Soil structure degradation quantification method based on soil pore parameters and hydrological functions

Abstract

The invention discloses a soil structure degradation quantification method based on soil pore parameters and hydrological functions, relates to the technical field of farmland soil degradation analysis, and aims to solve the problem that degradation characterization is one-sided due to the fact that a traditional evaluation method only depends on a single physical or hydraulic index. The method comprises the following steps: sampling soil; utilizing CT scanning and image analysis to obtain soil pore structure parameters; parameters reflecting the hydrological function of the soil are obtained; obtaining a farmland soil degradation value by adopting the Pearson correlation coefficient and the soil pore structure parameter and the soil hydrological function parameter obtained by redundancy analysis; and setting a farmland soil structure degradation quantification grade, and comparing an actually measured farmland soil degradation value with a natural forest land or grassland so as to obtain a specific quantification grade of the farmland soil structure degradation. According to the method, the three-dimensional pore morphological parameters obtained through high-resolution CT scanning and the dynamic hydrological function indexes are subjected to coupling analysis, and the soil structure degradation degree can be accurately represented.

Description

Technical Field

[0001] This invention relates to the field of farmland soil degradation analysis technology, specifically to a method for quantifying soil structure degradation based on soil pore parameters and hydrological functions. Background Technology

[0002] Soil structure consists of two parts: soil particles and pores. It serves as the habitat for soil organisms and also as the storage space and transport channel for soil moisture and nutrients, making it a key factor affecting soil quality and productivity. However, high-intensity intensive production, such as excessive soil disturbance and frequent mechanical operations, has led to soil structure degradation, a widespread phenomenon that has become a significant factor in soil quality decline.

[0003] Soil structure directly regulates hydrological processes such as soil water infiltration, storage, and transport through the geometry of the pore system (porosity, pore size distribution, connectivity, etc.). Conversely, the dynamic changes in hydrological function reflect the integrity of the pore system. These two aspects constitute a "structure-function" coupled feedback mechanism, which is the core dimension characterizing soil quality degradation. Current soil degradation research faces two major technical bottlenecks: first, it often focuses on single pore parameters (such as porosity alone) or isolated hydrological indicators (such as soil moisture content alone), neglecting the synergistic relationship between the two, leading to a one-sided characterization of degradation; second, it lacks analytical methods for quantitatively coupling pore structure parameters with hydrological function parameters, making it impossible to accurately quantify the contribution of structural deterioration to functional decline, thus failing to meet the technical requirements for graded remediation of farmland soil degradation. Therefore, establishing a quantitative method for soil structure degradation based on the pore-hydrological synergistic mechanism is crucial to overcoming existing technological limitations and improving the accuracy of soil degradation diagnosis.

[0004] Therefore, there is an urgent need to provide a quantitative method for soil structure degradation based on soil pore structure parameters and hydrological functions. Compared with existing technologies, this method can accurately characterize the degree of soil structure degradation by combining soil pore structure parameters and hydrological functions. Summary of the Invention

[0005] This invention addresses the technical problems existing in the prior art. It provides a quantitative method for soil structure degradation based on soil pore parameters and hydrological functions, breaking through the technical limitations of traditional single-parameter characterization of soil degradation. It constructs a quantitative analysis system that coordinates pore and hydrology, providing a new technical path for the accurate diagnosis and restoration of farmland soil degradation.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for quantifying soil structure degradation based on soil pore parameters and hydrological functions includes the following steps: S1. Conduct soil sampling; S2. Based on the soil sample obtained in step S1, obtain the soil pore structure parameters; the soil pore structure parameters include soil porosity, pore size and shape parameters, pore distribution and connectivity parameters; S3. Based on the soil samples from step S1, obtain parameters reflecting soil hydrological function; S4. Using the soil pore structure parameters obtained in step S2 and the soil hydrological function parameters obtained in step S3, the soil degradation value reflecting the farmland soil is obtained. A quantitative level of farmland soil structure degradation is set, and the actual measured farmland soil degradation value is compared with that of natural forest or grassland to obtain the specific quantitative level of farmland soil structure degradation.

