each layer belongs.

[0008] 3) Select at least two from the determined thickness weight, bulk density compensation coefficient, root regulation factor and soil type compensation coefficient to correct the volumetric water content of each layer. Calculate the weighted average volumetric water content of the soil based on the corrected volumetric water content data of each layer, and determine the soil moisture based on the weighted average volumetric water content of the soil.

[0009] Furthermore, the method also includes a quality assessment of the obtained average volumetric water content of the soil. If the quality does not meet the requirements, the obtained average volumetric water content of the soil is compensated using historical average volumetric water content. The quality assessment uses at least two of the following evaluation indicators: coefficient of variation, interlayer consistency, and temporal continuity. The coefficient of variation is used to characterize the overall difference in water content of each measured layer and is calculated based on the standard deviation and average value of the measured water content of each layer. The interlayer consistency is used to characterize the consistency of water content of adjacent layers. The temporal continuity is used to characterize the change of water content of each measured layer over time.

[0010] Furthermore, the quality assessment is a weighted sum of the coefficient of variation, interlayer consistency, and temporal continuity indicators.

[0011] Furthermore, the volumetric water content of each layer at different depths in step 1) is obtained by anomaly screening using the soil temperature and electrical conductivity of the corresponding layer.

[0012] Furthermore, the formula used to calculate the average volumetric water content of the soil is as follows:

[0013]

[0014] in VWC is the weighted average volumetric water content of the soil. i Let Δh be the measured volumetric water content of the i-th soil layer, n be the number of layers, and Δh be the volumetric water content of the i-th soil layer. i ρ represents the thickness weight of the i-th soil layer, corresponding to the actual thickness of each layer. i Let σ be the bulk density compensation coefficient of the i-th soil layer. i c is the root regulator of the i-th soil layer. i Let be the soil type compensation coefficient for the i-th soil layer.

[0015] Furthermore, the calculation formulas used for the bulk density compensation coefficient and the root system adjustment factor are as follows:

[0016]

[0017] σ i =1+α·exp(-β·|d i -dpeak |)

[0018] Where ρ i Let ρ be the bulk density compensation coefficient of the i-th soil layer. ref For standard reference density, ρ sample Soil bulk density measured by the ring sampler method, σ i is the root regulation factor of the i-th soil layer.

[0019] The present invention also provides a single-point soil moisture monitoring system, including a multi-depth sensor array and a data processing module for processing the soil moisture content of each layer measured by the multi-depth sensor array. The data processing module is used to correct the volumetric water content of each layer according to at least two of the following: thickness weight, bulk density compensation coefficient, root regulation factor and soil type compensation coefficient. Based on the corrected volumetric water content data of each layer, the weighted average volumetric water content of the soil is calculated, and the soil moisture is determined according to the weighted average volumetric water content of the soil.

[0020] The thickness weight of each layer is determined based on the depth range of each layer, the bulk density compensation coefficient of each layer is determined based on the soil bulk density of each layer, the root regulation factor of each layer is determined based on the crop growth period index decay model, the distribution depth of crop roots and the depth of each layer, and the soil type compensation coefficient of each layer is determined based on the soil type to which the depth of each layer belongs.

[0021] Furthermore, the system also includes a quality assessment module, which is used to assess the quality of the obtained average volumetric moisture content of the soil. If the quality does not meet the requirements, the average volumetric moisture content of the obtained soil is compensated using historical average volumetric moisture content. The quality assessment uses at least two of the following evaluation indicators: coefficient of variation, interlayer consistency, and temporal continuity. The coefficient of variation is used to characterize the overall difference in moisture content among the measured layers and is calculated based on the standard deviation and average value of the measured moisture content of each layer. The interlayer consistency index is used to characterize the consistency of moisture content among adjacent layers. The temporal continuity index is used to characterize the change in moisture content of each layer over time.

[0022] Furthermore, the data processing module uses the following formula to calculate the average volumetric water content of the soil:

[0023]

[0024] in VWC is the weighted average volumetric water content of the soil. i Let Δh be the measured volumetric water content of the i-th soil layer, n be the number of layers, and Δh be the volumetric water content of the i-th soil layer. i ρ represents the thickness weight of the i-th soil layer, corresponding to the actual thickness of each layer.i Let σ be the bulk density compensation coefficient of the i-th soil layer. i c is the root regulator of the i-th soil layer. i Let be the soil type compensation coefficient for the i-th soil layer.

