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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 10
Hydrol. Earth Syst. Sci., 20, 4017–4030, 2016
https://doi.org/10.5194/hess-20-4017-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 4017–4030, 2016
https://doi.org/10.5194/hess-20-4017-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Oct 2016

Research article | 06 Oct 2016

Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

Muhammad Naveed1, Per Moldrup3, Marcel G. Schaap4, Markus Tuller4, Ramaprasad Kulkarni4,5, Hans-Jörg Vogel6, and Lis Wollesen de Jonge2 Muhammad Naveed et al.
  • 1Institute of Biological and Environmental Sciences, University of Aberdeen, King's College, Aberdeen AB24 3FX, UK
  • 2Department of Agroecology, Faculty of Science and Technology, Aarhus University, Blichers Allé 20, Postbox 50, 8830 Tjele, Denmark
  • 3Department of Civil Engineering, Aalborg University, Sohngaardsholmsvej 57, 9000 Aalborg, Denmark
  • 4Department of Soil, Water and Environmental Science, The University of Arizona, 1177 E. 4th Street, Tucson, AZ 85721, USA
  • 5Department of Electrical and Computer Engineering, The University of Arizona, 1230 E Speedway Blvd., Tucson, AZ 85721, USA
  • 6Department of Soil Physics, Helmholtz Center for Environmental Research-UFZ, Theodor Lieser Straße 4, 06120 Halle (Saale), Germany

Abstract. Prediction and modeling of localized flow processes in macropores is of crucial importance for sustaining both soil and water quality. However, currently there are no reliable means to predict preferential flow due to its inherently large spatial variability. The aim of this study was to investigate the predictive performance of previously developed empirical models for both water and air flow and to explore the potential applicability of X-ray computed tomography (CT)-derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 cm to 8.5 cm depth) in a 15 m  ×  15 m grid from an agricultural field located in Silstrup, Denmark. All soil columns were scanned with an industrial X-ray CT scanner (129 µm resolution) and later employed for measurement of saturated hydraulic conductivity, air permeability at −30 and −100 cm matric potential, and gas diffusivity at −30 and −100 cm matric potential. Distribution maps for saturated hydraulic conductivity, air permeability, and gas diffusivity reflected no autocorrelation irrespective of soil texture and organic matter content. Existing empirical predictive models for saturated hydraulic conductivity and air permeability showed poor performance, as they were not able to realistically capture macropore flow. The tested empirical model for gas diffusivity predicted measurements at −100 cm matric potential reasonably well, but failed at −30 cm matric potential, particularly for soil columns with biopore-dominated flow. X-ray CT-derived macroporosity matched the measured air-filled porosity at −30 cm matric potential well. Many of the CT-derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also significantly correlated with saturated hydraulic conductivity, air permeability, and gas diffusivity. The predictive Ahuja et al. (1984) model for saturated hydraulic conductivity, air permeability, and gas diffusivity performed reasonably well when parameterized with novel, X-ray CT-derived parameters such as effective percolating macroporosity for biopore-dominated flow and total macroporosity for matrix-dominated flow. The obtained results further indicate that it is crucially important to discern between matrix-dominated and biopore-dominated flow for accurate prediction of macropore flow from X-ray CT-derived macropore network characteristics.

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Quantification of rapid flow of water and associated transport of contaminants through large soil pores generated by earthworms or decaying plant roots is of crucial importance for sustaining both soil and water quality. Advanced visualization and analysis techniques based on state-of-the-art X-ray computed tomography have been applied to 65 soil cores extracted from an agricultural field in Silstrup, Denmark, to improve models for the prediction of fast, preferential flow processes in soils.
Quantification of rapid flow of water and associated transport of contaminants through large...
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