A quantitative method for soil equivalent pore size distribution based on low-field nuclear magnetic resonance

Abstract

This invention discloses a quantitative method for soil equivalent pore size distribution based on low-field nuclear magnetic resonance (NMR). Soil samples are collected using a non-metallic ring sampler; the transverse NMR signal attenuation curve of the saturated soil sample is measured using a 22MHz low-field NMR instrument; the T2 spectrum of the low-field NMR is obtained; the NMR signal intensity is converted into soil volumetric water content; the relaxation time is converted into matrix suction; and the matrix suction is converted into soil equivalent pore size using the quantitative relationship between matrix suction and equivalent pore diameter. This invention is simple to operate, low in cost, and can shorten the soil equivalent pore size distribution measurement time from the traditional 1-3 months to just a few minutes. It is a simple and efficient quantitative measurement method for soil equivalent pore size distribution, and has wide applicability, suitable for rapid measurement of moisture characteristic curves and equivalent pore size distribution of different types and textures of soil in my country.

Description

Technical Field

[0001] This invention relates to a method for quantifying the equivalent pore size distribution of soil based on low-field nuclear magnetic resonance, belonging to the field of soil hydrology technology. Background Technology

[0002] Soil structure determines soil function, and the distribution of equivalent pore size is one of the most important characteristic indicators of soil structure. It determines soil hydraulic properties, influences soil hydrological processes, and has a significant impact on the functioning of soil production and ecology. The lack of detailed information on national or regional soil structure characteristics, represented by soil pore size distribution, is a major factor restricting agricultural production, hydrological forecasting, and ecological environment construction in my country. Therefore, determining the distribution of equivalent pore size is a crucial task in my country's soil digital information system. Due to the lack of in-situ field methods, the determination of soil equivalent pore size distribution or soil moisture characteristic curves is generally based on the analysis of undisturbed soil samples collected by metal ring cutters in the laboratory. Traditional testing methods include sandbox methods, suction plate methods, pressure membrane methods, tensiometer methods, and evaporation methods. Most of these methods are based on relatively slow water movement processes such as evaporation and drainage, resulting in high costs, long processing times, low efficiency, and high technical difficulty. These methods are insufficient to meet the needs of agricultural soil structure research, let alone the requirements for large-scale monitoring of soil hydraulic properties during regional soil surveys. Therefore, a simple and efficient method for determining soil equivalent pore size distribution is urgently needed. With its advantages of being rapid, non-destructive, harmless to humans, and highly sensitive, low-field nuclear magnetic resonance (NMR) was first used to determine soil moisture content in 1970. Later, it was also applied in food science, rock exploration, and oil well logging, serving as an important tool for studying the pore size distribution or the distribution of liquid substances such as water and oil in porous media. In recent years, NMR has been introduced into soil science and soil hydrology research, demonstrating its great potential for efficiently measuring the equivalent pore size distribution of soil. However, how to quantify the pore size distribution based on the low-field NMR signal of porous media remains a challenging problem. For relatively simple rock pore size distribution measurements, current common methods include mercury intrusion porosimetry (MIP) or using glass beads filled with regular particles and stable physicochemical properties to simulate actual rock pores to calibrate the relationship between low-field NMR signals and pore size. However, MIP involves toxic and harmful substances, and glass beads are far removed from actual rock pores. Furthermore, compared to geological exploration and oil well logging in the lithosphere, the unsaturated zone is the most biologically active sphere, and the study of hydrological processes in the unsaturated zone requires higher precision in understanding soil pore size distribution. However, soil particle composition, physicochemical properties, pore shape, and size distribution characteristics are far more complex than those of rock layers, with more factors influencing soil low-field NMR signals, such as paramagnetic substances, dielectric concentration, and soil texture. Currently, there is no effective way to quantify the relationship between low-field NMR signal characteristics and soil equivalent pore size distribution; related methods remain qualitative. Therefore, low-field NMR is a promising method for quantifying soil equivalent pore size distribution, but the quantitative relationship between soil low-field NMR signals and soil equivalent pore size distribution must first be resolved. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for quantifying the equivalent pore size distribution of soil based on low-field nuclear magnetic resonance.

