In-situ calibration method for soil moisture sensor based on multiple points

Abstract

The application belongs to the field of agricultural soil condition monitoring technology, and discloses a kind of in-situ calibration method of soil moisture sensor based on multiple points, comprising the following steps: installing soil moisture sensor, determining a right triangle with soil moisture sensor as vertex, and building cofferdam;First sampling and measuring in the right triangle, obtaining the current soil parameters;Selecting other two vertices on the right triangle as the first sampling point and the second sampling point, respectively sampling, obtaining the measured water content of soil at different stages and the corresponding current value of soil moisture sensor;According to the soil texture composition, through the modification of fitting, temperature correction formula and loose coefficient, then according to the weight coefficient, the soil moisture content is obtained, and then the calibration equation of soil moisture sensor is obtained through the fitting of current value and soil moisture content.The application realizes the in-situ calibration of soil moisture sensor, and also reduces the influence of various factors on the measurement results of soil moisture sensor.

Description

Technical Field

[0001] This invention belongs to the field of agricultural soil moisture monitoring technology, and relates to an in-situ calibration method for soil moisture sensors based on multiple locations. Background Technology

[0002] Soil moisture is a crucial indicator in agricultural production. With the continuous development of information technology in recent years, there are increasingly more information-based methods for monitoring soil moisture, among which soil moisture sensors are the most widely used. By using soil moisture sensors to measure real-time soil moisture content data and combining it with modeling techniques, the optimal irrigation water volume can be calculated relatively accurately, which can significantly improve the efficiency of agricultural irrigation water use and has significant social and ecological value.

[0003] Generally, sensors are calibrated at the factory and can be used immediately after calibration. However, soil moisture sensors are different from ordinary sensors. They need a stabilization period of 1 to 3 months after being buried in the soil to achieve accurate data measurement. The existing calibration method will destroy the original state of the soil and cause deviations in the soil moisture sensor data. Therefore, an in-situ calibration method for soil moisture sensors is needed.

[0004] Furthermore, soil moisture sensors measure soil moisture by measuring the dielectric constant of the soil medium. The dielectric constant changes nonlinearly, and different soil components have a significant impact on the soil moisture characteristic curve. The water content of different soil types also has a significant impact on the dielectric constant change curve. If the traditional single-point calibration method is used, it can only ensure the accuracy of the current humidity point value. At other humidity points, the data will be biased due to the influence of different soil types. Therefore, a multi-point in-situ calibration method for soil moisture sensors is needed. Summary of the Invention

[0005] This invention addresses the technical problems existing in the calibration of existing soil moisture sensors by providing a multi-point in-situ calibration method for soil moisture sensors. Employing a three-point in-situ sampling measurement method, it considers not only factors such as soil texture, water content at different stages, temperature, and looseness, but also the different weights of simulated and measured values. This not only achieves in-situ calibration of the soil moisture sensor but also reduces the influence of various factors on the measurement results, thereby improving the accuracy of soil moisture measurement.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] This invention provides an in-situ calibration method for a multi-point soil moisture sensor, comprising the following steps:

[0008] Step 1: Install a soil moisture sensor in the soil and wait for the soil at the installation location to return to normal.

[0009] Step 2: Using the soil moisture sensor as the vertex, determine an equilateral triangle with a side length of 60-80cm, and build a cofferdam;

[0010] Step 3: Take the first sample and measure within the equilateral triangle to obtain the current soil parameters;

[0011] Step 4: Select two vertices on the equilateral triangle other than the soil moisture sensor as the first sampling point and the second sampling point. Perform over-irrigation inside the cofferdam and take samples at the first and second sampling points respectively to obtain the measured soil moisture content at different stages and the corresponding current value of the soil moisture sensor.

[0012] Step 5: Based on the soil texture composition, obtain the simulated soil moisture content through polynomial fitting equations and quadratic function fitting equations;

[0013] Step 6: Use the temperature correction formula and the looseness coefficient to correct the simulated soil moisture content obtained in Step 5, and obtain the corrected soil moisture content.