[0007] Based on the above technical solution, further, in S1, the sampling process is as follows: using a ring cutter to collect undisturbed soil samples from 0cm to 40cm, randomly extracting 3 soil samples from each plot, the 3 soil samples randomly extracted from each plot are respectively from the 0-10cm position, the 10-20cm position, and the 20-40cm position of that plot, and then mixing the 3 soil samples extracted from each plot.

[0008] Based on the above technical solution, further, in S3, the parameters reflecting soil hydrological function include soil water storage, minimum soil moisture limit range, crop water availability value (PAW), soil moisture characteristic curve, average soil weight diameter (MWD), S-index, and penetration resistance (PR).

[0009] Based on the above technical solution, the calculation process for the soil water storage capacity is as follows: Where SWS is soil water storage capacity, in mm; θ is soil mass moisture content, in %; and BD is soil bulk density, in g / cm³. -3 ρ is the density of water, with units of g / cm³. -3 H represents soil depth, in mm.

[0010] Based on the above technical solution, the calculation process for the minimum soil moisture limit range is as follows: ; ; in, This refers to the volumetric water content, expressed in cm³. 3 cm -3 ; This refers to the saturated volumetric water content, expressed in cm³. 3 cm -3 ; Residual volumetric water content, in cm³ 3 cm -3 ; Soil matrix potential; , n, and m are curve fitting parameters.

[0011] Based on the above technical solution, the S-index is further defined as the slope at the inflection point of the soil moisture characteristic curve, used to characterize soil structural strength. S > 0.035 indicates good structure, and S < 0.02 indicates severe degradation. Its calculation process is as follows: .

[0012] Based on the above technical solution, the calculation process for the crop effective water value (PAW) is as follows: ; in, This is the field volume under -33 kPa conditions, in cm³. 3 cm -3 ; It is the permanent efflorescence coefficient at -1500 kPa, with units of cm. 3 cm -3 .

[0013] Based on the above technical solution, the calculation process for the penetration resistance PR is as follows: Where PR is the penetration resistance (in MPa), θ is the soil moisture content (in %), and a and b are the model fitting parameters.

[0014] Based on the above technical solution, the calculation process for the soil mean weight diameter (MWD) is as follows: ; Where, x i It is the average diameter of particles within each particle size range, in mm; w i q represents the proportion of each aggregate graded particle in the entire soil; q is the number of aggregate grades.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention is the first to couple and analyze the three-dimensional pore morphology parameters (such as fractal dimension and connectivity density) obtained by high-resolution CT scanning with dynamic hydrological function indicators, revealing the influence mechanism of microstructure on macro function and accurately characterizing the degree of soil structure degradation. (2) The present invention constructs a degradation distance index D based on RDA, which overcomes the subjective defects of the traditional linear weighted scoring method and realizes the objective quantification of the degree of degradation; (3) The present invention proposes a universal degradation grading system applicable to different land use types, which has good universality and promotion prospects. Attached Figure Description

[0016] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0018] like Figure 1 As shown, this invention provides a method for quantifying soil structure degradation based on soil pore parameters and hydrological functions, comprising the following steps: S1. Conduct soil sampling; Specifically, the sampling process is as follows: Undisturbed soil samples are collected from 0cm to 40cm using a ring cutter. Three soil samples are randomly extracted from each plot. The three soil samples randomly extracted from each plot are from the 0-10cm, 10-20cm, and 20-40cm positions of that plot, respectively. Then, the three soil samples extracted from each plot are mixed. Specifically, the "S" shaped sampling method can be used to sample and mix them evenly.