[0025] Furthermore, this single-point soil moisture monitoring system is also used to communicate with a cloud platform to send the obtained weighted average volumetric water content and quality assessment results of the soil to the cloud platform, so that the cloud platform can fuse the data with satellite remote sensing data to generate a moisture distribution map.

[0026] The beneficial effects of this invention are as follows: As an improved invention, after acquiring the volumetric water content of each layer at different depths of the soil using a multi-depth sensor array, this invention considers the influence of differences in stratum thickness, bulk density of different soil layers, crop root depth, and soil type on soil moisture. It corrects the volumetric water content of each layer using at least two of the following: thickness weight, bulk density compensation coefficient, root regulation factor, and soil type compensation coefficient. Based on the corrected volumetric water content data of each layer, the weighted average volumetric water content of the soil is calculated. Soil moisture is determined based on this weighted average volumetric water content. The soil moisture obtained in this way takes into account the factors affecting soil moisture, can accurately reflect soil moisture, and improves the accuracy of single-point moisture monitoring. Attached Figure Description

[0027] Figure 1 This is a flowchart of the single-point soil moisture monitoring method of the present invention;

[0028] Figure 2 This is a schematic diagram of the single-point soil moisture monitoring system of the present invention. Detailed Implementation

[0029] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0030] This invention obtains the factors that affect soil moisture content, uses the obtained factors to correct the volumetric water content of each layer of soil at different depths obtained by a multi-depth sensor array, and uses the corrected volumetric water content of each layer to determine the soil moisture at a single point.

[0031] Implementation of Single-Point Soil Moisture Monitoring Method

[0032] This invention first utilizes a multi-depth sensor array to acquire the volumetric water content of soil layers at different depths. Then, it corrects the volumetric water content of each layer using layer thickness weights, bulk density compensation coefficients, root regulation factors, and soil type compensation coefficients. Based on the corrected volumetric water content data, it calculates the weighted average volumetric water content of the soil and determines the soil moisture content. Finally, it assesses the quality of the obtained average volumetric water content. If the quality does not meet the requirements, it compensates for the obtained average volumetric water content using historical soil average volumetric water content. The implementation process of this method is as follows: Figure 1 As shown below, a detailed explanation will follow.

[0033] 1. Use a multi-depth sensor array to obtain the volumetric water content of soil layers at different depths.

[0034] This invention employs a multi-layer FDR / TDR sensor array to measure the volumetric water content of each layer. For example, a multi-depth sensor array using a four-layer FDR / TDR sensor array is inserted into the soil to be measured, allowing for the collection of volumetric water content data for soil layers at depths of 0-10cm, 10-30cm, 30-60cm, and 60-100cm. Simultaneously, temperature and conductivity sensors are installed in each layer to synchronously acquire auxiliary parameters such as soil temperature and conductivity. The soil temperature and conductivity of each layer can verify the validity of the measured volumetric water content, determining if any anomalies exist. If an anomaly is found, the corresponding layer's volumetric water content is excluded from subsequent calculations, thus preventing inaccurate calculations of the weighted average volumetric water content of the soil due to abnormal data from a particular layer.

[0035] 2. Obtain the factors affecting soil moisture content, and use the obtained factors to correct the volumetric water content of each layer of soil at different depths obtained by the multi-depth sensor array, and then calculate the weighted average volumetric water content of the soil.

[0036] The volumetric water content of each layer is corrected based on the thickness weight, bulk density compensation coefficient, root regulation factor, and soil type compensation coefficient. The weighted average volumetric water content of the soil is then calculated based on the corrected volumetric water content data of each layer. Soil moisture is determined based on this weighted average volumetric water content. The calculation formula used is as follows:

[0037]

[0038] in This is the weighted average volumetric water content of the soil, expressed in m³. 3 / m 3 VWC i Δh represents the measured volumetric water content of the i-th soil layer; n is the number of layers; Δh iρ represents the thickness weight of the i-th soil layer, corresponding to the actual thickness of each layer. i Let σ be the bulk density compensation coefficient of the i-th soil layer. i c is the root regulator of the i-th soil layer. i Let be the soil type compensation coefficient for the i-th soil layer.

