Application of X‐ray tomography to quantify macropore characteristics of loess soil under two perennial plants

Abstract

SummaryWith the advent of large-scale restoration of vegetation in the Loess Plateau, northwest China, there has been an increase in concern about the suitability of loess soil to support permanent vegetation cover. The quantification of soil macropore characteristics could be critical in determining the architecture and hydrological processes of loess soil on the plateau. In this research, we compared the effects of Purple alfalfa (Medicago sativa L.) and Korshinsk peashrub (Caragana korshinskii K.) on the macropore characteristics of a soil profile on the plateau with computed tomography (CT). To achieve this, undisturbed cores of soil were excavated from beneath purple alfalfa (ALF), 22-year-old Korshinsk peashrub (KOP 22 ) and 40-year-old Korshinsk peashrub (KOP 40 ) vegetation types in the Liudaogou watershed for evaluation. The soil macropore characteristics (including macroporosity, largest pore area, amounts of macropores, circularity, surface area density, branch density, junction density and connectivity) were determined with image analysis software. Soil under KOP 22 and KOP 40 treatments had approximately the same amounts of macropores (17 per 6359-mm 2 area), which was three times greater than those under ALF plants. Macroporosity ratios of soil under KOP 22 and KOP 40 plants to that under ALF plants were 2.3 and 3.6, respectively. Compared with KOP 22 , KOP 40 had a larger macroporosity and the largest pore area at the 100-300-mm soil depth. The KOP plants, in particular KOP 40 , apparently improved the macropore network structure of the soil more than ALF. However, the macropores under ALF were much rounder at the 100-300-mm soil depth than those under the other two plants. There was no correlation between macropore characteristics and organic matter content of the soil at 100-400-mm depth. Nevertheless, macroporosity was strongly correlated with the largest pore area. The findings of this research are critical for developing strategies for the restoration of vegetation in the Loess Plateau through improvement of the hydrological process of loess soil.

Quantitative evaluation of pore characteristics of sodic soils reclaimed by flue gas desulphurization gypsum using X‐ray computed tomography

“…For example, studies have been widely carried out on segmentation of X‐ray CT images (Baveye et al, ; Iassonov, Gebrenegus, & Tuller, ; Schlüter, Sheppard, Brown, & Wildenschild, ) involving image resolution selection (Sleutel et al, ; Wildenschild et al, ), representative elementary area identification (San José Martínez, Caniego, García‐Gutiérrez, & Espejo, ), and optimal thresholding methods (Elliot & Heck, ; Smet, Plougonven, Leonard, Degré, & Beckers, ; Wang, Kravchenko, Smucker, & Rivers, ); quantification and reconstruction of the pore structure (Marcelino, Cnudde, Vansteelandt, & Carò, ) such as characterization of macropores (Garbout, Munkholm, & Hansen, ; Luo, Lin, & Schmidt, ), extraction of three‐dimensional (3D) typical pore parameters (Al‐Raoush & Willson, ; Luo, Lin, & Li, ), and assessing the spatial variability of soil structure (Carducci, Zinn, Rossoni, Heck, & Oliveira, ); as well as the relationship between pore characteristics and soil functions (Helliwell et al, ) including correlations with soil physical properties (Anderson, Gantzer, Boone, & Tully, ; Munkholm, Heck, & Deen, ) and explanation of the hydraulic conductivity (Luo, Lin, & Halleck, ; Naveed et al, ; Paradelo et al, ; Tracy et al, ). Although the majority of current case studies focus on naturally cultivated soils, there are still some reports confirming that images extracted from X‐ray CT are effective in quantifying pore characteristics of unnaturally soils such as reconstructed, degraded, and reclaimed soils (Dowuona, Taina, & Heck, ; Langmaack, Schrader, Rapp‐Bernhardt, & Kotzke, ; Li, Shao, & Jia, ; Wang, Guo, Bai, & Yang, ). Langmaack et al () reported an interesting case performing X‐ray CT method to study the soil structure rehabilitation of degraded soil caused by compaction.…”

“…Wang et al () was successful in quantifying the pore distribution of reconstructed soils using X‐ray CT images. Li et al () indicated that it was feasible to apply X‐ray CT images to characterize the macropore of loess soil reclaimed by vegetation. So far, however, research on sodic soils is largely insufficient, very few typical findings have been reported on quantification of pore characteristic of sodic soils (Yu, Yang, Lin, Ren, & He, ), especially for their 3D pore characteristics before and after reclamation.…”

Effect of Sewage Irrigation on the CT-Measured Soil Pore Characteristics of a Clay Farmland in Northern China

“…X-ray computed tomography (CT) is an imaging technique based on the computation of many transmission measurements of photographs [ 26 ]. CT has been used to determine the shape, size, orientation, and size distribution of pores at high resolutions [ 27 ]. Kumar et al [ 28 ] quantified soil pore features, including the number of pores, number of macropores, number of coarse mesopores, porosity, macroporosity, coarse mesoporosity and fractal dimension, in agroforestry and grass buffer areas using X-ray CT. Meng et al [ 23 ] quantified soil macropore networks under different forest communities using industrial CT in a mountainous area.…”

The Ability of Soil Pore Network Metrics to Predict Redox Dynamics Is Scale Dependent

“…These parameters can be broken down into two major categories: (1) Parameters that describe the reaction space (i.e., the 3D pore space itself) and (2) parameters that describe the complexity or connectivity of the pore network (i.e., the number of pore connections per unit volume). Variables that belong to the first category are: Visible porosity [15,64,[70][71][72][73], pore size distribution [50,70,73,74], pore surface area [75][76][77], pore thickness (i.e., diameter) [71,77,78], and total visible pore volume [42,50,79]. Variables that fall in the second category rely largely on what is referred to as the skeleton, or single voxel width medial axes, of the pore network [47,80].…”