•2D and 3D analyses allowed the soil pore system characterization.•Tri-modal pore size distributions were found for soil under CT and NT.•For CT, the greatest contribution to AP is given by pores of ...round shape.•For NT, the greatest contribution to AP is given by large complex pore types.•A better pore connectivity was found for the 0–10cm layer for soil under NT.
Structure represents one of the main soil physical attributes indicators. The soil porous system (SPS) is directly linked to the soil structure. Water retention, movement, root development, gas diffusion and the conditions for all soil biota are related to the SPS. Studies about the influence of tillage systems in the soil structure are important to evaluate their impact in the soil quality. This paper deals with a detailed analysis of changes in the soil structure induced by conventional (CT) and no-tillage (NT) systems. Three different soil depths were studied (0–10, 10–20 and 20–30cm). Data of the soil water retention curve (SWRC), micromorphologic (impregnated blocks) (2D) and microtomographic (μCT) (3D) analyses were utilized to characterize the SPS. Such analyses enabled the investigation of porous system attributes such as: porosity, pore number and shape, pore size distribution, tortuosity and connectivity. Results from this study show a tri-modal pore size distribution (PSD) at depths 0–10 and 10–20cm for the soil under CT and a bi-modal PSD for the lower layer (20–30cm). Regarding the soil under NT, tri-modal PSDs were found at the three depths analyzed. Results based on the micromorphologic analysis (2D) showed that the greatest contribution to areal porosity (AP) is given by pores of round (R) shape for CT (52%: 0–10cm; 50%: 10–20cm; 67%: 20–30cm). Contrary to the results observed for CT, the soil under NT system gave the greatest contribution to AP, for the upper (0–10cm) and intermediate (10–20cm) layers, due to the large complex (C) pore types. For the μCT analysis, several types of pores were identified for each soil tillage system. Small differences in the macroporosity (MAP) were observed for the 0–10 and 20–30cm between CT and NT. A better pore connectivity was found for the 0–10cm layer under NT.
Since many processes in soil are highly sensitive to soil structure, this review intends to evaluate the potential of observable soil structural attributes to be used in the assessment of soil ...functions. We focus on the biomass production, storage and filtering of water, storage and recycling of nutrients, carbon storage, habitat for biological activity, and physical stability and support. A selection of frequently used soil structural properties are analyzed and discussed from a methodological point of view and with respect to their relevance to soil functions. These are properties extracted from soil profile description, visual soil assessment, aggregate size and stability analysis, bulk density, mercury porosimetry, water retention curve, gas adsorption, and imaging techniques. We highlight the greater relevance of the pore network characterization as compared to the aggregate perspective. We identify porosity, macroporosity, pore distances, and pore connectivity derived from imaging techniques as being the most relevant indicators for several soil functions. Since imaging techniques are not widely accessible, we suggest using this technique to build up an open access “soil structure library” for a large range of soil types, which could form the basis to relate more easily available measures to pore structural attributes in a site-specific way (i.e., taking into account texture, soil organic matter content, etc.).
•Structural properties are discussed with respect to their relevance to soil functions.•Pore network characterization is more powerful than analyzing disturbed aggregates.•We identified porosity, macroporosity, pore distances, and pore connectivity.•Imaging instruments appeared to be the most reliable tools to measure them.•We suggest developing an open access “soil structure library”.
•Void ratio is a major factor that affects the hydraulic properties.•A method to normalize the SWRCs with different void ratios is proposed.•A simple method to simulate the hydraulic properties is ...developed.