[0004] The technical solution adopted in this invention is: a method for quantitatively analyzing the equivalent pore size distribution of soil based on low-field nuclear magnetic resonance, characterized by comprising the following steps:

[0005] Step 1: Collect soil samples using a non-metallic ring cutter with very low or no hydrogen proton content;

[0006] Step 2: Measure the decay curve of the transverse nuclear magnetic resonance signal intensity of the saturated soil sample over time using a low-field nuclear magnetic resonance instrument of 10-22MHz.

[0007] Step 3: Using the inverse Laplace transform numerical inversion method, the NMR signal intensity H and relaxation time τ of water in soil pores of different sizes are interpreted from the transverse NMR signal attenuation curve to obtain the T2 spectrum of low-field NMR (…). Figure 2 a);

[0008] Step 4: Using the quantitative relationship between NMR signal intensity H and soil volumetric water content θ (Table 1), the NMR signal intensity H is converted into soil volumetric water content θ. Figure 2 b);

[0009] Step 5, utilize the quantitative relationship between relaxation time τ and matrix suction s ( Figure 2 c and Figure 2 d) Convert the relaxation time τ into matrix suction s;

[0010] Step 6: Using the quantitative relationship between matrix suction s and equivalent pore radius r (r = 2σ / s, where σ is the surface tension coefficient of water, in mN / m), the matrix suction s is converted into soil equivalent pore size r.

[0011] Preferably, the ring cutter in step 1 is made of PVC or quartz tube.

[0012] Preferably, the low-field nuclear magnetic resonance instrument used in step 2 has a measurement probe inner diameter of 30 mm, an effective monitoring area height of 50 mm, a magnet frequency of 22 MHz, a dead time of 23 μs, uses a CPMG pulse sequence, and the signal amplitude is determined by the first echo of the CPMG with an echo interval of 0.08 ms.

[0013] Preferably, in step 4, for soils with a clay content >35% and a paramagnetic substance content >1.5%, the quantitative relationship between NMR signal intensity and soil moisture content is defined as H = m·θ. n The quantitative relationship for the remaining soil is H = m·θ( Figure 2b), where θ is the soil moisture content, H is the soil NMR signal intensity, and m and n are empirical coefficients. Common classification conversion functions for typical soils are shown in Table 1.

[0014] Table 1. Classification conversion function of soil moisture content and NMR signal intensity

[0015]

[0016]

[0017] This invention is simple to operate and low in cost. It can shorten the time for determining the equivalent pore size distribution of soil from the traditional 1 to 3 months to just a few minutes. It is a simple and efficient quantitative measurement method for the equivalent pore size distribution of soil and has wide applicability. It can be used for the rapid measurement of moisture characteristic curves and equivalent pore size distribution of soils of different types and textures in my country.

[0018] The beneficial effects of this invention are as follows:

[0019] 1. It is simple to operate. The present invention has few operation steps, the process is simple and easy to master.

[0020] 2. High efficiency. The measurement time required by this invention is much shorter than that of traditional methods, and it is simple and efficient, making it suitable for batch measurements in large-scale soil surveys.

[0021] 3. Economic efficiency. High-field NMR offers higher measurement resolution and range, but it is bulky and expensive, currently mainly used for measuring molecular structures containing H protons and with relatively short relaxation times. Since water has a relatively long relaxation time, low-field NMR can be used to measure most pore water, significantly reducing instrument size and cost. Furthermore, compared to traditional methods for measuring equivalent pore size distribution in soil, such as sandbox-pressure membrane analyzers, this invention uses low-field NMR technology, which can achieve measurements in just a few minutes, requiring less time and reducing labor and monitoring costs, making it more suitable for large-scale measurements.

[0022] 4. High sensitivity. This invention exhibits low human error, good result stability, and high sensitivity to changes in soil pore structure caused by tillage compaction, material improvement, etc.

[0023] 5. Robustness. This invention fully considers the influencing factors that may exist in the measurement of equivalent pore size in soil (such as paramagnetic substances, solution mineralization, soil texture, etc.). The method clearly defines the scope of the influence of these factors, and the results have sufficient stability and reliability.

[0024] 6. Universality. This invention fully considers the differences in soil type and texture, that is, it takes into account the common relationship between soil low-field NMR signal and soil equivalent pore size distribution characteristics, as well as the differential characteristics, and classifies and establishes solutions that can be used for various types and textures of soil, thus having a wide range of applicability. Attached Figure Description

[0025] Figure 1 A flowchart of the present invention.

