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Title: Probabilistic Analysis of In Situ Soil Water Characteristic Curve Using Kernel Density Estimation
Soil water characteristic curve (SWCC) which describes the relationship between water content and matric suction is important to analyzing unsaturated soil behavior. Because of the degree of uncertainty in field conditions due to climatic variability and soil heterogeneities, it becomes necessary to probabilistically characterize the SWCC. A satisfactory probabilistic characterization of field-based SWCCs requires a substantial data pair of water content and suction and their distribution characteristics. In this study, the kernel density estimate (KDE) approach was applied to water content and suction data measured from field-installed co-located sensors of a compacted clay bed to (1) determine the modality of water content and suction distribution and their constitutive relationship at variable weather conditions and (2) demonstrate the importance of probabilistic analysis of SWCC. The Gaussian function was used in the KDE analysis. A moisture sensor and soil water potential sensor were juxtaposed at 0.3 m depth of the 3 m × 3 m compacted clay bed to collect the water content and suction data and determine their distribution under the field condition. The density plots of both water content and suction at 0.3 m depth exhibited multimodal distribution due to the uneven distribution of climatic events. The KDE reasonably identified the air entry value, saturated moisture content, and residual moisture content in the field conditions, which were validated with field-based SWCC plots. The study showed that probabilistic analysis better interprets the realistic scenarios of field unsaturated soil behavior.  more » « less
Award ID(s):
2101081
PAR ID:
10502826
Author(s) / Creator(s):
; ;
Editor(s):
T. Matthew Evans, Ph.D. Nina Stark
Publisher / Repository:
American Society of Civil Engineers
Date Published:
ISBN:
9780784485354
Page Range / eLocation ID:
276 to 286
Format(s):
Medium: X
Location:
Vancouver, British Columbia, Canada
Sponsoring Org:
National Science Foundation
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