[0019] In this embodiment, to ensure sampling uniformity, an "S"-shaped sampling method was used for sampling and homogenization, resulting in a total of 72 soil samples (4 treatments × 2 locations × 3 soil layers × 3 replicates). These 72 soil samples were then divided into three categories. Two of these categories were air-dried, ground, and sieved using different sieves. One of these two categories (Category 1 soil) was homogenized and broken into small pieces, then passed through an 8mm sieve for wet sieving of aggregates. The other category (Category 2 soil) was ground and passed through a 0.15mm sieve for measuring SOC and TN content. The third category of soil was selected to form aggregates of 5-8mm for subsequent CT scans.

[0020] All undisturbed soil samples were stored in a foam-filled box at 4°C to avoid damaging the soil pore structure.

[0021] S2. Based on the soil sample obtained in step S1, obtain the soil pore structure parameters, which include the soil porosity, pore size and shape parameters, pore distribution and connectivity parameters. Specifically, the porosity, pore size and shape parameters, pore distribution and connectivity parameters are obtained by performing CT scanning and image analysis on the third type of soil sample in step S1.

[0022] Specifically, a "stratified-randomized-repeated" aggregate screening strategy was adopted for the third type of soil samples. Three 5-8 mm aggregate samples were randomly selected from each soil layer (0-10 cm, 10-20 cm, 20-40 cm) (ensuring that the aggregates were undamaged and without cracks), for a total of 36 aggregate samples. High-resolution desktop micro-computed tomography (Skyscan-1172; Skyscan, Contige, Belgium) was used for scanning. The scanning parameters were innovatively optimized: for the different soil density differences in different soil layers, a tube voltage of 100 kV and a tube current of 90 μA were used for the 0-10 cm soil layer; and a tube voltage of 100 kV and a tube current of 100 μA were used for the 10-20 cm and 20-40 cm soil layers. The uniform scanning resolution was 9 μm, and three scans were repeated (to reduce instrument error), with a 10-minute interval between each scan (to avoid sample heating affecting the pore structure). Finally, 900 high-quality CT images were obtained, improving the accuracy and repeatability of pore parameter extraction.

[0023] ImageJ software was then used to process the image. A region of interest (ROI) of 397×397×397um was selected from the center of the sample image to avoid interference with the boundary region during sampling. The image segmentation of the original grayscale slices has a significant impact on the subsequent structural analysis. Therefore, the 2D image was imported into ImageJ software for preprocessing image segmentation. The specific processing steps included: (1) normalization to eliminate the brightness difference between different CT slice images; (2) speckle removal to eliminate image noise; and (3) median filtering to improve the image contrast of porous and non-porous parts.

[0024] To better distinguish between soil and pores, the grayscale image was processed using threshold segmentation, which means dividing the grayscale image into two parts by adjusting the threshold. Due to limited resolution, only pores larger than 8.95 mm were identified and studied. Specifically, the threshold was manually adjusted based on visual observation to ensure complete separation of the soil matrix and pores.

[0025] Porosity and pore size were specifically calculated using the 3d object counter plugin in ImageJ.

[0026] Pore ​​size distribution (PSD) can be classified into four levels based on equivalent diameter: micropores (P<50μm), mesopores (50≤P<150μm), macropores (150≤P<300μm), and extra-large pores (P>300μm). Based on the pore shape factor (F), it can be classified as elongated (F<0.2), regular (F>0.5), or irregular (0.2≤F<0.5).

[0027] Pore ​​morphology parameters (3D fractal dimension, roundness, and connectivity) were determined using the BongJ plugin. The 3D fractal dimension (FD) reflects the tortuosity or complexity of the geometry; a larger FD indicates a more complex pore structure. Pore roundness is represented by anisotropy (DA); a value closer to 0 indicates a more circular pore shape. Connectivity is calculated based on the connectivity density (CD) in the plugin; a higher value indicates greater soil pore connectivity.

