HR: 09:00h
AN: H21G-05    [Abstracts]
TI: Tracer Test Analysis Using a Bayesian Geostatistical Inverse Approach to Solve for Transfer Functions
AU: * Fienen, M
EM: fienen@stanford.edu
AF: Stanford University, Department of Civil and Environmental Engineering, Stanford, CA 94305-4020 United States
AU: Carley, J
H21G-05 AF: Oak Ridge National Laboratory, Environmental Services Division P.O. Box 2008, Oak Ridge, TN 37831 United States
AU: Criddle, C
H21G-05 AF: Stanford University, Department of Civil and Environmental Engineering, Stanford, CA 94305-4020 United States
AU: Jardine, P
H21G-05 AF: Oak Ridge National Laboratory, Environmental Services Division P.O. Box 2008, Oak Ridge, TN 37831 United States
AU: Kitanidis, P
H21G-05 AF: Stanford University, Department of Civil and Environmental Engineering, Stanford, CA 94305-4020 United States
AU: Mehlhorn, T
H21G-05 AF: Oak Ridge National Laboratory, Environmental Services Division P.O. Box 2008, Oak Ridge, TN 37831 United States
AU: Watson, D
H21G-05 AF: Oak Ridge National Laboratory, Environmental Services Division P.O. Box 2008, Oak Ridge, TN 37831 United States
AU: Wu, W
H21G-05 AF: Stanford University, Department of Civil and Environmental Engineering, Stanford, CA 94305-4020 United States
AB: Reactive transport modeling is invaluable in planning and design of remediation and chemical treatment. There remains a pressing need for practical and efficient models that do not require or assume attainable the high level of characterization needed by complex numerical models. Here, we explore a linear-systems or transfer-function approach to the problem of reactive tracer transport in a heterogeneous saprolite aquifer. In hydrology, transfer functions have been applied to rainfall-runoff relationships, unit hydrographs and karst aquifer discharge. In previous cases, transfer functions are typically parametric so a particular shape and corresponding equation are assumed for the transfer function that can be solved for using few fitting parameters. We present a nonparametric approach in which the only prior assumptions about the transfer function are the duration, discretization and nonnegativity. The nonparametric approach has the advantage of flexibility - particularly in the case of an unknown number of modes - at a computational cost. The nonparametric transfer functions are obtained through the Bayesian geostatistical inverse method applied to tracer injection histories and breakthrough curves. Nonnegativity is enforced through a reflected-Brownian-motion stochastic model. The inverse method enables us to quantify uncertainty and to generate conditional realizations of the transfer function. The methodology was first tested on challenging synthetic cases and excellent results were obtained. We analyze actual tracer data from a tracer test conducted at the Department of Energy Natural and Accelerated Bioremediation Research (NABIR) Field Research Center (FRC) in Oak Ridge, TN. A conservative and reactive tracer were simultaneously injected and monitored. Transfer functions for both compounds were obtained and the reaction rate for the reactive tracer was estimated using the ratio of the transfer function results. Our nonparametric approach enables rapid characterization of transport behavior in a geologically complex aquifer with a minimum of testing, little prior information and according limitations.
DE: 1832 Groundwater transport
DE: 1849 Numerical approximations and analysis
DE: 1869 Stochastic hydrology
DE: 1872 Time series analysis (3270, 4277, 4475)
SC: Hydrology [H]
MN: Fall Meeting 2005