[0026] Figure 2 The technical principles and schematic diagrams of this invention;

[0027] Figure 3 Low-field nuclear magnetic resonance soil samples and testing;

[0028] Figure 4 A comparison of the cumulative distribution curve of soil equivalent pore size quantified by the method of this invention with the measurement results of traditional methods;

[0029] Figure 5 The method of this invention measures the sensitivity of the soil equivalent pore size distribution to changes in the pore structure of typical farmland soil. Detailed Implementation

[0030] The following combines soil tests and Figure 1 This further illustrates the content of the present invention, but should not be construed as limiting the invention. Modifications and substitutions made to the methods, steps, or conditions of the present invention without departing from the spirit and essence of the invention are all within the scope of the invention. Unless otherwise specified, the technical means used in the following embodiments are conventional means well known to those skilled in the art.

[0031] Experimental Objectives: Example 1 selected four representative soils from major grain-producing areas in China, such as the Northeast Black Soil Region, the Huang-Huai-Hai Plain, the Southern Red Soil Region, and the Loess Plateau: black soil, alluvial soil, red soil, and loess. The accuracy of the method described in this invention in quantifying the equivalent pore size distribution of soils in major agricultural types in China was verified by comparing it with traditional soil moisture characteristic curve measurement methods. Example 2 selected field soils from alluvial soils of the Huang-Huai-Hai Plain, sandy black soils, and Northeast black soils used in structural improvement experiments to verify the sensitivity of the soil equivalent pore size distribution quantified by the method of this invention for monitoring the effects of structural improvement measures. This provides an effective means for large-scale soil structural characteristic surveys in agricultural areas of China and for agricultural soil improvement.

[0032] Example 1

[0033] 1. Materials and Methods

[0034] The soil samples used for testing were typical farmland soils with significant differences in properties between northern and southern China: sandy loam loam, collected from Baota District, Yan'an City, Shaanxi Province (36°44′N, 109°35′E); loamy alluvial soil, collected from Fengqiu County, Xinxiang City, Henan Province (35°00′N, 114°24′E); clay loam black soil, collected from Daowai District, Harbin City, Heilongjiang Province (45°49′N, 126°50′E); and clayey red soil, collected from Yujiang District, Yingtan City, Jiangxi Province (28°20′N, 116°95′E). After collection, the soil samples were brought back to the laboratory, air-dried, crushed, and sieved through a 2mm sieve before use.

[0035] The physicochemical properties of the four soils are shown in Table 3. The organic matter content of the soils was determined using the high-temperature external heating potassium dichromate oxidation-volume method (Zhang Rongrong, 2019); the soil particle size distribution was determined using a laser particle size analyzer LS13320 (Tao Lu et al., 2021); and the soil iron oxide content was determined using X-ray energy dispersive spectroscopy (Rong Nianhang et al., 2014). The moisture characteristic curves of the four soils were determined using the sandbox method and the pressure membrane method, with a ring cutter inner diameter of 4.7 cm, a height of 5.0 cm, and a bulk density controlled at 1.20 g·cm³. -3 (Black soil), 1.35 g·cm³ -3 (Yellow cotton soil), 1.39 g·cm³ -3 (soil) and 1.35g·cm -3 (Red soil) The bulk density was consistent with that measured during field sampling. The moisture content was measured in a sandbox under a suction force of 0-500 mbar, and the moisture content under a suction force greater than 500 mbar was measured using a pressure membrane apparatus.

[0036] Table 2. Main physicochemical properties of the tested soils

[0037]

[0038]

[0039] Before low-field NMR testing, the four types of test soil were dried in an oven at 105℃ for 8 hours until completely dry. The dried soil was then evenly packed into soil columns with an inner diameter of 2.5 cm and a height of 2.2 cm, with the bulk density controlled at 1.20 g·cm³. -3 (Black soil), 1.35 g·cm³ -3 (Yellow cotton soil), 1.39 g·cm³ -3 (soil) and 1.35g·cm -3(Red soil) The bulk density was consistent with that measured during field sampling. Two layers of 5cm diameter circular filter paper were wrapped around the bottom of the ring sampler and secured with rubber bands. Then, purified water was added to the soil column, and low-field nuclear magnetic resonance (NMR) testing was performed. Specific experimental treatments were as follows: 0, 1.5, 3, and 4.5 ml of purified water were slowly dripped into the four soil types using a pipette, maintaining soil volumetric water content at 0%, 13.9%, 27.8%, and 41.7%, respectively. Each water content treatment was repeated in triplicate. After air was expelled from the soil, it was sealed and allowed to stand for 2-3 days to allow for moisture redistribution before low-field NMR testing.

