Improvements to the contact filter paper method and its application in the testing of unsaturated soil properties
Year: 2025
Type: article
Abstract: Background The filter paper method is an economical, simple, and time-efficient method for testing matric suction, but the accuracy of its results is often affected by the skill of the operator and the experimental environment, leading to significant variability. To address this issue, this study systematically optimizes and refines the operations and equipment of the filter paper method, improving sealing technique, peeling and retrieval of the sensor filter paper, and operator workflow. Results The improved method significantly enhances stability, repeatability, and accuracy. Comparison with soil-water characteristic curves obtained from a pressure plate apparatus confirms the validity of the improved method. The stability and repeatability of the improvements are demonstrated through comparisons of results from tests conducted by different teams of novice operators. Furthermore, the application of the improved filter paper method to tests of unsaturated hydraulic conductivity and unsaturated shear strength further expands its utility in analyzing unsaturated soil properties. Conclusion The improved filter paper method offers broad prospects for engineering applications. By reducing operator- and environment-induced variability, it provides a more accurate, stable, and repeatable approach for matric suction measurement. It also enables practical extensions to unsaturated hydraulic conductivity and shear strength testing, supporting advances in geotechnical and geoenvironmental engineering.
Source: Geoenvironmental Disasters
Authors: Zhiyan Zhao, Ping Li, Mengmeng Zhang, Jianchao Chen, Denghai Liu, Yaguo Zhang, Xiaokun Hou, Tonglu Li, Xiangyang Hu
Language: English
Topic: Soil and Unsaturated Flow
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,390
Award: 植被-毛细屏障防渗体系的水力效应和固坡机理研究
OpenAlex ID: W4416071160