[0014] Step 7: Based on the weighting coefficients, sum the measured soil moisture content and the corrected soil moisture content to obtain the soil moisture content;

[0015] Step 8: Using the current value of the soil moisture sensor as the independent variable and the soil moisture content as the dependent variable, perform quadratic function fitting using the least squares method to obtain the calibration equation of the soil moisture sensor.

[0016] Furthermore, the current soil parameters mentioned in step 3 of this invention include soil texture composition, looseness coefficient, and current value of the soil moisture sensor.

[0017] Furthermore, the measured soil moisture content at different stages in step 4 of this invention includes the measured saturated soil moisture content, the measured field capacity, and the measured wilting point moisture content.

[0018] Further, step 4 of the present invention specifically includes: selecting the soil sampled for the first time, measuring the current value of the soil moisture sensor at the wilting point and the measured water content at the wilting point; selecting two vertices on the equilateral triangle other than the soil moisture sensor as the first sampling point and the second sampling point; performing excessive irrigation within the dike, and recording the current value of the soil moisture sensor when the current value of the soil moisture sensor changes from a rapid increase to a stable state, sampling at the first sampling point and measuring the measured saturated water content of the soil; recording the current value of the soil moisture sensor when the current value of the soil moisture sensor changes from a rapid decrease to a stable state, sampling at the second sampling point and measuring the measured field capacity of the soil.

[0019] Furthermore, the polynomial fitting equation in step 5 of this invention is as follows:

[0020] F1=θ1WSP+θ2WP+θ3SP+θ4WS+θ5W+θ6S+θ7P+θ8,

[0021] Where W is the sand content in the soil, S is the clay content in the soil, P is the organic matter content in the soil, and θ 1～ θ8 is the fitting coefficient, and F1 is the polynomial fitting water content of the soil.

[0022] Furthermore, in step 7 of this invention, the weighting coefficient for the measured soil moisture content is 0.8, and the weighting coefficient for the corrected soil moisture content is 0.2.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] This invention employs a three-point sampling measurement method, which ensures high consistency between the soil conditions at the sampling points and those measured by the soil moisture sensor, while also minimizing damage to the surrounding soil structure. Since the operating environment of the soil moisture sensor varies, factors such as soil texture, water content, temperature, and aeration all affect the accuracy of the measurement. Therefore, this invention, after employing the three-point sampling method, considers not only factors such as soil texture, water content at different stages, temperature, and aeration, but also the different weights of simulated and measured values ​​to obtain the soil moisture content. Furthermore, by fitting a quadratic function to the current value of the soil moisture sensor and the soil moisture content, the calibration equation for the soil moisture sensor is finally obtained. This not only achieves in-situ calibration of the soil moisture sensor but also reduces the influence of various factors on the measurement results.

[0025] Compared to traditional single-point calibration, this invention obtains the measured soil moisture content and the corresponding current value of the soil moisture sensor at different stages through three-point sampling, thereby improving the accuracy of soil moisture sensor in measuring soil moisture. Attached Figure Description

[0026] Figure 1 This is a sampling point distribution diagram for the three-point sampling method used in this invention.

[0027] Figure 2 This is a schematic diagram illustrating the soil moisture variation pattern according to the present invention. Detailed Implementation

[0028] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of protection of the present invention. Unless otherwise specified, the technical means used in the embodiments are conventional means well known to those skilled in the art. Unless otherwise specified, the test methods in the following embodiments are conventional methods.

[0029] Example 1

[0030] Taking four soil samples from the experimental site in Yuanyang County as examples, the soil moisture sensor selected is a current-type sensor with an output signal of 4-20mA and a maximum range of 100mA. The in-situ calibration method for soil moisture sensors based on multiple locations according to this invention is described in detail, specifically including the following steps:

[0031] Step 1: Install a soil moisture sensor in the soil and wait for the soil at the installation location to return to normal.

[0032] Step 2: As Figure 1 As shown, an equilateral triangle with a side length of 70cm is defined with the soil moisture sensor as the vertex, and a cofferdam is built.

[0033] Step 3: Take the first sample and measure within the equilateral triangle to obtain the current soil texture composition, looseness coefficient, and soil moisture sensor current value I, as shown in Table 1.

