Linking air and water transport in intact soils to macropore characteristics inferred from X-ray computed tomography

Soil macropores largely control fluid and solute transport, making visualization and quantification of macropore characteristics essential for better understanding and predicting soil hydrogeochemical functions. In this study, seventeen large (19 x 20 cm) intact soil cores taken across a loamy field site (Silstrup, Denmark) were scanned at in-situ sampling conditions (-field capacity) at a relatively coarse resolution (500 pm) by medical X-ray computed tomography (CT). In the image analyses, artifacts related to the presence of rocks were identified and removed before linking CT-derived pore parameters to measured fluid transport parameters. After CT scanning, soil cores were saturated and drained at -20 hPa soil-water potential, leaving only pores > 150 mu m air-filled. Air permeability (k(a20)) and air-filled porosity (epsilon(20)) were measured to evaluate gas transport behavior in macropore networks under these conditions. Finally, tracer transport experiments at a constant, high flow rate (10 mm h(-1)) were carried out, and the arrival time for 5% of the applied tracer (T-5%) was used as an index for the magnitude of water transport in macropores. Although X-ray CT scanning only identified 5-25% of the total air-filled pore network at -20 hPa, CT-derived macroporosity (average for whole column) and macroporosity for the limiting-quarter section of each column were highly correlated to both k(a20) and T-5% (R-2 from 0.6 to 0.8). The CT-inferred limiting depth for soil-gas transport was typically located at 90-165 mm depth, and likely a result of soil management history. Results suggest that the functional macropore network for fluid transport was well quantified by rapid, coarse-resolution X-ray CT scanning. Linking rapid X-ray CT scanning with classical fluid transport measurements on large intact columns thus proves highly useful for characterizing soil macropore functions and in perspective may prove to be useful in predicting field-scale variations in gas, water, and chemical transport. (C) 2014 Elsevier B.V. All rights reserved.