[0040] The NMR analyzer system used in this experiment measured the low-field nuclear magnetic resonance T2 distribution spectrum of soil. The probe inner diameter was 30 mm, the effective monitoring area height was 50 mm, the magnet frequency was 22 MHz, and the dead time was 23 μs. The instrument used a CPMG pulse sequence, and the signal amplitude was determined by the first echo of the CPMG. The echo interval (T...) E The pulse width was 0.08 ms. When testing black soil and red soil, the pulse widths at 90° and 180° were 7.68 μs and 15.16 μs, respectively; when testing alluvial soil, the pulse widths at 90° and 180° were 15.24 μs and 30.48 μs, respectively. For NMR testing, the best results are obtained when the ring sample is in close contact with the probe. Therefore, the filter paper at the bottom of the ring sample is gently removed, and the sample is then placed into a 30 mm outer diameter glass tube for testing. Figure 3 a). During the experiment, the soil sample was placed into the probe inside the monitoring chamber. Figure 3 b) After calibrating the test parameters, perform nuclear magnetic resonance testing.

[0041] After the measurement is completed, the instrument acquires the relaxation information of each sample, namely the decay curve of the transverse nuclear magnetic resonance signal intensity over time. The transverse relaxation time T2 distribution spectrum is obtained by inverse Laplace transform. Figure 2 a) This refers to the data sequence of low-field NMR signal intensity H as a function of relaxation time τ. Then, according to steps 4-6 of the technical solution, the low-field NMR T2 distribution spectra of the four soil types at saturation are converted into soil equivalent pore size distribution curves. Specifically, the relaxation time τ on the horizontal axis is converted into the soil equivalent pore size r, and the low-field NMR signal intensity H on the vertical axis is converted into the volumetric water content of the corresponding pore size. The specific process is as follows:

[0042] Step 4: Based on the soil clay, paramagnetic iron oxide, and soil organic matter content in Table 2, select the corresponding quantitative relationship between low-field NMR signal intensity H and soil volumetric water content θ in Table 1, and convert the NMR signal intensity H on the vertical axis into the volumetric water content of the corresponding pore size. Figure 2(b) For example: Black soil is taken from a semi-humid region, with a clay content greater than 35%, a paramagnetic iron oxide content less than 1.5%, and an organic matter content greater than 3%. Therefore, the conversion relationship H = 3.38·θ corresponding to high organic matter soils in semi-humid regions is selected. Yellow loam soil is taken from an arid region, with a clay content less than 35% and a paramagnetic iron oxide content less than 1.5%. Therefore, the conversion relationship H = 4.16·θ corresponding to soils in arid regions is selected. Alluvial soil is taken from a semi-humid region, with a clay content less than 35%, a paramagnetic iron oxide content less than 1.5%, and an organic matter content less than 3%. Therefore, the conversion relationship H = 3.67·θ corresponding to low organic matter soils in semi-humid regions is selected. Red soil is taken from a humid region, with a clay content of 45.3%, much greater than 35%, a high degree of ferroaluminization, and a paramagnetic iron oxide content as high as 4.03%, much greater than 1.5%. Therefore, the conversion relationship H = 0.24·θ corresponding to highly weathered ferroaluminate soils in humid regions is selected. 1.67 .

[0043] Step 5: Based on the climatic characteristics of the soil region and the soil organic matter content in Table 2, select an appropriate quantitative relationship between relaxation time τ and matrix suction s. Figure 2 c and Figure 2 d) First, convert the relaxation time τ on the horizontal axis into matrix suction s. For example, black soil is taken from a semi-humid region with an organic matter content greater than 3%, therefore, the conversion relationship corresponding to high organic matter soils in a semi-humid region is selected. Since the loess soil was taken from an arid region, a transformation relationship corresponding to soils in arid regions was selected. The alluvial soil sample was taken from a semi-humid region and had an organic matter content of less than 3%. Therefore, a conversion relationship corresponding to low-organic-matter soils in semi-humid regions was selected. The red soil sample was taken from a humid region with abundant rainfall and strong leaching, resulting in a high degree of iron and aluminum oxidization. Therefore, the conversion relationship corresponding to highly weathered iron and aluminum soils in the humid region was selected.