[0039] Considering data anomalies and inherent limitations of the depth sensor array itself, the data measured by the depth sensor array may be incomplete. If a significant amount of data is missing, it is considered invalid, and the weighted average volumetric water content of the soil will not be calculated.

[0040]

[0041] In other words, the weighted average volumetric water content of the soil is calculated only if the number of missing data is less than half the number of layers in the depth sensor array. In this invention, n=4 and m needs to be less than 2.

[0042] The calculation of each influencing factor is explained in detail below.

[0043] The thickness weight of each layer is determined based on the depth range of each layer, with the thickness weight Δh of the i-th soil layer being... i Corresponding to the actual thickness of each soil layer, for the four-layer FDR / TDR sensor array in this embodiment, there are 4 Δh values. i These 4 Δh i The calculations are as follows:

[0044] Δh1=10-0=10, Δh2=30-10=20, Δh3=60-30=30, Δh4=100-60=40.

[0045] The bulk density compensation coefficient for each layer is determined based on the bulk density of the soil in each layer. The bulk density compensation coefficient ρ of the i-th soil layer is... i That is, the standard reference density ρ ref (Usually taken as 1.35g / cm) 3 ) and the measured soil bulk density ρ of this layer i sample The ratio of the soil density to the measured density of each layer was obtained using the ring sampler method. The density compensation coefficient ρ... i The calculation formula is as follows:

[0046]

[0047] The root regulation factors for each layer are determined based on the crop growth period exponential decay model, the distribution depth of crop roots, and the depth of each layer. The calculation formula used for the root regulation factor of the i-th soil layer is as follows:

[0048] σ i=1+α·exp(-β·|d i -d peak |)

[0049] Where α∈[0.1, 0.3] (representing the maximum adjustment range of the crop), β∈[0.05, 0.15] (attenuation coefficient), d peak d represents the root distribution depth. i Let be the monitoring depth of the i-th soil layer.

[0050] The soil type compensation coefficient for each layer is determined based on the soil type corresponding to the depth of each layer. The soil type compensation coefficient c for the i-th soil layer is... i The soil type is determined by the soil type of the i-th soil layer. When the soil type of the i-th soil layer is sandy soil, c i The value is 1.05; when the soil type of the i-th soil layer is loam, c i The value is 1.00; when the soil type of the i-th soil layer is clay, c i The value is 0.95.

[0051] The above method uses four influencing factors (thickness weight, bulk density compensation coefficient, root regulation factor, and soil type compensation coefficient) to correct the soil moisture content of each layer, thus obtaining a weighted average volumetric water content that accurately reflects soil moisture. As another embodiment, the present invention can also select some of the thickness weight, bulk density compensation coefficient, root regulation factor, and soil type compensation coefficient to participate in the correction of soil moisture content, generally selecting at least two; for example, thickness weight and root regulation factor can be selected for correction.

[0052] 3. Conduct a quality assessment and compensate for the weighted average volumetric moisture content of the soil obtained in step 2 based on the quality assessment results.

[0053] This invention includes a quality assessment of the average volumetric water content of the obtained soil. If the quality does not meet the requirements, the average volumetric water content of the obtained soil is compensated by using the historical average volumetric water content of the soil. The evaluation indicators used in the quality assessment are the coefficient of variation index, the interlayer consistency index, and the temporal continuity index.

[0054] Specifically, the coefficient of variation index is used to characterize the overall difference in water content among the measured layers, and is calculated based on the standard deviation and average value of the water content of each layer; the interlayer consistency index is used to characterize the consistency of water content between adjacent layers; and the temporal continuity index is used to characterize the change of water content among the measured layers over time. The calculation of each index is explained in detail below.