[0034] Table 1 Soil parameters from four soil samples

[0035]

[0036]

[0037] Step 4: Select two vertices on the equilateral triangle other than the soil moisture sensor as the first sampling point and the second sampling point. Perform over-irrigation within the cofferdam and take samples at the first and second sampling points respectively to obtain the measured soil moisture content F0 at different stages and the corresponding current value I0 of the soil moisture sensor.

[0038] The specific steps are as follows: Select the soil sampled for the first time, and measure the current value I of the soil moisture sensor at the wilting point. 0W And the measured water content at the wilting point F 0W Select two vertices on the equilateral triangle other than the soil moisture sensor as the first and second sampling points; conduct over-irrigation within the cofferdam, and record the soil moisture sensor current value I when the current value changes from a rapid increase to a stable state. 0B The measured saturated water content F of the soil was obtained by taking samples at the first sampling point (second sampling). 0B Once the current value of the soil moisture sensor stabilizes after a rapid decrease, record the current value I at this point. 0C The measured field capacity F of the soil was obtained by taking samples at the second sampling point (the third sampling). 0C After the measurement was completed, the soil was backfilled into the sampling holes and compacted. After compaction, water was injected to accelerate the soil recovery of the sampling holes. The results are shown in Tables 2 and 3.

[0039] Table 2 Measured water content of four soil types at different stages

[0040] serial number Soil texture <![CDATA[Measured saturated water content F 0B > <![CDATA[Measured field water holding capacity F 0C > <![CDATA[Wilting point water content F 0W > Group 1 loam 0.553 0.274 0.158 Group 2 loam 0.494 0.289 0.142 Group 3 Sandy loam soil 0.468 0.245 0.125 Group 4 Sandy loam soil 0.436 0.204 0.95

[0041] Table 3. Current values ​​of soil moisture sensors for four types of soil at different stages.

[0042]

[0043]

[0044] like Figure 2 As shown, the soil moisture change pattern is divided into five stages: 1) Normal state, the current state of the soil; 2) Initial irrigation stage, where water rapidly infiltrates and soil moisture quickly increases from the normal state to saturation; 3) Stabilization stage, where soil moisture remains at saturation; 4) Recession stage, where water rapidly infiltrates to surrounding areas after water replenishment ceases, and soil moisture content decreases; 5) Stabilization stage, where most of the available water has infiltrated and the soil reaches field capacity. The sampling stages of this invention focus on the normal state, the stabilization stage of irrigation, and the stabilization stage of receding water, allowing the determination of the soil's wilting point moisture content F. 0W Measured saturated water content F 0B and measured field water holding capacity F 0C It should be noted that the wilting point refers to the soil moisture content that cannot be absorbed and utilized by plants. Below this soil moisture content, plants will wilt and die. Since the normal soil moisture content is generally lower than the moisture content during the stabilization phase after waterlogging, the normal soil moisture content can be used as the measured wilting point moisture content F. 0W .

[0045] This invention constructs an equilateral triangle with sides of 60-80cm, using a soil moisture sensor as the vertex. The first and second sampling points are equidistant from the soil moisture sensor, ensuring high consistency between the soil moisture at the sampling points and the moisture measured by the sensor, while minimizing damage to the surrounding soil structure. After the first sampling, water is injected through a dike. Because holes are left after the first sampling within the equilateral triangle, water flows outwards from the holes at the first sampling point, quickly bringing the soil to saturation. Furthermore, since the distances from the first and second sampling points to the soil moisture sensor are equidistant, the soil moisture measured by the sensor during the second sampling is consistent with the moisture at the second sampling point. Different soil textures have different infiltration capacities; after an interval of 48-72 hours, the current value of the soil moisture sensor changes from a rapid decrease to a stable state, at which point the second sampling is performed.

[0046] Step 5: Based on the soil texture composition, the simulated soil moisture content is obtained through polynomial fitting equations and quadratic function fitting equations, namely the simulated saturated soil moisture content, simulated field capacity, and simulated wilting point moisture content.

[0047] The polynomial fitting equation used in this step is as follows:

[0048] F1=θ1WSP+θ2WP+θ3SP+θ4WS+θ5W+θ6S+θ7P+θ8,

[0049] Where W is the sand content in the soil, S is the clay content in the soil, P is the organic matter content in the soil, and θ 1～ θ8 is the fitting coefficient, and F1 is the polynomial fitting water content of the soil.