[0044] Step 6: Calculate the surface tension coefficient based on the water temperature t and the formula σ = 75.796 - 0.145 * t - 0.00024 * t^2. For example, at t = 20℃, σ = 72.8 mN / m. Then, using the quantitative relationship r = 2σ / s, the matrix suction s on the horizontal axis is further converted into the equivalent soil pore size r. This transforms the T2 distribution spectra of low-field nuclear magnetic resonance at saturation for four soil types into equivalent soil pore size distribution curves.

[0045] The sandbox-pressure membrane method is currently recognized as the standard method for obtaining the equivalent pore size distribution of soil, and it serves as a reference for verifying the method of this invention. The result measured by the sandbox-pressure membrane method is a soil moisture characteristic curve, i.e., the relationship between the total pore water content θ below a certain equivalent pore size and the matrix suction s corresponding to the equivalent pore size r. Similarly, using the formula r = 2σ / s from step 6 above, the matrix suction s on the horizontal axis is converted into the equivalent pore size r, thus transforming the soil moisture characteristic curve into a cumulative distribution curve of the equivalent pore size of soil. Figure 4 The soil equivalent pore size distribution curve obtained by the low-field nuclear magnetic resonance method is similar to the frequency curve. For easy comparison, it needs to be transformed again. By using the discrete summation method, the water content of pores with a diameter of r on the vertical axis is transformed into the water content of all pores with a diameter less than or equal to r, thus obtaining the cumulative distribution curve of soil equivalent pore size (points in the middle). Figure 4 (The line in the middle).

[0046] 2. Experimental Results

[0047] Yellow loess, alluvial soil, black soil, and red soil represent the main soil types in our major grain-producing areas. These regions span a wide area, with significant differences in soil occurrence environments, soil types, clay minerals, texture, organic matter, and paramagnetic substances (Table 2). Using these soil types to verify the present invention has general significance. The equivalent pore size distribution curves of the four soil types, measured by the traditional sandbox and pressure membrane apparatus methods and by the method of the present invention, are plotted respectively on [Table 2]. Figure 4 ad. by Figure 4 It can be seen that the soil equivalent pore size distribution results obtained by the method of this invention for loess, alluvial soil, black soil, and red soil are in excellent agreement with the results obtained by the traditional standard method, and the coefficient of determination R of their correlation is very high. 2 The values ​​reached 0.9361, 0.9477, 0.9824, and 0.9892 respectively (P<0.01). Therefore, the cumulative pore size distribution curve predicted based on the low-field NMR signal has a highly significant correlation with the measured value. The soil equivalent pore size distribution information obtained using this invention is relatively reliable and accurate, and has strong adaptability to differences in soil type, texture, and properties.