[0055] Coefficient of variation index S cvAlso known as the coefficient of variation score, it is obtained by calculating the standard deviation and arithmetic mean of the corrected soil moisture content in each layer, and comparing the ratio of these two to an empirical threshold. In this embodiment, the corrected soil moisture content of the four layers is first statistically analyzed to determine the standard deviation θ and arithmetic mean μ, and then calculated according to the following formula:

[0056]

[0057] Among them, CV th This is an empirical threshold that can be set according to the actual situation. It is generally less than 0.5, and in this embodiment it is 0.25.

[0058] Inter-layer consistency index S cons Also known as consistency scoring, it is calculated by comparing the difference in soil moisture content between any two adjacent layers after correction with a dynamic threshold, and then statistically analyzing the comparison results of each pair of adjacent layers. In this embodiment, the formula used to calculate the interlayer consistency index based on the corrected soil moisture content of the four layers is as follows:

[0059]

[0060] Where I is an indicator function (1 if the condition is met, 0 otherwise), Δ t This is a dynamic threshold; the default value is 0.05m. 3 / m 3 VWC i This represents the soil moisture content after correction (by influence factors) for the i-th layer.

[0061] Time series continuity index S trend Also known as temporal continuity scoring, it determines the temporal continuity of soil moisture content by statistically analyzing the adjusted soil moisture content over time. The formula used to calculate the temporal continuity index is as follows:

[0062]

[0063] This formula for calculating the temporal continuity index applies to each layer. It calculates the temporal continuity index for each layer, where k is time and tk refers to the k previous time points. In one implementation, the current time point is compared with the data from the three most recent time points. In other implementations, k can take other values, such as 2 or 4. VWC t This represents the soil moisture content at time t of a certain layer after adjustment by the influence factor.

[0064] Based on the calculated indicators, this invention performs a comprehensive quality assessment by weighted summation of the three indicators. The specific calculation formula is as follows:

[0065] Q=ω1·S cv +ω2·S cons +ω3·S trend

[0066] The Q comprehensive quality assessment result is defined as follows: Q is in the range [0, 1], and when Q equals 1, it indicates that the comprehensive quality is optimal. ω1, ω2, and ω3 represent the weights of the coefficient of variation, inter-layer consistency, and time series continuity indicators, respectively. Their values ​​can be set according to actual needs. For example, when the coefficient of variation is more important, ω1 = 0.5, ω2 = 0.3, and ω3 = 0.2 can be set.

[0067] Based on the comprehensive quality assessment results, the quality grades are divided into three levels, as follows:

[0068]

[0069] As can be seen, grade A is the highest, grade B is the next highest, and grade C is the lowest. This invention believes that when the quality grade is classified as grade C, it indicates that the quality of the soil moisture content in each layer after the current correction needs to be further compensated.

[0070] For further compensation, this invention uses the weighted average volumetric moisture content data of the corresponding historical soil for compensation and correction. The most recent period, for example, the weighted average volumetric moisture content of the soil within the last 3 hours, can be used to compensate and correct the weighted average volumetric moisture content of the soil that currently does not meet the quality requirements. Assuming the current time is t, the weighted average volumetric moisture content of the soil between t and t-3 (hours) can be averaged to obtain the weighted average volumetric moisture content of the historical soil. The specific compensation and correction formula is as follows:

[0071] VWC adj =a·VWC raw +(1-a)·VW Chist

[0072] Where α is the adaptive compensation strength, which is related to the overall mass Q. The larger Q is, the larger α is. For example, α = Q / 0.6, VWC adj VWC is the average volumetric water content of the soil after overall compensation (including all strata). raw VWC is the average volumetric water content of the soil before compensation. hist It is the weighted average volumetric water content of historical soil, which is the average volumetric water content of soil over the most recent set time period.

[0073] In another embodiment, when performing a comprehensive quality assessment, the calculation of Q can also select any two indicators from the coefficient of variation index, interlayer consistency index, and time series continuity index. The specific two indicators selected can also be determined according to the actual situation.