Reliable estimates of the unsaturated soil hydraulic properties are needed in many research and engineering projects. The void ratio or bulk density is an important factor affecting the unsaturated soil hydraulic properties. The bulk density of one soil can change considerably due to the influences of rain, irrigation, and traffic compaction. It remains a difficult task to accurately describe the hydraulic hysteresis of the unsaturated soil with different void ratios or bulk densities. The aim of this study was to evaluate hydraulic hysteresis behavior and permeability of unsaturated soil with different void ratios or bulk densities based on the normalized soil water retention curves (SWRCs) method. After the normalization, the normalized main drying and wetting SWRCs are independent of the void ratio or bulk density. The hysteresis behavior between the normalized main drying and wetting SWRCs can be described by referring to the existing void ratio independent hysteresis model. Additionally, a simple estimation method to simulate the effects of the void ratio or bulk density on the relative permeability coefficient of unsaturated soils is proposed. The approach proposed here requires no additional parameters. The results show that the proposed hysteresis model can be used to describe the arbitrary main drying, wetting, and scanning curves at arbitrary void ratios over a wide suction range, and the predictions for the relative permeability coefficient with different void ratios by the proposed permeability model can match the experimental data well.
The experimental measurement of water retention curve in hydrate‐bearing sediments is critically important to understand the behavior of hydrate dissociation and gas production. In this study, ...tetrahydrofuran (THF) is selected as hydrate former. The pore habit of THF hydrates is investigated by visual observation in a transparent micromodel. It is confirmed that THF hydrates are not wetting phase on the quartz surface of the micromodel and occupy either an entire pore or part of pore space resulting in change in pore size distribution. And the measurement of water retention curves in THF hydrate‐bearing sediments with hydrate saturation ranging from Sh = 0 to Sh = 0.7 is conducted for excess water condition. The experimental results show that the gas entry pressure and the capillary pressure increase with increasing hydrate saturation. Based on the experimental results, fitting parameters for van Genuchten equation are suggested for different hydrate saturation conditions.
Key Points
THF hydrate is a nonwetting phase on the quartz grain surface with the existence of water
Capillary pressure and gas entry pressure of THF hydrate‐bearing sediments increase with increasing hydrate saturation
The m value governing the shape of water retention curve decreases with increasing hydrate saturation
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•CoreVESS Sq improved predictive ability of PTFs when replacing bulk density.•Soil strength, easily measured in the field, can enhance PTFs prediction accuracy.•Point PTFs performed ...better than Parametric PTFs.•KNN method provided the best predictive performance in this study.•Grouping the datasets improved the predictive ability of PTFs.
Soil hydraulic properties, such as the soil–water retention curve (SWRC), play a crucial role in simulating water transport within the vadose zone. They can be directly measured in the laboratory or field, or indirectly predicted by using Pedotransfer Functions (PTFs). It has been advocated that accounting for soil structure could marginally improve the prediction accuracy of PTFs in its wet range. The aim of this study was to test whether the use of an easy-to-determine soil structure-related variable could effectively increase the prediction accuracy of water retention curve PTFs. Additionally, we explored whether including soil strength, another soil property that is easy and quickly to determine in the field in many replicates, could improve PTF performance. Our investigation involved extensive sampling of 252 soil horizons across 42 cropped fields, each exhibiting within-field variations in soil structural degradation. Soil structure was represented by a soil structural quality score (Sq) taken from a semi-quantitative visual soil assessment (CoreVESS), which was included in the PTFs as predictor variable or as discriminator (Sq) for data grouping in addition to or instead of ‘classical’ predictors such as soil organic carbon content, clay and sand content, bulk density and soil layer. Penetration resistance (PR) was taken as a variable for soil strength. Various regression methods from classical regression to machine learning were evaluated on Train and Test subdatasets. To evaluate the effect of data grouping, the dataset was split in two based on structure and on texture. Both point and parametric PTFs were developed, with the latter predicting the parameters of the Van Genuchten (VG) water retention equation. Overall, the k-nearest neighbors PTFs (KNN-PTFs) achieved the best performance showing the highest R2 and lowest RMSE values. Moreover, the point PTFs showed much better and more stable predictive ability than parametric PTFs. The inclusion of PR as an additional predictor variable slightly improved the prediction performance in the wet range of the SWRC. Interestingly, Sq proved beneficial when substituted for bulk density but not when used in addition to it. Grouping data based on texture and structure improved the prediction accuracy of the PTFs, particularly evident in textural grouping and MLR, but not in KNN.