[0048] Example 2

[0049] 1. Materials and Methods

[0050] The tested soils were farmland soils from my country's three major grain-producing areas, including undisturbed samples of alluvial soil, black soil, and sandy black soil. Alluvial soil was collected from a long-term biochar improvement experimental site in Fengqiu County, Xinxiang City, Henan Province (35°00′N, 114°24′E); sandy black soil was collected from a long-term experimental site at the Anhui Agricultural University's Northern Anhui Comprehensive Experimental Station in Yongqiao District, Suzhou City, Anhui Province (33°64′N, 116°98′E); and black soil was collected from black soil structure compaction and compaction reduction experimental demonstration areas in Hailun City, Suihua City, Heilongjiang Province (47°43′N, 126°79′E) and Gongzhuling City, Jilin Province (43°62′N, 124°80′E). Fengqiu County is located in northeastern Henan Province, under the jurisdiction of Xinxiang City, situated in the central part of the Huang-Huai Plain, with a warm temperate continental monsoon climate and an average annual temperature of 13.9℃. The average annual precipitation is 615.1 mm. Yongqiao District is located in the central part of Suzhou City and the northeastern part of Anhui Province, situated on the Huanghuai Plain. It has a warm temperate semi-humid monsoon climate with an average annual temperature of 14.4℃ and an average annual precipitation of 857.1mm. Hailun City is located in the northern part of Suihua City and the central part of Heilongjiang Province, situated in the northeastern part of the Songnen Plain. It has a mid-temperate continental monsoon climate with an average annual temperature of 2.5℃ and an average annual precipitation of 544mm. Gongzhuling City is located in the central and western part of Jilin Province, situated in the middle reaches of the Dongliao River. It has a mid-temperate continental monsoon climate with an average annual temperature of 5.6℃ and an average annual precipitation of 594.8mm. The alluvial soil has a clay content of 19.5%, an organic matter content of 1.41%, and an iron oxide content of Fe. x O y The content is 1.18%; the clay content of sandy black soil is 35%, the organic matter content is 16.76%, and the iron oxide content is 0.9%; the texture of Hailun and Gongzhuling black soils is similar, with a clay content of 37%, an organic matter content of 5.5% in Hailun and 22% in Gongzhuling, and an iron oxide content of no more than 1.5% in both.

[0051] Four treatments were set up for alluvial soil by controlling the amount of biochar applied. Four treatments were set up for sandy black soil by controlling whether straw was returned to the field, the type of soil conditioner, and the tillage method. Two treatments were set up for black soil: mechanical compaction and no compaction (see Table 3 for details). The inner diameter of the MRI probe is 30mm. The ring cutter is made of custom-made PVC pipe. Since there are no PVC pipes with an outer diameter of 30mm on the market, a PVC ring cutter with a height of 50mm and an outer diameter of 25mm was customized to collect undisturbed soil samples for low-field MRI testing to best match the probe.

[0052] Table 3. Different treatments of the three tested soils

[0053]

[0054] The NMR analyzer system used in this experiment measured the low-field nuclear magnetic resonance T2 distribution spectrum of soil. The probe inner diameter was 30 mm, the effective monitoring area height was 50 mm, the magnet frequency was 22 MHz, and the dead time was 23 μs. The instrument used a CPMG pulse sequence, and the signal amplitude was determined by the first echo of the CPMG. The echo interval (T...) E The pulse width was 0.08 ms. When testing black soil and red soil, the pulse widths at 90° and 180° were 7.68 μs and 15.16 μs, respectively; when testing alluvial soil, the pulse widths at 90° and 180° were 15.24 μs and 30.48 μs, respectively.

[0055] Before NMR testing, the undisturbed soil sample collected by the ring cutter method was wrapped around the bottom of the ring cutter with two layers of circular filter paper with a diameter of 5 cm, and the filter paper was fixed with a rubber band. The wrapped ring cutter sample was then soaked until saturated. During NMR testing, the test results are optimal when the ring cutter wall is in close contact with the probe; therefore, the filter paper at the bottom of the ring cutter was gently removed first, and then the ring cutter sample was placed into a glass tube with an outer diameter of 30 mm for testing. During the experiment, the soil sample was placed into the probe inside the monitoring chamber, and the test parameters such as gain were calibrated before the NMR test was performed. After the measurement was completed, the instrument acquired the relaxation information of each sample, i.e., the decay curve of the transverse NMR signal intensity over time. The transverse relaxation time T2 distribution spectrum was obtained through inverse Laplace transform. Then, according to steps 4-6 in the technical solution, the low-field NMR T2 distribution spectrum of the three soil types at saturation was converted into the soil equivalent pore size distribution curve, i.e., the low-field NMR signal intensity H on the vertical axis was converted into soil volumetric water content, and the relaxation time τ on the horizontal axis was converted into soil equivalent pore size r. The specific process is as follows:

