Journal of the Japanese Society of Soil Physics

[title in Japanese]

[in Japanese]

2025Volume 161 Pages 1-2
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_1

JOURNAL RESTRICTED ACCESS

Download PDF (717K)
A bibliometric analysis of soil physics research in Japan

Juri ASANO, Yuki KOJIMA, Taku NISHIMURA, Satomi KAWAI

2025Volume 161 Pages 3-10
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_3

JOURNAL RESTRICTED ACCESS

Show abstractHide abstract

To obtain an overall understanding of soil physics research in Japan, we conducted a bibliometric analysis of “Journal of the Japanese Society of Soil Physics” and “Proceedings of the Annual Meeting, Japanese Society of Soil Physics” (hereafter re-ferred to as “Proceedings”). Using VOSviewer, we analyzed titles, abstracts, authors, and affiliated institutions. The results indicated that proceedings provided better insights due to the larger number of terms included, the reflection of the latest research topics, and the clear depiction of pure collaborative relationships. Soil physics research in Japan initially focused on understanding the physical properties of paddy soils and developing measurement techniques. From 1989 to 2018, re-search actively adapted to changing societal demands and background conditions. In recent years, since 2019, interest in previously studied topics, such as paddy soil properties and measurement techniques, has resurged, leading to deeper exploration of these research themes. This study provided a comprehensive overview of the trends in soil physics research in Japan.

View full abstract

Download PDF (5985K)
Rapid measurement of water diffusivity using a short horizontal soil column implementing a time-domain reflectometry (TDR) soil moisture sensor

Takahiro YOSHIOKA, Toshihiro DOI, Naoto SATO, Yuichi MARUO, Kosuke NOB ...

2025Volume 161 Pages 11-17
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_11

JOURNAL RESTRICTED ACCESS

Show abstractHide abstract

Understanding soil hydraulic properties is essential for efficient irrigation and fertilization management in agricultural fields. Water diffusivity D(θ ) is a critical parameter in hydraulic properties and is known to be directly determined using the Bruce and Klute method (conventional method). However, the conventional method presents challenges in reducing experimental time and simplifying procedures. In this study, we proposed and compared a new horizontal infiltration experiment method using time domain reflectometry (TDR) soil moisture sensor, referred to as the TDR and fixed-location observation method, with the conventional method. The results showed that the determined D(θ ) values were of the same order, ranging from 0.01 to 10 cm2 s−1, across all methods, confirming that horizontal infiltration experiments using TDR soil moisture sensor are feasible. The TDR method successfully simplified the process and eliminated the cumbersome procedures of the conventional method. Moreover, while fixed-location observation method enabled quick and simple determination of D(θ ), it was found that high temporal resolution was required for accurate measurement.

View full abstract

Download PDF (12032K)
Rapid measurement of water diffusivity using a short horizontal soil column implementing a time-domain reflectometry (TDR) soil moisture sensor

Naoki MASUDA, Hideki MIYAMOTO

2025Volume 161 Pages 19-26
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_19

JOURNAL RESTRICTED ACCESS

Show abstractHide abstract

To clarify the effectiveness of machine learning approaches such as linear and random forest (RF) regressions in predicting apparent permittivity (ε ) in clayey soils, we obtained long-term ε and meteorological datasets from a reclaimed agricultural field and constructed prediction models of the ε at 6, 12, 24 and 48 h using these approaches. The predicted ε values from the linear regression model were generally consistent with the observed data, except during rainfall events. Although datasets for at least the last 72 h must be included as explanatory variables in such models, we confirm that the RF regression model could provide more accurate forecasts at the specified times than linear regression. A machine learning approach with RF regression would facilitate the autonomous prediction of ε values in clayey soils exhibiting structural changes based on the availability of long-term ε and meteorological datasets at the locations.

View full abstract

Download PDF (2981K)
[title in Japanese]

Shoichiro HAMAMOTO, Yuki KOJIMA, Junko NISHIWAKI, Chihiro KATO, Hirota ...

2025Volume 161 Pages 29-31
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_29

JOURNAL RESTRICTED ACCESS

Download PDF (769K)
[title in Japanese]

Masahiro KOBAYASHI

2025Volume 161 Pages 33-
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_33

JOURNAL RESTRICTED ACCESS

Download PDF (755K)
Report of the 2025 Kirkham Conference: Fukushima, Japan

Kosuke NOBORIO, Masaru MIZOGUCHI

2025Volume 161 Pages 35-36
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_35

JOURNAL RESTRICTED ACCESS

Download PDF (829K)
[title in Japanese]

[in Japanese]

2025Volume 161 Pages 39-40
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_39

JOURNAL RESTRICTED ACCESS

Download PDF (752K)
[title in Japanese]

[in Japanese]

2025Volume 161 Pages 45
Published: November 20, 2025
Released on J-STAGE: December 05, 2025

DOIhttps://doi.org/10.34467/jssoilphysics.161.0_45

JOURNAL RESTRICTED ACCESS

Download PDF (422K)

Register with J-STAGE for free!