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Predicting flow and transport in highly heterogeneous alluvial aquifers
Author(s) -
Dogan Mine,
Van Dam Remke L.,
Liu Gaisheng,
Meerschaert Mark M.,
Butler James J.,
Bohling Geoffrey C.,
Benson David A.,
Hyndman David W.
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl061800
Subject(s) - aquifer , plume , advection , groundwater flow , groundwater , flow (mathematics) , geology , hydraulic conductivity , alluvium , environmental science , aquifer properties , cellular automaton , diffusion , soil science , hydrology (agriculture) , geotechnical engineering , mechanics , computer science , meteorology , geomorphology , physics , algorithm , groundwater recharge , thermodynamics , soil water
Successful prediction of groundwater flow and solute transport through highly heterogeneous aquifers has remained elusive due to the limitations of methods to characterize hydraulic conductivity ( K ) and generate realistic stochastic fields from such data. As a result, many studies have suggested that the classical advective‐dispersive equation (ADE) cannot reproduce such transport behavior. Here we demonstrate that when high‐resolution K data are used with a fractal stochastic method that produces K fields with adequate connectivity, the classical ADE can accurately predict solute transport at the macrodispersion experiment site in Mississippi. This development provides great promise to accurately predict contaminant plume migration, design more effective remediation schemes, and reduce environmental risks.