[0050] The quadratic function fitting formula used in this step is as follows:

[0051] F2=aF1 2 +bF1+c

[0052] Where F2 is the quadratic function fitting water content of the soil, and a, b, and c are the quadratic function fitting coefficients.

[0053] Based on the various components in the soil, the polynomial and quadratic function fitting equations for the simulated saturated water content, simulated field capacity, and simulated wilting point water content of the soil are shown in Table 4.

[0054] Table 4. Polynomial and Quadratic Function Fitting Equations for Soil

[0055]

[0056] Substituting the components of the soil into the polynomial fitting equation, the polynomial fitting water content F1 of the four soils is shown in Table 5.

[0057] Table 5 Polynomial-fit water content of four soil types

[0058]

[0059] Substituting the polynomial-fitted water content of the four soil types into the quadratic function fitting equation, the quadratic function-fitted water content F2 of the four soil types is obtained as shown in Table 6.

[0060] Table 6 Quadratic function fit to water content for four soil types

[0061]

[0062] Step 6: Correct the simulated soil moisture content obtained in Step 5 using the temperature correction formula and the looseness coefficient, respectively, to obtain the corrected soil moisture content F3 and F4.

[0063] The temperature correction formula used in this invention is as follows:

[0064] F3 = F2 / (1 + α△t),

[0065] Where F3 is the simulated soil moisture content after temperature correction; α is the temperature variation coefficient, α is taken as 0.02; Δt is the temperature change relative to 20℃.

[0066] In this embodiment, the current temperature is 25℃, so the temperature correction formula is as follows: F3=F2 / (1+0.02*5)=F2 / 1.1. The corrected moisture content F3 for the four types of soil is shown in Table 7.

[0067] Table 7. Simulated moisture content of four soil types after temperature correction.

[0068]

[0069] The soil moisture content was further corrected using the looseness coefficient, i.e., F4 = F3 * looseness coefficient. The corrected moisture content F4 of the four soils after further correction by the looseness coefficient is shown in Table 8.

[0070] Table 8. Corrected moisture content of four soil types after further adjustment for looseness coefficient.

[0071]

[0072] Step 7: Based on the weighting coefficients, sum the measured soil moisture content F0 and the corrected soil moisture content F4 to obtain the soil moisture content F5.

[0073] In this invention, the weighting coefficient for the measured soil moisture content is set to 0.8, and the weighting coefficient for the corrected soil moisture content is set to 0.2. The soil moisture content is shown in Table 9.

[0074] Table 9. Weighted water content of the four soil types

[0075]

[0076] Step 8: Using the current value of the soil moisture sensor as the independent variable and the soil moisture content as the dependent variable, perform quadratic function fitting using the least squares method to obtain the calibration equation of the soil moisture sensor.

[0077] Specifically, the current value I of the soil moisture sensor at saturated water content is used. 0B and saturated water content F 5B The current value I of the soil moisture sensor at field water holding capacity. 0C Field water holding capacity F 5C The current value I of the soil moisture sensor at the wilting point 0W and the moisture content at the wilting point F5W The three points are used to fit a quadratic function using the least squares method. The calibration equations for the soil moisture sensors of the four soil types are shown in Table 10.

[0078] Table 10 Calibration equations for soil moisture sensors for four soil types

[0079] serial number Soil type Fitting formula Group 1 loam <![CDATA[F=0.37I 2 -1.40I+9.39]]> Group 2 loam <![CDATA[F=-0.04I 2 +5.43I-17.21]]> Group 3 Sandy loam soil <![CDATA[F=0.18I 2 +1.66I-4.01]]> Group 4 Sandy loam soil <![CDATA[F=0.24I 2 +0.56I-0.58]]>

[0080] Substitute the current value I of the soil moisture sensor measured in Table 1 into the fitting formula in Table 10 to obtain the calibrated soil moisture content. At the same time, use the conventional current to moisture content conversion formula (F=100 / 16*(I-4)) to obtain the uncalibrated soil moisture content. The results are shown in Table 11.

