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STATISTICAL METHODOLOGY FOR ESTIMATING TRANSPORT PARAMETERS: THEORY AND APPLICATIONS TO ONE-DOMENSIONAL ADVECTIVE-DISPERSIVE SYSTEMS.

Water Resources Research

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Abstract

A simulation nonlinear multiple-regression methodology for estimating parameters that characterize the transport of contaminants is developed and demonstrated. Finite difference containment transport simulation is combined with a nonlinear weighted least squares multiple-regression procedure. The technique provides optimal parameter estimates and gives statistics for assessing the reliability of these estimates under certain general assumptions about the distributions of the random measurement errors. Monte Carlo analysis is used to estimate parameter reliability for a hypothetical homogeneous soil column for which concentration data contain large random measurement errors. The value of data collected spatially versus data collected temporally was investigated for estimation of velocity, dispersion coefficient, effective porosity, first-order decay rate, and zero-order production. The use of spatial data gave estimates that were 2-3 times more reliable than estimates based on temporal data for all parameters except velocity. (Estimated author abstract) Refs.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
STATISTICAL METHODOLOGY FOR ESTIMATING TRANSPORT PARAMETERS: THEORY AND APPLICATIONS TO ONE-DOMENSIONAL ADVECTIVE-DISPERSIVE SYSTEMS.
Series title:
Water Resources Research
Volume
22
Issue:
8
Year Published:
1986
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Water Resources Research
First page:
1303
Last page:
1315
Number of Pages:
13