The water retention curve (WRC) of unsaturated soils plays a significant role in evaluating rainfall-induced geohazards in geological and geotechnical engineering, such as ground subsidence and slope ...failure. Stress can affect WRC because loading/unloading alters not only density but also pore size distribution (PSD). Previous studies of stress-dependent WRC focused on soils with mono- and bi-modal PSDs only. In this study, the WRCs of intact paleosol and intact loess with quadri- and tri-modal PSDs were measured using suction- and stress-controlled pressure plate tests. The full-range PSDs of tested specimens were determined by combining X-ray computed tomography (CT) and mercury intrusion porosimetry (MIP). Experimental results show that the multi-modal PSDs and hence WRCs of both soils are strongly affected by stress in a similar approach. For instance, the relationship between degree of hysteresis and suction showed a double-humped pattern, in which the Peak-I and Peak-II were identified at the relatively low (0.1–20 kPa) and high (20–400 kPa) suctions, respectively. The application of stress resulted in a decrease of hysteresis in the Peak-I (about 30%) but an increase in the Peak-II (about 31%). The increase of hysteresis in the Peak-II differs from the behaviour of soils with mono- and bi-modal PSDs, mainly because the reduction of mega- and macro-pore diameters upon loading increases pore non-uniformity in the range corresponding to the Peak-II.
•CT and MIP are combined to characterize the full-range PSDs of two intact soils.•The full-range PSD is crucial for interpreting the WRC of soil with a multi-modal PSD.•Intact paleosol and intact loess show quadri-modal and tri-modal PSDs, respectively.•Stress-dependent PSDs and WRCs of intact paleosol and loess are unique.•Stress enhances and reduces hysteresis in WRC at low and high suctions, respectively.
Hydraulic conductivity curves (HCCs) are important inputs in land surface modeling. The general way for predicting an HCC from a soil water retention curve (SWRC) requires an additional input of the ...saturated hydraulic conductivity. However, the macro effect near saturation often results in difficulty and poor performance when predicting the conductivity. In this paper, we introduce a novel method for predicting the HCC fully from the SWRC, requiring no additional parameters. This is achieved by applying an estimated conductivity (from the SWRC) in the dry range as a new matching point, in addition to modifying an existing HCC model that accounts for both capillary and adsorption forces. Testing with a total of 159 soil samples indicated that the new model substantially improves the prediction of the HCC in compared with the model with the input of the saturated hydraulic conductivity, with the R2 increased from 0.48 to 0.76 and the root‐mean‐square error value reduced from 1.60 to 0.81 cm d−1. The abrupt drop near saturation of the HCC model for soils with small n values close to 1.0, which is a parameter used in shaping the SWRC, was also overcome by forcing the water content be saturated above a fixed potential of −1 cm.