[0028] The pore size of the soil is calculated using the following formula: ;in, ρ is the pore size of the soil (μm), and v is the surface tension of the water within the pores (72.8 gs). -2 ρ is the density of water (0.998 g / cm³). -3 g is the acceleration due to gravity (980 cm / s²). -2 ω is the contact angle between water and soil (ω≈0); h (Pressure Head) represents the pressure head (m).

[0029] S3. Based on the soil samples from step S1, parameters reflecting soil hydrological function are obtained. These parameters mainly include soil water storage, minimum soil moisture limit, crop effective water value, soil moisture characteristic curve, S-index, and penetration resistance.

[0030] (1) Soil water storage capacity is specifically calculated using the following formula: Where SWS is soil water storage (mm), θ is soil moisture content (%), and BD is soil bulk density (g / cm³). -3 ρ is the density of water (g / cm³). -3 H is the soil depth (mm).

[0031] (2) The minimum soil moisture limit range was obtained by the following method: The minimum moisture limit range (LLWR) is determined by measuring the upper and lower limits of soil moisture content for normal crop growth. The upper limit is the soil moisture content at an air-filled porosity of 10%. (or field water holding capacity) This indicates that when the proportion of macropores is less than 10%, gas diffusion is limited, and root respiration is inhibited. When soil penetration resistance (PR) exceeds 2 MPa, crop growth is restricted. Therefore, the lower limit of LLWR is the soil moisture content at which PR is 2 MPa. ) or permanent withering coefficient ( Field capacity () Soil matrix potential = -33 kPa) and permanent wilting coefficient ( The soil parent material potential (-1500 kPa) was calculated from the soil moisture characteristic curve (SWRC). It should be noted that the centrifuge method for determining SWRC is acceptable, as the results are similar to those obtained using the pressure plate method. Ring sample soil was measured using a Kohusan H-1400pF centrifuge (Kokusan, Tokyo), with 11 speed levels set: 0, 300, 500, 800, 1300, 1800, 2400, 3300, 5400, 7700, and 10000 rpm, corresponding to matrix potentials from 0 kPa to 1600 kPa (Lietal., 2020). The Van-Genuchten model (GenuchtenVan, 1980) was used to determine SWRC, and the specific calculation formula is as follows: ; ; in, This refers to the volumetric water content, expressed in cm³. 3 cm -3 ; Water content at saturation volume (cm³) 3 cm -3 ), Residual volumetric water content (cm³) 3 cm -3 ), Soil matrix potential; , n, and m are curve fitting parameters.

[0032] Soil moisture content when the porosity is 10% (%,%) is derived from the following empirical formula: ; in, Particle density (g / cm³) -3 BD is the bulk density (g / cm³). -3 ).

[0033] (3) The crop effective water value (PAW) is specifically calculated using the following formula: ; in, Field volume (cm³) under -33 kPa conditions 3 cm -3 ), It is the permanent wilting coefficient at -1500 kPa (cm). 3 cm -3 ).

[0034] (4) To determine the soil penetration resistance (PR) curve, undisturbed soil samples from each plot were placed on a pressure plate and pressures of 2, 10, 60, 100, 500, and 1000 kPa were applied. PR and soil moisture content were measured while the weight of these samples remained constant. PR was measured using a miniature penetration resistance meter (Omega LC703, USA), with a cone diameter of 2 mm and an angle of 15°. The cone was inserted into the soil at a speed of 10 mm / min. The soil penetration resistance model proposed by Mielke et al. (1994) was used to establish a functional relationship between PR and θ for each treatment, where the penetration resistance PR was calculated by the following formula: ; Where PR is the penetration resistance (MPa), θ is the soil mass water content, and a and b are the model fitting parameters.

[0035] In this embodiment, according to , , and There are four possibilities for calculating the LLWR value (Liet al., 2020), among which, Soil moisture content; if ≥ and ≤ Then LLWR= - ; if ≥ and ≥ Then LLWR= - ; if ≤ and ≤ Then LLWR= - ; if ≤ and ≥ Then LLWR= - .

