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Title: Simulating Field-Scale Moisture Flow Using a Combined Power-Averaging and Tensorial Connectivity-Tortuosity Approach

Journal Article · · Water Resources Research, 46:Article No. W09505

Various stochastic methods have been developed over the past two decades to estimate effective unsaturated hydraulic properties. We develop in this paper an alternative practical approach to estimate three-dimensional effective unsaturated hydraulic conductivity via a combined power-averaging and tensorial connectivity-tortuosity (PA-TCT) model. An application of the new approach to data collected at a field injection site suggests that the PA-TCT model provides 1) a reasonable framework for upscaling core-scale measurements and 2) an accurate simulation of moisture flow in a heterogeneous vadose zone. The heterogeneous media at the injection site is composed of multiple geologic units, each of which is represented by an anisotropic equivalent homogeneous medium (EHM). The directional effective hydraulic conductivity for each anisotropic EHM was determined by upscaling the laboratory-measured hydraulic properties with the combined PA-TCT approach. A larger difference between the power values in the horizontal and vertical directions indicates a larger macroscopic anisotropy in unsaturated hydraulic conductivity. A moment analysis was used to quantify the center of mass and the spread of the moisture content difference. Numerical simulations showed that, if the flow domain were treated as being isotropic, the vertical migration was significantly overestimated while the lateral movement was underestimated when compared to observations. To the contrary, if the media was treated as perfectly stratified, the lateral moisture movement was considerably overestimated while the vertical movement was underestimated. However, when the flow domain was modeled as being mildly anisotropic with the PA-TCT based parameters, the model can successfully predict the moisture flow and the simulated plume matched the observed moisture plume the best.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
991083
Report Number(s):
PNNL-SA-68187; WRERAQ; 830403000; TRN: US201020%%693
Journal Information:
Water Resources Research, 46:Article No. W09505, Vol. 46; ISSN 0043-1397
Country of Publication:
United States
Language:
English