Quantitative characterization of the
pore network of a macroporous soil
using µ X-ray CT
Sofie Herman, department of Land
Management, K.U. Leuven
Sofie.Herman@agr.kuleuven.ac.be
Introduction

Geometry of pore space: understand water
flow
Richards’ eq and effective hydraulic properties

Macropores (cracks, root channels,…)
Preferential flow
Pore network models

Need to quantify soil structure and pore
network of a macroporous soil
General research outline
Field and laboratory methods:
e.g. multistep outflow
method, tensio-infiltrometer
measurements
sandy loam
macroporous
soil
Hydraulic characterization
Characterization of porous structure
and derivation of macropore network
K(), h()
Comparison between
measured and
simulated variables
µCT and image analysis
K(), h()
Simulation of flow (and
transport) in a pore scale model
Interaction between different flow
domains
Microfocus X-ray CT


Sample: 5 cm diameter, 5 cm height
Scan parameters:


135 kV and 0.1 mA
Cu-filter (0.82 mm) to reduce beamhardening
70
sand with Cu filter (0.82 mm)
sand without filter
Resolution:

0.1 mm
50
-1

att. coeff. µ (m )
60
40
30
20
10
0
-30
-20
-10
0
10
distance from CR (mm)
20
30
Determination and characterization of
the pore network



Macropores-matrix
separation by
binarization
Macropore volume:
10 %
Pore size distribution
and connectivity
function by means
of mathematical
morphology
Pore size distribution


Opening of the image with spheres of
increasing diameter
Opening: erosion followed by dilation
Original image
Erosion of the
original image
Struct. Elem.
Dilation of the
eroded image:
Smaller parts
removed
Pore size distribution

Result: cumulative PSD, pore size
classes depend on pixel size
% of macropores (-)
0.3
0.2
D>0.11mm
D>1.02 mm
0.1
0
0.11 0.57 1.02 1.47 1.92 2.37 2.83 3.28 3.73 4.18
pore diameter (mm)
D>1.92 mm
D>2.83 mm
D>3.5 mm
Connectivity function

0.04
N C  H
EV 
V
0.03
V (-)
Connectivity: EulerPoincaré-characteristic:
0.02
N: number of isolated
components
C: total number of redundant
connections
H: number of holes
0.01
0
0.34 0.79 1.24 1.70 2.15 2.60 3.05 3.50 3.96
pore diameter (mm)
as a function of the
pore size class
Determination of soil hydraulic
properties



Generation of a pore network with the same
pore size distribution and connectivity
function by the Topnet model (Vogel, 1998)
Drainage is simulated (initial state:
saturation) by applying pressure steps that
correspond to a given pore size (YoungLaplace) within the model.
Water retention and hydraulic conductivity
curves are estimated under drainage
water content (cm 3cm -3)
Pore network generated by the
Topnet model based on the PSD
and connectivity data
0.5
0.4
0.3
0.2
Topnet model
0.1
0
fit Topnet to VG eq
-1
0
1
pF
2
3
Face-centered cubic grid
Cylindrical pores with fixed radius r
Pores drained at P=-2cm
log K (cmhr -1 )
2
0
-2
-4
-6
fit to VG-Mualem eq
-8
-10
Topnet model
-1
0
1
pF
2
3
Distribution of water content
Moisture content
µwet
µwater
µdry
low
=
calculated=0.27 cm3cm-3 <-> measured=0.32 cm3cm-3
high
Swelling/shrinking
dry
Variable aperture of macropores depending
on the degree of saturation
wet
attenuation coefficient (m -1 )

50
40
30
20
 dry (m-1)
 wet (m -1 )
10
FWHMdry=0.48mm FWHMwet=0.33mm
0
1
2
length (mm)
3
Conclusions



The macropore network was characterized
quantitatively in terms of the pore size
distribution and connectivity by µCT
Effective hydraulic properties were estimated
from a static pore network model
µCT offers the potential to visualize dynamic
phenomena that occur during wetting/drying
cycles such as shrinking and swelling of pores
Future objectives



Describe and measure swelling of pores
as a function of moisture content
Simulate drainage/imbibition of soil by a
dynamic model
Incorporate swelling into the model