[0081] Table 11 Soil moisture content calibrated using the method of this invention and uncalibrated soil moisture content

[0082] serial number Soil type Calibrated values Uncalibrated values Change before and after calibration Group 1 loam 0.19 0.21 0.02 Group 2 loam 0.39 0.46 0.07 Group 3 Sandy loam soil 0.13 0.14 0.01 Group 4 Sandy loam soil 0.26 0.34 0.08

[0083] As can be seen from Table 11, the soil moisture content calibrated using the method of the present invention is lower than that of the uncalibrated value. This demonstrates the importance of calibrating the soil moisture sensor, which can accurately predict soil moisture content, replenish water in a timely manner, and reduce crop yield reduction caused by untimely water replenishment.

[0084] The embodiments described above are merely preferred embodiments of the present invention and are only used to explain the present invention. They are not intended to limit the scope of the present invention. For those skilled in the art, other implementation methods can be easily made by substitution or modification based on the technical content disclosed in this specification. Therefore, all changes and improvements made on the principle of the present invention should be included within the scope of the patent application of the present invention.

Claims

1. A method for in-situ calibration of a multi-point soil moisture sensor, characterized in that, Includes the following steps: Step 1: Install a soil moisture sensor in the soil and wait for the soil at the installation location to return to normal. Step 2: Using the soil moisture sensor as the vertex, determine an equilateral triangle with a side length of 60-80cm, and build a cofferdam; Step 3: Take the first sample and measure within the equilateral triangle to obtain the current soil parameters; Step 4: Select two vertices on the equilateral triangle other than the soil moisture sensor as the first and second sampling points. Perform over-irrigation within the dike, and take samples at both the first and second sampling points to obtain the measured soil moisture content at different stages and the corresponding current value of the soil moisture sensor. The measured soil moisture content at different stages includes the measured saturated soil moisture content, measured field capacity, and measured wilting point moisture content. Step 4 specifically includes: using the soil sampled in the first sampling, measuring the current value of the soil moisture sensor at the wilting point, and... To measure the water content at the wilting point, two vertices of an equilateral triangle other than the soil moisture sensor were selected as the first and second sampling points. Excessive irrigation was carried out within the enclosure. When the current value of the soil moisture sensor changed from a rapid increase to a stable state, the current value of the soil moisture sensor was recorded. The soil saturation water content was measured at the first sampling point. When the current value of the soil moisture sensor changed from a rapid decrease to a stable state, the current value of the soil moisture sensor was recorded. The soil field capacity was measured at the second sampling point. Step 5: Based on the soil texture composition, obtain the simulated soil moisture content through polynomial fitting equations and quadratic function fitting equations; Step 6: Use the temperature correction formula and the looseness coefficient to correct the simulated soil moisture content obtained in Step 5, and obtain the corrected soil moisture content. Step 7: Based on the weighting coefficients, sum the measured soil moisture content and the corrected soil moisture content to obtain the soil moisture content; Step 8: Using the current value of the soil moisture sensor as the independent variable and the soil moisture content as the dependent variable, perform quadratic function fitting using the least squares method to obtain the calibration equation of the soil moisture sensor.

2. The in-situ calibration method for a multi-point soil moisture sensor according to claim 1, characterized in that, The current soil parameters mentioned in step 3 include soil texture composition, looseness coefficient, and current value of the soil moisture sensor.

3. The in-situ calibration method for a multi-point soil moisture sensor according to claim 1, characterized in that, The polynomial fitting equation in step 5 is as follows: F1= θ 1 WSP+θ 2 WP+θ 3 SP+θ 4 WS+θ 5 W+θ 6 S+θ 7 P+θ 8 ， Where W represents the sand content in the soil, S represents the clay content in the soil, and P represents the organic matter content in the soil. θ 1~ θ 8 is the fitting coefficient, and F1 is the polynomial fitting water content of the soil.

4. The in-situ calibration method for a multi-point soil moisture sensor according to claim 1, characterized in that, In step 7, the weighting factor for the measured soil moisture content is 0.8, and the weighting factor for the corrected soil moisture content is 0.2.

Images