[0056] Step 4: Based on the soil clay, paramagnetic iron oxide, and soil organic matter content in Table 2, select the corresponding quantitative relationship between low-field NMR signal intensity H and soil volumetric water content θ in Table 1, and convert the NMR signal intensity H on the vertical axis into soil volumetric water content θ. Figure 2 (b) For example: Black soil is taken from a semi-humid region, with a clay content greater than 35%, a paramagnetic iron oxide content less than 1.5%, and an organic matter content greater than 3%. Therefore, the conversion relationship H = 3.38·θ corresponding to high organic matter soils in semi-humid regions is selected. Alluvial soil is taken from a semi-humid region, with a clay content less than 35%, a paramagnetic iron oxide content less than 1.5%, and an organic matter content less than 3%. Therefore, the conversion relationship H = 3.67·θ corresponding to low organic matter soils in semi-humid regions is selected. Sandy black soil is taken from a semi-humid region, with a clay content of 35%, a high degree of ferroaluminization, and a paramagnetic iron oxide content as high as 4.03%, far greater than 1.5%. Therefore, the conversion relationship H = 0.24·θ corresponding to high weathered ferroaluminate soils in humid regions is selected. 1.67 .

[0057] Step 5: Based on the climatic characteristics of the soil region and the soil organic matter content in Table 2, select an appropriate quantitative relationship between relaxation time τ and matrix suction s. Figure 2 c and Figure 2 d) First, convert the relaxation time τ on the horizontal axis into matrix suction s. For example, the Gongzhuling black soil is taken from a semi-humid area with an organic matter content greater than 3%, therefore, the conversion relationship corresponding to high organic matter soils in a semi-humid area is selected. Gongzhuling black soil, Henan alluvial soil, and sandy ginger black soil were taken from a semi-humid region, with an organic matter content of less than 3%. Therefore, the conversion relationship corresponding to low organic matter soils in a semi-humid region was selected.

[0058] Step 6: Calculate the surface tension coefficient based on the water temperature t and the formula σ = 75.796 - 0.145 * t - 0.00024 * t^2. For example, at t = 20℃, σ = 72.8 mN / m. Then, using the quantitative relationship r = 2σ / s, the matrix suction s on the horizontal axis is further converted into the equivalent soil pore size r. This transforms the T2 distribution spectra of low-field nuclear magnetic resonance at saturation for four soil types into the equivalent soil pore size distribution curve, which is the relationship curve between the water content and pore size of the current pore size. Figure 5 ).

[0059] 2. Experimental Results

[0060] Long-term, high-intensity planting, topsoil compaction, and structural degradation are among the main problems facing alluvial soils. Biochar has great potential to improve soil structure and enhance carbon sequestration efficiency, and is one of the potential measures for improving the structure of alluvial soils. Figure 5 As shown in Figure a, compared to the FS-1 treatment of alluvial soil without biochar application, the equivalent pore distribution of the soil treated with biochar application (FS-(2-4)) changed significantly, and the change was more pronounced with increasing biochar application. Biochar increased the pore size of the largest equivalent pore in the soil, while having little effect on the smallest equivalent pore. This result implies that biochar application increased the largest pore size of the alluvial soil, increased the water content at both large and small pores, changed the pore size distribution of the soil, and greatly improved the soil pore structure. This is consistent with the conclusions of Liu et al. (2014) and Wei Yongxia et al. (2022), indicating that low-field NMR signals can sensitively and accurately capture information on changes in the pore structure of alluvial soil.

[0061] The main structural problems of sandy loam black soil are its stiffness when dry and its cracking when wet, which seriously affect agricultural production. Returning straw to the field, applying biochar and fly ash, and deep plowing are the main measures to improve the structure of sandy loam black soil. Figure 5As shown in b, compared to treatment SJ-1 without wheat and corn straw, treatment SJ-2 with added wheat and corn straw increased the moisture content in both large and small pores and improved the pore size distribution. Biochar treatment SJ-3 was more effective than fly ash treatment SJ-2 in improving soil pore size distribution. Rotary tillage treatment SJ-2 altered the topsoil pore distribution, especially the pore size distribution in large pores, more significantly than deep plowing treatment SJ-4. These results are consistent with findings from other methods, indicating that low-field NMR signals can sensitively and accurately capture changes in the pore structure of sandy loam black soil.

[0062] Black soil is considered the "giant panda" of my country's arable land, but large-scale agricultural planting and mechanized operations accelerate the decomposition of soil organic matter, leading to soil compaction and increasing the risk of black soil degradation. Studying the response of soil structure to mechanical compaction and mitigating black soil compaction is one of the key tasks for protecting and utilizing black soil effectively. The black soils of Hailun and Gongzhuling represent deep and thin layers of black soil, respectively, and are highly representative. Figure 5 The results from the CD analysis show that mechanical compaction significantly altered the pore size distribution of the black soil in Hailun and Gongzhuling to varying degrees, with a decrease in macropores, an increase in micropores, and a reduction in total porosity. This result aligns with current understanding of the effects of mechanical compaction, indicating that low-field NMR signals can effectively respond to this change. This invention can accurately capture changes in the pore structure of black soil.

