Inverse modeling of unsaturated flow using clusters of soil texture and pedotransfer functions
AffiliationUniv Arizona, Dept Hydrol & Atmospher Sci
Univ Arizona, Dept Soil Water & Environm Sc
MetadataShow full item record
PublisherAMER GEOPHYSICAL UNION
CitationInverse modeling of unsaturated flow using clusters of soil texture and pedotransfer functions 2016, 52 (10):7631 Water Resources Research
JournalWater Resources Research
Rights© 2016. American Geophysical Union. All Rights Reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractCharacterization of heterogeneous soil hydraulic parameters of deep vadose zones is often difficult and expensive, making it necessary to rely on other sources of information. Pedotransfer functions (PTFs) based on soil texture data constitute a simple alternative to inverse hydraulic parameter estimation, but their accuracy is often modest. Inverse modeling entails a compromise between detailed description of subsurface heterogeneity and the need to restrict the number of parameters. We propose two methods of parameterizing vadose zone hydraulic properties using a combination of k-means clustering of kriged soil texture data, PTFs, and model inversion. One approach entails homogeneous and the other heterogeneous clusters. Clusters may include subdomains of the computational grid that need not be contiguous in space. The first approach homogenizes within-cluster variability into initial hydraulic parameter estimates that are subsequently optimized by inversion. The second approach maintains heterogeneity through multiplication of each spatially varying initial hydraulic parameter by a scale factor, estimated a posteriori through inversion. This allows preserving heterogeneity without introducing a large number of adjustable parameters. We use each approach to simulate a 95 day infiltration experiment in unsaturated layered sediments at a semiarid site near Phoenix, Arizona, over an area of 50 x 50 m(2) down to a depth of 14.5 m. Results show that both clustering approaches improve simulated moisture contents considerably in comparison to those based solely on PTF estimates. Our calibrated models are validated against data from a subsequent 295 day infiltration experiment at the site.
NoteFirst published: 5 October 2016; 6 month embargo.
VersionFinal published version
SponsorsUS Nuclear Regulatory Commission [NRC-04-97-056 (1997-2002)]; NSF-EAR grant [0737945 (2005-2009)]; University of Arizona; Vanderbilt University under the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) III; U.S. Department of Energy