[0036] (5) The soil mean weight diameter (MWD) can be calculated using the following formula: ; where x i It is the average diameter (mm) of particles within each particle size range, w iIt represents the proportion of each aggregate graded particle in the entire soil, and q is the number of aggregate grades.

[0037] (6) The soil moisture characteristic curve is obtained through the following methods: Centrifugation is a suitable method for measuring SWRC because it yields results similar to the pressure plate method but takes less time (Reatto, 2008). However, the centrifugation method has a wider matric potential range compared to the pressure plate method (Shukla et al., 2004). Undamaged soil samples were measured using a Kohusan H-1400pF centrifuge (Kokusan Corp.). Eleven rotation speeds were set: 0, 300, 500, 800, 1300, 1800, 2400, 3300, 5400, 7700, and 10000 rpm, corresponding to different pressures from 0 to 1600 kPa. Two running times were set (60 minutes for each speed range of 300–2400 rpm, and 90 minutes for 3300–10000 rpm). The weight and height of the sample were recorded after each rotation speed was reached, and then higher speeds were performed.

[0038] The matrix potential h1 is calculated using the following formula, in kPa: ; In the formula, k is equal to 0.098 kPacm. -1 The constant, ω1 is the angular velocity (rads) -1 L is the soil sample height (cm), and g is the gravitational acceleration (980cm / s²). -2 ), Where h is the outer radius of the centrifuge (8.3 cm). i The height decreases during each rotational speed.

[0039] The relationship between soil volumetric water content and soil parent material potential (SWRC) is determined by the following model (GenuchtenVan, 1980): ; .

[0040] (7) The S-index is the slope at the inflection point of the soil moisture characteristic curve, used to characterize the soil structural strength. S>0.035 indicates good structure, and S<0.02 indicates severe degradation. It is calculated based on the slope at the inflection point of the SWRC curve: .

[0041] S4. Using the soil pore structure parameters obtained in step S2 and the soil hydrological function parameters obtained in step S3, the soil degradation value reflecting the farmland soil is obtained. A quantitative level of farmland soil structure degradation is set. The actual measured farmland soil degradation value is compared with that of natural forest or grassland to obtain the specific quantitative level of farmland soil structure degradation.

[0042] In this embodiment, the specific process of S4 is as follows: A three-level quantitative analysis framework of "Pearson correlation screening - principal component dimensionality reduction - redundancy analysis coupling" is adopted: First, the core pore structure parameters related to hydrological functions were screened using Pearson correlation coefficient (redundant parameters were removed, and key indicators with a contribution rate of ≥85% were retained) and core hydrological function parameters that were significantly related to pore structure. Secondly, principal component analysis (PCA) was performed on the two types of core parameters to extract principal components with eigenvalues ​​≥1, reducing data dimensionality and eliminating multicollinearity. Finally, redundancy analysis (RDA) was performed using the hydrological function principal component score as the response variable and the pore structure principal component score as the explanatory variable. The Euclidean distance between the sample point in the RDA ordination diagram and the "pore-hydrological optimal coupling reference point" (determined based on baseline data of different soil types and suitable crop growth thresholds; preferably, the coupling parameters of soil structure and hydrological function in natural forest or grassland are used as this reference point; if the farmland was reclaimed from forest, natural forest is used as the reference point; if it was reclaimed from grassland, natural grassland is used as the reference point) was calculated. This distance is the soil degradation value (D). Meanwhile, based on the distribution characteristics of degradation values ​​of typical farmland soil samples from different regions across the country, five levels of farmland soil structure degradation were classified (D < 0.8 for no degradation, 0.8 ≤ D < 1.5 for slight degradation, 1.5 ≤ D < 2.2 for moderate degradation, 2.2 ≤ D < 3.0 for severe degradation, and D ≥ 3.0 for extremely severe degradation). Soil degradation values ​​were compared with the classification standards to obtain specific quantitative levels. It should be noted that in the RDA ordination space, the theoretical optimal reference point is set as the principal component coordinates corresponding to the optimal level of various hydrological function indicators under ideal conditions. It should be further noted that this value will vary depending on soil type, crop type, etc., and is not explicitly limited here. Furthermore, the larger the D value, the further the actual hydrological function of the soil deviates from the optimal function supported by its structure, and the more severe the degradation.

