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

Muhammad Naveed, Per Moldrup, Marcel Schaap, Markus Tuller, Ramaprasad Kulkarni, Hans Jorg Vogel, Lis Wollesen De Jonge

Research output: Contribution to journalArticle

17 Citations (Scopus)

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 (6ĝ€cm diameter and 3.5ĝ€cm height) were extracted from the topsoil (5ĝ€cm to 8.5ĝ€cm depth) in a 15ĝ€mĝ€ × ĝ€15ĝ€m grid from an agricultural field located in Silstrup, Denmark. All soil columns were scanned with an industrial X-ray CT scanner (129ĝ€μm resolution) and later employed for measurement of saturated hydraulic conductivity, air permeability at ĝ'30 and ĝ'100ĝ€cm matric potential, and gas diffusivity at ĝ'30 and ĝ'100ĝ€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 ĝ'100ĝ€cm matric potential reasonably well, but failed at ĝ'30ĝ€cm matric potential, particularly for soil columns with biopore-dominated flow. X-ray CT-derived macroporosity matched the measured air-filled porosity at ĝ'30ĝ€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.

Original languageEnglish (US)
Pages (from-to)4017-4030
Number of pages14
JournalHydrology and Earth System Sciences
Volume20
Issue number10
DOIs
StatePublished - Oct 6 2016

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macropore
air permeability
tomography
matric potential
diffusivity
hydraulic conductivity
matrix
prediction
soil column
gas
preferential flow
soil texture
scanner
soil quality
autocorrelation
airflow
topsoil
water flow
porosity
water quality

ASJC Scopus subject areas

  • Water Science and Technology
  • Earth and Planetary Sciences (miscellaneous)

Cite this

Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics. / Naveed, Muhammad; Moldrup, Per; Schaap, Marcel; Tuller, Markus; Kulkarni, Ramaprasad; Vogel, Hans Jorg; De Jonge, Lis Wollesen.

In: Hydrology and Earth System Sciences, Vol. 20, No. 10, 06.10.2016, p. 4017-4030.

Research output: Contribution to journalArticle

Naveed, Muhammad ; Moldrup, Per ; Schaap, Marcel ; Tuller, Markus ; Kulkarni, Ramaprasad ; Vogel, Hans Jorg ; De Jonge, Lis Wollesen. / Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics. In: Hydrology and Earth System Sciences. 2016 ; Vol. 20, No. 10. pp. 4017-4030.
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