HR: 09:30h
AN: H41G-07 INVITED     [Abstracts]
TI: Multivariate Sensitivity Analysis of Saturated Flow Through Simulated Highly Heterogeneous Groundwater Aquifers
AU: * Winter, L
EM: lwinter@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO 80305 United States
AU: Tartakovsky, D M
EM: dmt@ucsd.edu
AF: University of California, San Diego, EBU II, Room 577, Mail Code 0411, La Jolla, CA 92093 United States
AU: Guadagnini, A
EM: alberto.guadagnini@polimi.it
AF: Politecnico di Milano, Piazza L. Da Vinci, 32, Milan, 20133 Italy
AU: Nychka, D
EM: nychka@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO 80305 United States
AB: A multivariate Analysis of Variance (ANOVA) is used to measure the relative sensitivity of groundwater flow to two factors that indicate different dimensions of aquifer heterogeneity. An aquifer is modeled as the union of a disjoint collection of volumes, or blocks, composed of different materials with different hydraulic conductivities. The factors are correlation between the hydraulic conductivities of the different materials and the contrast between mean conductivities in the different materials. The precise values of aquifer properties are usually uncertain because they are only sparsely sampled, yet are highly heterogeneous. Hence, the spatial distribution of blocks and the distribution of materials in blocks are uncertain and are modeled as stochastic processes. The ANOVA is performed on a large sample of Monte Carlo simulations of a simple model flow system composed of two materials and three blocks. Simulated flow is much more sensitive to the contrast between mean conductivities of the blocks than it is to the intensity of correlation, although both factors are statistically significant. The methodology of the experiment - ANOVA performed on Monte Carlo simulations of a multi-material flow system - can form the basis of additional studies of more complicated interactions between factors that define flow through an uncertain aquifer.
DE: 1873 Uncertainty assessment (3275)
DE: 3245 Probabilistic forecasting (3238)
DE: 3265 Stochastic processes (3235, 4468, 4475, 7857)
DE: 3275 Uncertainty quantification (1873)
DE: 4468 Probability distributions, heavy and fat-tailed (3265)
SC: Hydrology [H]
MN: Fall Meeting 2005