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    USING GEOSTATISTICS, PEDOTRANSFER FUNCTIONS TO GENERATE 3D SOIL AND HYDRAULIC PROPERTY DISTRIBUTIONS FOR DEEP VADOSE ZONE FLOW SIMULATIONS

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    Author
    Fang, Zhufeng
    Issue Date
    2009
    Keywords
    Artificial Neural Network
    Geostatistics
    Modeling
    Pedotransfer Functions
    Advisor
    Neuman, Shlomo P.
    Committee Chair
    Neuman, Shlomo P.
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    We use geostatistical and pedotrasnfer functions to estimate the three-dimensional distributions of soil types and hydraulic properties in a relatively large volume of vadose zone underlying the Maricopa Agriculture Center near Phoenix, Arizona. Soil texture and bulk density data from the site are analyzed geostatistically to reveal the underlying stratigraphy as well as finer features of their three-dimensional variability in space. Such fine features are revealed by cokriging soil texture and water content measured prior to large-scale long-term infiltration experiments. Resultant estimates of soil texture and bulk density data across the site are then used as input into a pedotransfer function to produce estimates of soil hydraulic parameter (saturated and residual water content θs and θr, saturated hydraulic conductivity Ks, van Genuchten parameters αand n) distributions across the site in three dimensions. We compare these estimates with laboratory-measured values of these same hydraulic parameters and find the estimated parameters match the measured well for θs, n and Ks but not well for θr nor α, while some measured extreme values are not captured. Finally the estimated soil hydraulic parameters are put into a numerical simulator to test the reliability of the models. Resultant simulated water contents do not agree well with those observed, indicating inverse calibration is required to improve the modeling performance. The results of this research conform to a previous work by Wang et al. at 2003. Also this research covers the gaps of Wang’s work in sense of generating 3-D heterogeneous fields of soil texture and bulk density by cokriging and providing comparisons between estimated and measured soil hydraulic parameters with new field and laboratory measurements of water retentions datasets.
    Type
    text
    Electronic Thesis
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Hydrology
    Graduate College
    Degree Grantor
    University of Arizona
    Collections
    Master's Theses

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