HR: 0800h
AN: H51E-04    [Abstracts]
TI: Non-Parametric Statistical Methods for Evaluating Heavily-Censored Hydraulic Conductivity Data
AU: * McGraw, D
EM: David.McGraw@dri.edu
AF: Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, United States
AU: Schumer, R
EM: Rina.Schumer@dri.edu
AF: Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, United States
AU: Oberlander, P
EM: Phil.Oberlander@dri.edu
AF: Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, United States
AB: A statistical analysis was performed to evaluate the relationship between hydraulic conductivity and rock classification in seven boreholes at the Underground Testing Area near Las Vegas, NV. High-resolution flowmeter data were collected at 6 cm intervals and related to the rock classifications: hydrostratigraphic unit, hyrogeologic unit, lithology, stratigraphic unit, and alteration. The combined length of borehole measurements is greater than 1750 m, providing hundreds of hydraulic conductivity values. The complicating factor in this analysis is that over 70% of the data are censored, or less-than some minimum detection limit. Non-parametric censored data techniques described in Helsel (2005) were used to describe the data and determine the best classification method for describing hydraulic conductivity. Results show that 24% of the rock classifications exhibit a significant decrease in K with depth. 90% of the rock classifications are heterogeneous, with hydrostratigraphic unit being the most heterogeneous. The greatest variability in hydraulic conductivity among rock classifications was found in stratigraphic units, while the lowest variability was found in lithology.
DE: 1849 Numerical approximations and analysis
SC: Hydrology [H]
MN: 2007 Joint Assembly