Claims

1. A method for quantifying soil equivalent pore size distribution based on low-field nuclear magnetic resonance, characterized by The method comprises the following steps: Step 1, collecting soil samples by using a non-metallic ring knife; Step 2, measuring the decay curve of the transverse nuclear magnetic resonance signal intensity of the saturated soil sample with time by using a low-field nuclear magnetic resonance instrument with a frequency of 10-22 MHz; Step 3, the NMR signal intensity H and relaxation time of water in different size soil pores are interpreted from the transverse NMR signal decay curve by inverse Laplace transform numerical inversion method Step 4, converting the nuclear magnetic signal intensity H into the soil volume water content θ by using the quantitative relationship between the nuclear magnetic signal intensity H and the soil volume water content θ; , to obtain the T2 spectrum of low-field NMR; Step 6, converting the matrix suction s into the soil equivalent pore size r by using the quantitative relationship r = 2σ / s between the matrix suction s and the pore equivalent radius r, wherein σ is the surface tension coefficient of water. Step 5, using relaxation time The material of the ring knife in step 1 is PVC or quartz tube. Quantitative relationship with substrate attraction s, converting relaxation time The measuring probe of the low-field nuclear magnetic resonance instrument used in step 2 has an inner diameter of 30 mm, an effective monitoring area of 50 mm in height, a magnet frequency of 22 MHz, a dead time of 23 μs, adopts a CPMG pulse sequence, and the signal amplitude is determined by the first echo of CPMG with an echo interval of 0.08 ms. to substrate attraction s; In step 5, wherein the quantitative relationship between the NMR signal intensity and the soil water content is defined as H = m•θ for soils with a clay content > 35% and a paramagnetic material content > 1.5% in step 4 n and H = m•θ for the remaining soils, wherein θ is the soil water content, H is the soil NMR signal intensity, and m and n are empirical coefficients; The quantitative relationship between the relaxation time and the matrix suction in step 5 is a double exponential function , plus a lateral and longitudinal translation, wherein, s is the matrix suction, ​ is the relaxation time, A1, A2, B1 and B2 are empirical coefficients, and the quantitative relationship between the relaxation time and the matrix suction is a general double exponential function.

2. The method for quantifying soil equivalent pore size distribution based on low-field nuclear magnetic resonance according to claim 1, characterized in that: ​ 3. The method for quantifying soil equivalent pore size distribution based on low-field nuclear magnetic resonance according to claim 1, characterized in that: ​ 4. The method for quantifying soil equivalent pore size distribution based on low-field nuclear magnetic resonance according to claim 1, characterized in that: For the humid zone highly weathered iron-aluminum soil with clay content > 35% and paramagnetic substance content > 1.5%, the quantitative relationship between the nuclear magnetic signal intensity and the soil water content is ; For the arid region soil with paramagnetic substance content ≤ 1.5% or clay content <= 35%, the quantitative relationship between the nuclear magnetic signal intensity and the soil water content is ; For semi-humid region low organic matter soil with paramagnetic substance content ≤ 1.5% or clay content <= 35%, the quantitative relationship between the nuclear magnetic signal intensity and the soil water content is , wherein the low organic matter soil refers to SOM < 3%, and SOM is the content of organic matter in the soil. For semi-humid region high organic matter soil with paramagnetic substance content ≤ 1.5% or clay content ≤ 35%, the quantitative relationship between the nuclear magnetic signal intensity and the soil water content is , wherein the high organic matter soil refers to SOM≥3%.

5. The method for quantifying soil equivalent pore size distribution based on low-field nuclear magnetic resonance according to claim 1, characterized in that: ​ For arid zone soils, the conversion formula is ; For the low organic matter soil in semi-humid region with SOM < 3%, the conversion formula is ; For the semi-humid region with SOM≥3% of high organic matter soil, the conversion formula is ; For the moist zone highly weathered iron-aluminum soil, the conversion formula is .

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