Core Ideas
Specimen preparation methods have a significant influence on hydraulic conductivity.
The difference caused by different methods can be large as one order of magnitude.
Soil pore structure should be considered in predicting hydraulic conductivity.
A pore‐information‐based model is presented to predict hydraulic conductivity.
The new model is more accurate than traditional particle information based models.
A series of laboratory tests were performed to investigate the influences of specimen preparation on pore size distribution of soil and saturated hydraulic conductivity (Ks). Nuclear magnetic resonance technology was used to measure the pore size distribution of the saturated samples of silty soil, which were prepared by three different kinds of methods: Proctor compaction, static compaction, and the consolidation method. The Ks of the samples was measured by the falling head permeability test. The results show that the difference in Ks caused by different specimen preparations can be large as one order of magnitude, as the measured Ks varied from 3.09 × 10−3 to 3.36 × 10−4 cm s−1. The consolidated specimen tended to have the greatest Ks value, followed by those prepared by Proctor compaction and static compaction. The observed difference highlights the importance of pore structure in determining Ks. This study also presents a pore‐information‐based theoretical approach for predicting Ks. A comparison of measured data shows that the proposed model performs better than the traditional void‐ratio‐based models.
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