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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. Leuven Sofie.Herman@agr.kuleuven.ac.be

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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

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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

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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

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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

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Pore size distribution Opening of the image with spheres of increasing diameter Opening: erosion followed by dilation Original imageErosion of the original image Dilation of the eroded image: Smaller parts removed Struct. Elem.

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Pore size distribution Result: cumulative PSD, pore size classes depend on pixel size D>0.11mmD>1.02 mm D>3.5 mmD>2.83 mmD>1.92 mm

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Connectivity function Connectivity: Euler- Poincaré-characteristic: N: number of isolated components C: total number of redundant connections H: number of holes as a function of the pore size class

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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

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Pore network generated by the Topnet model based on the PSD and connectivity data Pores drained at P=-2cm Face-centered cubic grid Cylindrical pores with fixed radius r

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Distribution of water content calculated =0.27 cm 3 cm -3 measured =0.32 cm 3 cm -3 - = µ water µ wet µ dry highlow Moisture content

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Swelling/shrinking Variable aperture of macropores depending on the degree of saturation drywet FWHM dry =0.48mmFWHM wet =0.33mm

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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

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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

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z = -50 cm, ψ = -100 cm, h = z + ψ = -50cm + -100cm = -150 cm Which direction will water flow? 25 cm define z = 0 at soil surface h = z + ψ = 0 + -200cm.

z = -50 cm, ψ = -100 cm, h = z + ψ = -50cm + -100cm = -150 cm Which direction will water flow? 25 cm define z = 0 at soil surface h = z + ψ = 0 + -200cm.

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