Key Points
A physically based method was provided for predicting hydraulic conductivity curves (HCC) fully from soil water retention curve requiring no additional parameters
The abrupt drop near saturation of the HCC model for soils with small n values was overcome by introducing a non‐zero air‐entry value
The new model significantly improved the predictions of conductivity compared to that requiring the input of saturated conductivity
Soil Water Retention Curve (SWRC) provides crucial information for understanding soil moisture retention, essential for agriculture, hydrology, engineering and environmental science applications. ...Many SWRC fitting models in the literature are based on empirical equations without a direct physical meaning. However, SWRC data is physically related to the soil’s porous structure and its interactions with the wetting fluid. Hence, the curve’s behavior reflects the porous complexity. Non-physical model equations might even be able to fit the data to be used in several applications; however, the search for physically fitting models representing the SWRC data as a smooth continuous distribution function can reflect new insights and information about this heterogeneous porous media. In this regard, the well-established physically-based Kosugi model is based on the assumption of lognormal pore size distributions. However, a general approach for any modality and distribution shape could be interesting. This paper proposes applying the mathematical method known as “Inverse Laplace Transform” (ILT) to fit the Soil Water Retention Curve using a weighted superposition of exponential decays. This multi-exponential approach involves working with two physically related parameters, the amplitude and its respective characteristic matric potential, which are physically interpreted as the amount of pores that empty at that suction head. The ILT-EXP method proposed was implemented in Python software to fit the curves, and it is now available in an online web app. The evaluation of the ILT-EXP model to fit SWRC data is discussed, presenting its potential to estimate soil pore size distribution of multimodal samples. One advantage of ILT-EXP over other multimodal models is that it does not need to know how many modal components are present in the SWRC data, being automatically determined by the method. Finally, a statistical fitting comparison of 439 SWRC data, with six other classical models is discussed. The results indicate that fitting with the ILT-EXP model demonstrates strong potential, making it a powerful method for handling multimodal curves. This approach represents a novel and robust method for estimating a smooth, continuous soil pore size distribution.
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•Inverse Laplace Transform was used to fit the soil water retention curve as a sum of exponential decays.•The ILT-EXP model allows a reliable estimation of multimodal soil pore distribution (PSD).•An online WebApp was developed to perform the ILT-EXP and other classical methods in SWRC data.
Many engineering practices are carried out within the unsaturated soil. Soil-water retention curves (SWRCs) of many soils exhibit bimodal characteristics that significantly affect strength behavior, ...this issue still remains unresolved. This work employs suction stress concept to examine the uniqueness of strength parameters for coarse- and fine-grained unsaturated soils with bimodal SWRCs. Capillary degree of saturation is used to upscale pore-scale suction to macroscopic suction stress. In the suction stress-shear strength plane, both coarse- and fine-grained soils display the bi-linear strength envelope, differing from unsaturated soils with unimodal SWRC.
•The shear strength of unsaturated soils with bimodal water-retention curves are analyzed using suction stress concept.•The influences of soil type on the shear strength of soils with bimodal SWRC are discussed.•The unified strength criterion for soils with bimodal SWRC is manifested by a bi-linear relationship.
•Transient evaporation method was proposed to measure the WRC of structured soils.•Non-invasive TDR probes were developed to allow the measurement of soil water content without penetration.•Compliant ...sampling volume of the TDR and the tensiometer is important to obtain accurate WRC using transient method.
Transient evaporation method is promising for rapid measurement of soil water retention curve (WRC). Existing apparatuses of transient evaporation method are not ideal for measuring the WRC of structured soils because of the sample disturbance induced by invasive water content probes used. In this study, non-invasive TDR probes with different waveguide layouts (i.e., different number of conductors and waveguide length) were developed to measure the WRC of loess during transient evaporation, while the soil suction is recorded through a tensiometer. Results show that the WRCs of undisturbed and remolded loess measured by a three-conductor non-invasive TDR probe are in good agreement with the results of pressure plate tests. The differences in the air entry value (AEV) and desorption rate between the WRCs measured by the transient evaporation method and the pressure plate measurement are less than 10 %. On the other hand, the WRCs measured by a two-conductor non-invasive TDR probe underestimate the water content for a given suction. The AEV of undisturbed and remolded loess determined by the transient evaporation method is 66.7 % and 112.9 % smaller than the results of pressure plate measurements, respectively. The underestimation of the two-conductor non-invasive TDR probe in measuring the WRC of loess can be attributed to the fact that the vertical sampling range of two-conductor non-invasive TDR probe is two times greater than that of the tensiometer. The results in this study show the effectiveness of using the non-invasive TDR probe along with a tensiometer for measuring the WRC. More importantly, great caution should be taken on compliant sampling volume of the non-invasive TDR probe and tensiometer to obtain accurate WRC measurements.
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