[0074] Through the above process, it can be seen that the present invention can correct the volumetric water content of each layer measured by the sensor array based on the influence of differences in stratum thickness, bulk density of different soil layers, crop root depth, and soil type on soil moisture. The weighted average volumetric water content of the soil is obtained by weighted summing of the corrected volumetric water content of each layer. Furthermore, to further improve the accuracy of water content monitoring, the present invention also performs a quality assessment on the corrected volumetric water content of each layer and the weighted average volumetric water content of the soil. If the quality assessment does not meet the requirements (e.g., Q < 0.6), corresponding historical data is used for compensation and correction to ensure that the final soil moisture content meets the requirements.

[0075] Implementation of a single-point soil moisture monitoring system

[0076] The single-point soil moisture monitoring system of the present invention includes a multi-depth sensor array and a data processing module for processing the soil moisture content of each layer measured by the multi-depth sensor array. The data processing module is used to correct the volumetric water content of each layer according to at least two of the following: thickness weight, bulk density compensation coefficient, root regulation factor and soil type compensation coefficient. Based on the corrected volumetric water content data of each layer, the weighted average volumetric water content of the soil is calculated, and the soil moisture is determined according to the weighted average volumetric water content of the soil.

[0077] like Figure 2 As shown, the single-point soil moisture monitoring system of the present invention includes Figure 2The system consists of a multi-depth sensing layer and an intelligent computing layer. The multi-depth sensing layer employs a depth sensor array, temperature sensor, and conductivity sensor. The depth sensor array acquires the volumetric water content of each layer at different depths, while the temperature and conductivity sensors acquire the temperature and conductivity of the corresponding layers. The multi-depth sensing layer transmits the measurements from the depth sensor array, temperature sensor, and conductivity sensor to the intelligent computing layer. The intelligent computing layer includes an edge computing gateway and a cloud fusion platform. The edge computing gateway first verifies the validity of the measured volumetric water content of each layer based on temperature and conductivity, determining if there are any anomalies. If an anomaly is found, the volumetric water content of that corresponding layer is excluded from subsequent calculations to avoid inaccurate calculations of the weighted average volumetric water content of the soil due to abnormal data from a particular layer. Then, the filtered measurement data from the depth sensor array is used for subsequent correction calculations (the specific calculation process has been detailed in the implementation of the single-point soil moisture monitoring method and will not be repeated here). The data processing module is located in the edge computing gateway. The edge computing gateway sends the calculated final weighted average volumetric water content of the soil and the corresponding comprehensive quality assessment results to the cloud fusion platform (hereinafter referred to as the cloud platform). It can be transmitted to the cloud platform via LoRa / 4G dual-mode communication. The cloud platform fuses the final weighted average volumetric water content of the soil with satellite remote sensing data to generate a spatiotemporally continuous water distribution map for use by the decision application layer. The decision application layer includes an irrigation control system and a drought early warning platform. The irrigation control system and the drought early warning platform carry out irrigation decision-making and drought early warning services respectively in different forms and with different contents based on the water distribution map.

Claims

1. A method for single-point soil moisture monitoring, characterized in that, The monitoring method includes the following steps: 1) Use a multi-depth sensor array to obtain the volumetric water content of each layer at different depths in the soil; 2) Determine the thickness weight of each layer based on the depth range of each layer, determine the bulk density compensation coefficient of each layer based on the soil bulk density of each layer, determine the root regulation factor of each layer based on the crop growth period index decay model, the distribution depth of crop roots and the depth of each layer, and determine the soil type compensation coefficient of each layer based on the soil type to which the depth of each layer belongs. 3) Select at least two from the determined thickness weight, bulk density compensation coefficient, root regulation factor and soil type compensation coefficient to correct the volumetric water content of each layer. Calculate the weighted average volumetric water content of the soil based on the corrected volumetric water content data of each layer, and determine the soil moisture based on the weighted average volumetric water content of the soil.

2. The single-point soil moisture monitoring method according to claim 1, characterized in that, The method also includes a quality assessment of the average volumetric water content of the obtained soil. If the quality does not meet the requirements, the average volumetric water content of the obtained soil is compensated by using the historical average volumetric water content of the soil. The quality assessment uses at least two of the following evaluation indicators: coefficient of variation, interlayer consistency, and temporal continuity. The coefficient of variation is used to characterize the overall difference in the water content of each layer, and is calculated based on the standard deviation and average value of the water content of each layer. Interlayer consistency index is used to characterize the consistency of water content in adjacent layers obtained from measurements; temporal continuity index is used to characterize the change of water content in each layer over time.

