Record Display for the EPA National Library Catalog


Main Title Statistical estimation and visualization of ground-water contamination data
Author Boeckenhauer, R. K. ; Cox, D. D. ; Ensor, K. B. ; Bedient, P. B. ; Holder, A. W.
Other Authors
Author Title of a Work
Boeckenhauer, Rachel K.
CORP Author Rice Univ., Houston, TX. Dept. of Environmental Science and Engineering.;National Risk Management Research Lab., Ada, OK. Subsurface Protection and Remediation Div.
Publisher National Risk Management Laboratory, Office of Research and Development, U.S. Environmental Protection Agency,
Year Published 2000
Report Number EPA/600/R-00/034
Stock Number PB2001-104380
OCLC Number 47293045
Subjects Groundwater--Computer simulation ; Groundwater flow--Computer simulation
Additional Subjects Ground water ; Water pollution ; Soil pollution ; Statistical analysis ; Visualization ; Estimates ; Remediation ; Methods ; Exploratory analysis
Internet Access
Description Access URL
Library Call Number Additional Info Location Last
EHAD  EPA/600/R-00-034 Region 1 Library/Boston,MA 04/12/2002
EJBD ARCHIVE EPA 600/R-00/034 Headquarters Library/Washington,DC 09/29/2014
EJBD  EPA 600/R-00/034 Headquarters Library/Washington,DC 07/13/2001
EMBD  EPA/600/R-00/034 NRMRL/GWERD Library/Ada,OK 12/12/2003
ESAD  EPA 600-R-00-034 2 copies Region 10 Library/Seattle,WA 06/02/2016
NTIS  PB2001-104380 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation ix, 49 p. : ill., charts ; 28 cm.
This work presents methods of visualizing and animating statistical estimates of ground water and/or soil contamination over a region from observations of the contaminant for that region. The primary statistical methods used to produce the regional estimates are nonparametric regression and geostatistical modeling to produce surface estimates with little outside intervention, whereas geostatistical modeling produces prediction errors. Finally, a method is proposed for estimating the total amount of contaminant present in a region. The proposed method models the data as a realization of a lognormal stochastic process and then capitalizes on conditional simulation to generate realizations of the modeled process from which the distribution of the total contaminant (or integral of the process) is estimated.
"August 2000." "EPA/600/R-00/034." Includes bibliographical references (p. 49).