X‐ray CT‐Derived Soil Characteristics Explain Varying Air, Water, and Solute Transport Properties across a Loamy Field. Issue 4 (15th April 2016) - Paradelo, Marcos
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 ( K a ) and saturated hydraulic conductivity ( K sat ). 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 ( t 0.05 ). The CT‐derived macroporosity (pores >1.2 mm) was correlated with K a and log10 ( K sat ). 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 t 0.05 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.