Applicability of soil pore size distribution derived from digital microscopy images to determination of water retention curve

Abstract Information on the water retention curve (WRC) is required for the numerical simulation of water flow; however, its acquisition is time‐ and cost‐consuming. In this study, the applicability of two‐dimensional (2D) image of soil taken by a digital microscope to WRC measurement was assessed. For this purpose, four undisturbed soil samples were collected at surface (10–15 cm) and undersurface (22.5–27.5 cm) depths to acquire 2D images and measure WRCs from the conventional method, pressure plate method. To derive the WRCs, soil pore‐size distribution in soil images was manually extracted using the following three methods: In Methods 1 and 2, the fuzzy region and the dark region, respectively, in the image were assumed to be a soil pore, and in Method 3, the pore boundary, being assumed to be a bright part, connected the lines and divided the region into pores. Method 3 had much large‐size pores (>75 µm in radius) at deeper depths than at surface depths. This trend was the same as the pressure plate method. The WRCs in three methods were well fitted to the lognormal model. In all methods, the values of parameter of θ e were larger at surface layers than at deeper depths, of which similar result was also seen in the pressure plate method. We discussed applicability of the parameters. It is effective to determine θ e from the pressure plate method and the other parameters ( ψ m and σ ) from the image‐based method. From those analyses, it could be said to prove to obtain WRC from an image‐based method.

Authors

Institutions

Publication Details

Journal
Agrosystems Geosciences & Environment
Published
2025-02-07
DOI
https://doi.org/10.1002/agg2.70049
Citations
1
Primary Topic
Soil and Unsaturated Flow
Type
article
Field-Weighted Citation Impact
0.95

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Applicability of soil pore size distribution derived from digital microscopy images to determination of water retention curve

Yuki Hayashi
1 citations
Agrosystems Geosciences & Environment
Soil and Unsaturated Flow
0.95
article

Applicability of soil pore size distribution derived from digital microscopy images to determination of water retention curve

Yuki Hayashi
article en
1 citations

Abstract

Abstract Information on the water retention curve (WRC) is required for the numerical simulation of water flow; however, its acquisition is time‐ and cost‐consuming. In this study, the applicability of two‐dimensional (2D) image of soil taken by a digital microscope to WRC measurement was assessed. For this purpose, four undisturbed soil samples were collected at surface (10–15 cm) and undersurface (22.5–27.5 cm) depths to acquire 2D images and measure WRCs from the conventional method, pressure plate method. To derive the WRCs, soil pore‐size distribution in soil images was manually extracted using the following three methods: In Methods 1 and 2, the fuzzy region and the dark region, respectively, in the image were assumed to be a soil pore, and in Method 3, the pore boundary, being assumed to be a bright part, connected the lines and divided the region into pores. Method 3 had much large‐size pores (>75 µm in radius) at deeper depths than at surface depths. This trend was the same as the pressure plate method. The WRCs in three methods were well fitted to the lognormal model. In all methods, the values of parameter of θ e were larger at surface layers than at deeper depths, of which similar result was also seen in the pressure plate method. We discussed applicability of the parameters. It is effective to determine θ e from the pressure plate method and the other parameters ( ψ m and σ ) from the image‐based method. From those analyses, it could be said to prove to obtain WRC from an image‐based method.

Agrosystems Geosciences & EnvironmentVol. 8(1)
Ritsumeikan University (JP)
Ritsumeikan University
Openalex Percentile: Top 29%
Soil and Unsaturated Flow
0.95
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.