Developing Spectroscopic and Imaging Techniques for Advanced Studies in Soil Physics Based on Results Obtained at Embrapa Instrumentation

Crestana, Sı́lvio; Cruvinel, P. E.

doi:10.1007/s13538-022-01202-8

Cited by 1 publication

(1 citation statement)

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“…The simulation and modeling of physical parameters using non‐destructive techniques such as high‐resolution tomography opens new opportunities for dynamic studies at different scales, like synchrotron‐based tomography (Menke et al., 2016), including the dynamics of unsaturated flow in soils. One challenge is the integration and interpretation of results at different scales (downscaling and upscaling), such as from the use of different types of µCTs (Crestana & Cruvinel, 2023).…”

Section: Introductionmentioning

confidence: 99%

Multiscale pore‐network reconstruction of a fine‐textured heterogeneous soil

Pontedeiro,

van Genuchten,

Godoy

et al. 2024

Vadose Zone Journal

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Digital samples offer many opportunities to study subsurface fluid flow and contaminant transport processes. The pore size distribution of especially fine‐textured porous media often covers many orders of magnitude in the length scale, which makes accurate microCT scanning and modeling of the underlying processes difficult. When a single‐resolution image is not capable of capturing all relevant details of a sample, one should scan the sample, or selected parts of it, at different resolutions. Combining multiple resolutions into one single sample for subsequent pore‐scale modeling is generally not possible due to limitations in computer memory and speed, thus making it necessary to create a simpler sample containing relevant information from the parent networks. We imaged four samples using different resolutions to capture the multiscale heterogeneity of a fine‐textured soil and combined them into one overall digital sample based on the original pore networks. The parent networks were characterized using their geometrical properties, correlations between these properties, and connectivity functions describing the network topologies. Our approach creates stochastic networks of arbitrary size with the same flow properties as the parent network. The method, implemented using the PoreStudio pore network model, repeatedly integrates information at two subsequent scales, with the resulting digital sample having the same hydraulic properties as the original samples. The procedure leads to more useful three‐dimensional digital models, facilitating basic analyses of underlying pore size distributions. Porosity calculations were compared with direct measurements, while those for the hydraulic conductivity were compared with estimates based on the particle size distribution and nearby field data.

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Section: Introductionmentioning

confidence: 99%