Numerical assessment of morphological and hydraulic properties of moss, lichen and peat from a permafrost peatland

[摘要] Due to its insulating and draining role,assessing ground vegetation cover properties is important for high-resolution hydrological modeling of permafrost regions. In this study,morphological and effective hydraulic properties of Western Siberian Lowlandground vegetation samples (lichens, Sphagnum mosses, peat) are numerically studiedbased on tomography scans. Porosity is estimated through a void voxelscounting algorithm, showing the existence of representative elementaryvolumes (REVs) of porosity for most samples. Then, two methods are used to estimate hydraulic conductivity depending on the sample's homogeneity. Forhomogeneous samples, direct numerical simulations of a single-phase flow are performed, leading to a definition of hydraulic conductivity related to aREV, which is larger than those obtained for porosity. For heterogeneoussamples, no adequate REV may be defined. To bypass this issue, a porenetwork representation is created from computerized scans. Morphological andhydraulic properties are then estimated through this simplifiedrepresentation. Both methods converged on similar results for porosity. Somediscrepancies are observed for a specific surface area. Hydraulic conductivity fluctuates by 2 orders of magnitude, depending on the methodused. Porosity values are in line with previous values found in the literature,showing that arctic cryptogamic cover can be considered an open andwell-connected porous medium (over 99 % of overall porosity is openporosity). Meanwhile, digitally estimated hydraulic conductivity is highercompared to previously obtained results based on field and laboratoryexperiments. However, the uncertainty is less than in experimental studiesavailable in the literature. Therefore, biological and sampling artifacts are predominant over numerical biases. This could be related tocompressibility effects occurring during field or laboratory measurements. These numerical methods lay a solid foundation for interpreting thehomogeneity of any type of sample and processing some quantitative properties' assessment, either with image processing or with a pore networkmodel. The main observed limitation is the input data quality (e.g., the tomographic scans' resolution) and its pre-processing scheme. Thus, somesupplementary studies are compulsory for assessing syn-sampling andsyn-measurement perturbations in experimentally estimated, effectivehydraulic properties of such a biological porous medium.

[学科分类] 妇产科学