Correlating pore space morphology with numerically computed soil gas diffusion for structured loam and sand, including stochastic 3D microstructure modeling

Prifling B, Weber M, Rötzer M, Ray N, Prechtel A, Phalempin M, Schlüter S, Vetterlein D, Schmidt V (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Scientific Reports Nature Publishing Group: Open Access Journals - Option B

Book Volume: 15

Article Number: 20174

Issue: 1

DOI: 10.1038/s41598-025-05825-0

Abstract

Biogeochemical soil processes are closely linked to the structure of soil. In particular, nutrient transport depends on diffusivity and permeability within the soil’s pore network. A deeper understanding of the relationship between microscopic soil structure and such effective macroscopic properties can be obtained by tomographic imaging combined with a quantitative analysis of soil morphology and numerical simulations of effective macroscopic properties. In a previous work it has been shown that different parametric regression formulas can be used to predict these relations for finely sieved soils of loam and sand. In the present paper, we validate these formulas and further extend their applicability to structured soils. In particular, 3D CT data of a total of six samples, consisting of three loam and three sand samples, are used as the basis for an extensive structural analysis. As expected, the performance of most regression formulas can be improved by specifically adjusting their parameters for the considered soil structures. However, it turns out that some regression formulas based on, e.g., tortuosity which were fitted for finely sieved soils still reliably predict diffusion for structured soils without adjusting their parameters. For additional validation and improvement of the considered regression formulas, artificially generated soil structures can be utilized. Therefore, a method for the generation of such structures via samples drawn from a parametric stochastic 3D microstructure model is outlined which may serve as a basis for further work.

Authors with CRIS profile

Maximilian Rötzer Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik) Alexander Prechtel Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik)

Involved external institutions

Helmholtz-Zentrum für Umweltforschung (UFZ) / Helmholtz Center for Environmental Research DE Germany (DE) Universität Ulm DE Germany (DE) Katholische Universität Eichstätt-Ingolstadt DE Germany (DE)

How to cite

APA:

Prifling, B., Weber, M., Rötzer, M., Ray, N., Prechtel, A., Phalempin, M.,... Schmidt, V. (2025). Correlating pore space morphology with numerically computed soil gas diffusion for structured loam and sand, including stochastic 3D microstructure modeling. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-05825-0

MLA:

Prifling, Benedikt, et al. "Correlating pore space morphology with numerically computed soil gas diffusion for structured loam and sand, including stochastic 3D microstructure modeling." Scientific Reports 15 (2025).

BibTeX: Download