Guber, A. K., T. Kutlu, M. L. Rivers, and A. N. Kravchenko. 2021. Mass-balance approach to quantify water distribution in soils based on X-ray CT images. European Journal of Soil Science 72:578-592.

Citable PDF link: https://lter.kbs.msu.edu/pub/3865

X‐ray computed tomography (CT) is commonly used in soil science to quantify distributions of pores, water and solids within soil samples. Particularly promising for liquid visualization is dual‐energy scanning of samples with added dopant solutions. The approach uses solutions of heavy elements as a proxy for the soil water and utilizes the abrupt increase of the mass attenuation coefficient of heavy elements when crossing an X‐ray absorption edge, detectable by dual‐energy CT scanning. However, a key step in visualization of the added liquid is image segmentation. In partially saturated soils, the X‐ray CT images consist of voxels with the presence of solid, liquid and gaseous phases in different ratios. These ratios are generally ignored by the traditional image segmentation methods, which separate image voxels into groups with either zero or complete saturation by either prevailing phase. The objective of this study was to develop and test a new physically based segmentation approach that accounts for partial saturation of image voxels by liquids. We combined a theoretical equation for detected photon intensity with the mass conservation equation to compute saturation of image voxels by dopant solution applied to the soil. This approach was tested on soil micro‐columns with potassium iodide (KI) solutions. The proposed approach outperformed the traditional segmentation methods, particularly at low and intermediate water contents. Tests conducted for KI solutions in the concentration ranges from 2 to 20% revealed deterioration of the method accuracy with decreasing dopant concentration in the soil. Based on the results of this study we recommend 10 wt% KI solution for quantifying spatial distribution of liquids in soils using dual‐energy X‐ray microtomography.

DOI: 10.1111/ejss.13005

Associated Treatment Areas:

GLBRC Scale-up Fields

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