[0043] The above analysis procedure was repeated for the collected natural grassland and forest samples. Using the strongly correlated hydrological function and structural indicators identified by correlation and redundancy analysis, soil degradation indices (SDIs) for forest, farmland, and grassland were constructed, respectively. By comparing the differences in SDI values ​​among different land use types, using natural forest or grassland as a benchmark (the specific choice depends on whether farmland was converted from forest or grassland; for example, farmland converted from forest land uses forest land as the benchmark), the degree of farmland soil structure degradation can be further assessed.

[0044] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for quantifying soil structure degradation based on soil pore parameters and hydrological functions, characterized in that, Includes the following steps: S1. Conduct soil sampling; S2. Based on the soil samples obtained in step S1, CT scans and image analysis are used to obtain soil pore structure parameters. Soil pore structure parameters include soil porosity, pore size and shape parameters, pore distribution and connectivity parameters. S3. Based on the soil samples from step S1, obtain parameters reflecting soil hydrological function; S4. Using the soil pore structure parameters obtained in step S2 and the soil hydrological function parameters obtained in step S3, the soil degradation value of farmland is obtained. A quantitative level of farmland soil structure degradation is set, and the actual measured farmland soil degradation value is compared with that of natural forest or grassland to obtain the specific quantitative level of farmland soil structure degradation.

2. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 1, characterized in that, In S1, the sampling process is as follows: Undisturbed soil samples are collected from 0cm to 40cm using a ring cutter. Three soil samples are randomly extracted from each plot. The three soil samples randomly extracted from each plot are from the 0-10cm, 10-20cm, and 20-40cm positions of the plot, respectively. Then, the three soil samples extracted from each plot are mixed.

3. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 1, characterized in that, In S3, parameters reflecting soil hydrological function include soil water storage, minimum soil moisture limit, crop water availability (PAW), soil moisture characteristic curve, mean soil mass diameter (MWD), S-index, and penetration resistance (PR).

4. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 3, characterized in that, The calculation process for the soil water storage is as follows: ； Where SWS is soil water storage capacity, in mm; θ is soil mass water content, in %; and BD is soil bulk density, in g / cm³. -3 ρ is the density of water, with units of g / cm³. -3 H represents soil depth, measured in mm.

5. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 3, characterized in that, The calculation process for the minimum soil moisture limit range is as follows: ； ； in, This refers to the volumetric water content, expressed in cm³. 3 cm -3 ; This refers to the saturated volumetric water content, expressed in cm³. 3 cm -3 ; Residual volumetric water content, in cm³ 3 cm -3 ; Soil matrix potential; , n, and m are curve fitting parameters.

6. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 5, characterized in that, The calculation process for the S-index is as follows: 。 7. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 3, characterized in that, The calculation process for the crop effective water value (PAW) is as follows: ； in, This is the field volume under -33 kPa conditions, in cm³. 3 cm -3 ; It is the permanent efflorescence coefficient at -1500 kPa, with units of cm. 3 cm -3 .

8. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 4, characterized in that, The calculation process for the penetration resistance PR is as follows: ； Where PR is the penetration resistance in MPa; θ is the soil moisture content in %; and a and b are the model fitting parameters.

9. The method for quantifying soil structure degradation based on soil pore parameters and hydrological functions according to claim 3, characterized in that, The calculation process for the soil mean weight diameter (MWD) is as follows: ； Where, x i It is the average diameter of particles within each particle size range, in mm; w i q represents the proportion of each aggregate graded particle in the entire soil; q is the number of aggregate grades.

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