dc.contributor.author |
Pantazidou, M |
en |
dc.contributor.author |
Liu, K |
en |
dc.date.accessioned |
2014-03-01T01:28:10Z |
|
dc.date.available |
2014-03-01T01:28:10Z |
|
dc.date.issued |
2008 |
en |
dc.identifier.issn |
0169-7722 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/18746 |
|
dc.subject |
DNAPL infiltration |
en |
dc.subject |
Field-scale heterogeneity |
en |
dc.subject |
Hazardous waste site characterization |
en |
dc.subject |
Multiphase fluid flow |
en |
dc.subject.classification |
Environmental Sciences |
en |
dc.subject.classification |
Geosciences, Multidisciplinary |
en |
dc.subject.classification |
Water Resources |
en |
dc.subject.other |
Aquifers |
en |
dc.subject.other |
Computer simulation |
en |
dc.subject.other |
Hydraulic conductivity |
en |
dc.subject.other |
Impurities |
en |
dc.subject.other |
Multiphase flow |
en |
dc.subject.other |
Thermal plumes |
en |
dc.subject.other |
DNAPL infiltration |
en |
dc.subject.other |
Field-scale heterogeneity |
en |
dc.subject.other |
Hazardous waste site characterization |
en |
dc.subject.other |
Soils |
en |
dc.subject.other |
Aquifers |
en |
dc.subject.other |
Computer simulation |
en |
dc.subject.other |
Hydraulic conductivity |
en |
dc.subject.other |
Impurities |
en |
dc.subject.other |
Multiphase flow |
en |
dc.subject.other |
Soils |
en |
dc.subject.other |
Thermal plumes |
en |
dc.subject.other |
aquifer |
en |
dc.subject.other |
estimation method |
en |
dc.subject.other |
heterogeneity |
en |
dc.subject.other |
hydraulic conductivity |
en |
dc.subject.other |
nonaqueous phase liquid |
en |
dc.subject.other |
numerical model |
en |
dc.subject.other |
plume |
en |
dc.subject.other |
pollutant source |
en |
dc.subject.other |
pollutant transport |
en |
dc.subject.other |
soil structure |
en |
dc.subject.other |
spatial distribution |
en |
dc.subject.other |
article |
en |
dc.subject.other |
geostatistical analysis |
en |
dc.subject.other |
hydraulic conductivity |
en |
dc.subject.other |
plume |
en |
dc.subject.other |
priority journal |
en |
dc.subject.other |
qualitative analysis |
en |
dc.subject.other |
quantitative analysis |
en |
dc.subject.other |
simulation |
en |
dc.subject.other |
soil analysis |
en |
dc.subject.other |
soil pollution |
en |
dc.subject.other |
soil structure |
en |
dc.subject.other |
statistical analysis |
en |
dc.subject.other |
Computer Simulation |
en |
dc.subject.other |
Filtration |
en |
dc.subject.other |
Pressure |
en |
dc.subject.other |
Soil |
en |
dc.subject.other |
Uncertainty |
en |
dc.title |
DNAPL distribution in the source zone: Effect of soil structure and uncertainty reduction with increased sampling density |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1016/j.jconhyd.2007.11.002 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1016/j.jconhyd.2007.11.002 |
en |
heal.language |
English |
en |
heal.publicationDate |
2008 |
en |
heal.abstract |
This paper focuses on parameters describing the distribution of dense nonaqueous phase liquid (DNAPL) contaminants and investigates the variability of these parameters that results from soil heterogeneity. In addition, it quantifies the uncertainty reduction that can be achieved with increased density of soil sampling. Numerical simulations of DNAPL releases were performed using stochastic realizations of hydraulic conductivity fields generated with the same geostatistical parameters and conditioning data at two sampling densities, thus generating two simulation ensembles of low and high density (three-fold increase) of soil sampling. The results showed that DNAPL plumes in aquifers identical in a statistical sense exhibit qualitatively different patterns, ranging from compact to finger-like. The corresponding quantitative differences were expressed by defining several alternative measures that describe the DNAPL plume and computing these measures for each simulation of the two ensembles. The uncertainty in the plume features under study was affected to different degrees by the variability of the soil, with coefficients of variation ranging from about 20% to 90%, for the low-density sampling. Meanwhile, the increased soil sampling frequency resulted in reductions of uncertainty varying from 7% to 69%, for low- and high-uncertainty variables, respectively. In view of the varying uncertainty in the characteristics of a DNAPL plume, remedial designs that require estimates of the less uncertain features of the plume may be preferred over others that need a more detailed characterization of the source zone architecture. (C) 2007 Elsevier B.V. All rights reserved. |
en |
heal.publisher |
ELSEVIER SCIENCE BV |
en |
heal.journalName |
Journal of Contaminant Hydrology |
en |
dc.identifier.doi |
10.1016/j.jconhyd.2007.11.002 |
en |
dc.identifier.isi |
ISI:000254134400011 |
en |
dc.identifier.volume |
96 |
en |
dc.identifier.issue |
1-4 |
en |
dc.identifier.spage |
169 |
en |
dc.identifier.epage |
186 |
en |