3. The single-point soil moisture monitoring method according to claim 2, characterized in that, The quality assessment is a weighted sum of the coefficient of variation, interlayer consistency, and time series continuity indicators.

4. The single-point soil moisture monitoring method according to claim 1, characterized in that, In step 1), the volumetric water content of each layer at different depths of the soil is obtained by anomaly screening using the soil temperature and electrical conductivity of the corresponding layer.

5. The single-point soil moisture monitoring method according to claim 2, characterized in that, The formula used to calculate the average volumetric water content of soil is: in VWC is the weighted average volumetric water content of the soil. i Let Δh be the measured volumetric water content of the i-th soil layer, n be the number of layers, and Δh be the volumetric water content of the i-th soil layer. i ρ represents the thickness weight of the i-th soil layer, corresponding to the actual thickness of each layer. i Let σ be the bulk density compensation coefficient of the i-th soil layer. i c is the root regulator of the i-th soil layer. i Let be the soil type compensation coefficient for the i-th soil layer.

6. The single-point soil moisture monitoring method according to claim 1, characterized in that, The calculation formulas used for the bulk density compensation coefficient and the root system adjustment factor are as follows: s i =1+α·exp(-β·|d i -d peak |) Where ρ i Let ρ be the bulk density compensation coefficient of the i-th soil layer. ref For standard reference density, ρ sample Soil bulk density measured by the ring sampler method, σ i is the root regulation factor of the i-th soil layer.

7. A single-point soil moisture monitoring system, comprising a multi-depth sensor array and a data processing module for processing the soil moisture content of each layer measured by the multi-depth sensor array, characterized in that, The data processing module is used to correct the volumetric water content of each layer according to at least two of the following: thickness weight, bulk density compensation coefficient, root regulation factor and soil type compensation coefficient; calculate the weighted average volumetric water content of the soil based on the corrected volumetric water content data of each layer; and determine the soil moisture based on the weighted average volumetric water content of the soil. The thickness weight of each layer is determined based on the depth range of each layer, the bulk density compensation coefficient of each layer is determined based on the soil bulk density of each layer, the root regulation factor of each layer is determined based on the crop growth period index decay model, the distribution depth of crop roots and the depth of each layer, and the soil type compensation coefficient of each layer is determined based on the soil type to which the depth of each layer belongs.

8. The single-point soil moisture monitoring system according to claim 7, characterized in that, The system also includes a quality assessment module, which is used to assess the quality of the obtained average volumetric water content of the soil. If the quality does not meet the requirements, the average volumetric water content of the obtained soil is compensated by using the historical average volumetric water content of the soil. The quality assessment uses at least two of the following evaluation indicators: coefficient of variation, interlayer consistency, and temporal continuity. The coefficient of variation is used to characterize the overall difference in the measured water content of each layer, and is calculated based on the standard deviation and average value of the measured water content of each layer. Interlayer consistency index is used to characterize the consistency of water content in adjacent layers obtained from measurements; temporal continuity index is used to characterize the change of water content in each layer over time.

9. The single-point soil moisture monitoring system according to claim 7, characterized in that, The data processing module uses the following formula to calculate the average volumetric water content of the soil: in VWC is the weighted average volumetric water content of the soil. i Let Δh be the measured volumetric water content of the i-th soil layer, n be the number of layers, and Δh be the volumetric water content of the i-th soil layer. i ρ represents the thickness weight of the i-th soil layer, corresponding to the actual thickness of each layer. i Let σ be the bulk density compensation coefficient of the i-th soil layer. i c is the root regulator of the i-th soil layer. i Let be the soil type compensation coefficient for the i-th soil layer.

10. The single-point soil moisture monitoring system according to claim 8, characterized in that, The single-point soil moisture monitoring system is also used to communicate with a cloud platform to send the obtained weighted average volumetric water content and quality assessment results of the soil to the cloud platform, so that the cloud platform can fuse the data with satellite remote sensing data to generate a moisture distribution map.

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