quantitative characterization of the pore network of a macroporous soil using µ x-ray ct sofie...
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Quantitative characterization of the pore network of a macroporous soil using µ X-ray CT
Sofie Herman, department of Land Management, K.U.
Introduction Geometry of pore space: understand
water flowRichards’ eq and effective hydraulic
properties Macropores (cracks, root channels,…)
Preferential flowPore network models
Need to quantify soil structure and pore network of a macroporous soil
General research outline
Hydraulic characterization
K(), h()
Characterization of porous structure and derivation of macropore network
Simulation of flow (and transport) in a pore scale model
Comparison between measured and simulated variables
sandy loam macroporous
soil
K(), h()
Field and laboratory methods: e.g. multistep outflow method, tensio-infiltrometer measurements
µCT and image analysis
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 beam-
hardening Resolution:
0.1 mm 0
10
20
30
40
50
60
70
-30 -20 -10 0 10 20 30distance from CR (mm)
att
. co
eff
. µ
(m
-1)
sand with Cu fi lter (0.82 mm)
sand without fi lter
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
Dilation of the eroded image:Smaller parts removedStruct. Elem.
0. 11 0. 57 1. 02 1. 47 1. 92 2. 37 2. 83 3. 28 3. 73 4. 18
pore diameter (mm)
0
0. 1
0. 2
0. 3
% o
f m
acro
pore
s (-
)
Pore size distribution Result: cumulative PSD, pore size
classes depend on pixel size
D>0.11mm D>1.02 mm
D>3.5 mmD>2.83 mmD>1.92 mm
Connectivity function Connectivity: Euler-
Poincaré-characteristic:
N: number of isolated componentsC: total number of redundant connectionsH: number of holes
as a function of the pore size class
0. 34 0. 79 1. 24 1. 70 2. 15 2. 60 3. 05 3. 50 3. 96
pore diameter (mm)
0
0. 01
0. 02
0. 03
0. 04
V (
-) V
HCNEV
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 (Young-Laplace) within the model.
Water retention and hydraulic conductivity curves are estimated under drainage
Pore network generated by the Topnet model based on the PSD and connectivity data
Pores drained at P=-2cm
- 1 0 1 2 3pF
0
0. 1
0. 2
0. 3
0. 4
0. 5
wat
er c
onte
nt (
cm3
cm-3
)
T opnet model
f it T opnet t o VG eq
- 1 0 1 2 3pF
- 10
- 8
- 6
- 4
- 2
0
2
log
K (
cmhr
-1
)f it t o VG- M ualem eq
T opnet model
Face-centered cubic gridCylindrical pores with fixed radius r
Distribution of water content
calculated=0.27 cm3cm-3 <-> measured=0.32 cm3cm-3
-
=µwater
µwe
t
µdr
y
highlow
Moisture content
Swelling/shrinking Variable aperture of macropores
depending on the degree of saturation
dry wet
0 1 2 3
length (mm)
10
20
30
40
50
atte
nuat
ion
coef
fici
ent
(m-
1)
dry(m- 1)
wet(m- 1)
FWHMdry=0.48mm
FWHMwet=0.33mm
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