X‐ray CT‐Derived Soil Characteristics Explain Varying Air, Water, and Solute Transport Properties across a Loamy Field

Abstract

Core Ideas We used CT‐derived parameters to explain solute, water, and air transport at field scale. CTmatrix was found to be the best parameter to explain solute transport. Limiting macroporosity gave the highest correlations with water and air transport. Combining macroporosity and CTmatrix improved the relationships of water and air flow. The characterization of soil pore space geometry is important for explaining fluxes of air, water, and solutes through soil and understanding soil hydrogeochemical functions. X‐ray computed tomography (CT) can be applied for this characterization, and in this study CT‐derived parameters were used to explain water, air, and solute transport through soil. Forty‐five soil columns (20 by 20 cm) were collected from an agricultural field in Estrup, Denmark, and subsequently scanned using a medical CT scanner. Nonreactive tracer leaching experiments were performed in the laboratory along with measurements of air permeability (Ka) and saturated hydraulic conductivity (Ksat). The CT number of the matrix (CTmatrix), which represents the moist bulk density of the soil matrix, was obtained from the CT scans as the average CT number of the voxels in the grayscale image excluding macropores and stones. The CTmatrix showed the best relationships with the solute transport characteristics, especially the time by which 5% of the applied mass of tritium was leached, known as the 5% arrival time (t0.05). The CT‐derived macroporosity (pores >1.2 mm) was correlated with Ka and log10(Ksat). The correlation improved when the limiting macroporosity (the minimum macroporosity for every 0.6‐mm layer along the soil column) was used, suggesting that soil layers with the narrowest macropore section restricted the flow through the whole soil column. Water, air, and solute transport were related with the CT‐derived parameters by using a best subsets regression analysis. The regression coefficients improved using CTmatrix, limiting macroporosity, and genus density, while the best model for t0.05 used CTmatrix only. The scanning resolution and the time for soil structure development after mechanical activities could be factors that increased the uncertainty of the relationships. Nevertheless, the results confirmed the potential of X‐ray CT visualization techniques for estimating fluxes through soil at the field scale.

Combining Visible−Near‐Infrared and Pedotransfer Functions for Parameterization of Tile Drain Flow Simulations

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Reconfiguration of macropore networks in a silty loam soil following biochar addition identified by X‐ray microtomography and network analyses

“…The accessibility of macropore networks is particularly important for the flow of water, nutrients and air through the soils, although they comprise only a small fraction of total porosity. A macropore network with large accessibility increases the rate of infiltration and reduces surface runoff (Sandin, Koestel, Jarvis, & Larsbo, ), whereas a macropore network with small accessibility decreases the emission of GHGs (greenhouse gases) (Rabot, Lacoste, Henault, & Cousin, ), decreases air permeability and cuts off the water transport to deeper soil layers (Paradelo et al, ). Accessibility of the macropore network in this study was evaluated by the pore network model and network analyses.…”

Prediction of the soil water retention curve for structured soil from saturation to oven‐dryness

“…The field has a 4‐year crop rotation of potato ( Solanum tuberosum L.), winter wheat ( Triticum aestivum L.), sugar beet ( Beta vulgaris L.) and spring barley ( Hordeum vulgare L.), and the sampling took place in spring of the winter wheat season 6 months after the last ploughing (30‐cm depth). All three fields showed aggregated or macroporous soil structure to some extent, which has been confirmed by X‐ray computed tomography observations or infiltration measurements (Naveed et al ., ; Norgaard et al ., ; Paradelo et al ., ). The Danish field sites had 45 (Estrup) and 8 (Silstrup) individual sampling locations where undisturbed soil cores were taken in triplicate from 6‐ to 10‐cm depth together with disturbed soil samples for particle‐size distribution and organic carbon analyses.…”