Doctoral Dissertations

Date of Award

12-1995

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Civil Engineering

Major Professor

James L. Smoot

Committee Members

Chris D. Cox, Terry L. Miller, Ronald E. Yoder

Abstract

The Gaussian plume model is based on the assumptions that (1) the contaminant concentration profile in a porous medium can be represented by a Gaussian distribution and (2) that the contaminant plume can be modeled by a combination of discrete releases from a point source. The basic three-dimensional Gaussian equation is modified to reflect the transport processes encountered in groundwater contaminant transport, such as retardation and decay. The major advantages of the Gaussian plume model are demonstrated when modeling sources that are not point sources (line, area, or volume sources) or are not instantaneous (steady state or continuous). For the various spatial source configurations, the Gaussian plume model takes advantage of the observation that the plume from a non-point source cannot easily be distinguished from the plume from a point source located at a further distance from the observation point. This point source, or "virtual image," is then used for all calculations, eliminating the need to integrate across the source. The Gaussian plume approach for non-instantaneous sources are made similar to those for non-point sources. A continuous release is divided into discrete releases and the plume is modeled as the sum of those discrete releases. The Gaussian plume model provides the same problem-solving capability provided by analytical solution but with less mathematical complexity and computational requirements. In addition, the Gaussian plume model offers solutions not readily available through analytical solutions, such as volumetric sources and the use of spatially-dependent diffusivities. All of this is obtained with little or no loss of accuracy when compared to analytical solutions. The Gaussian plume model is not intended to replace the traditional analytical or numerical solutions. Rather, it extends the range of applications beyond those found in the analytical solutions without requiring the complexity of the numerical solutions. In this sense, it partially fills the gap between the easy to use, but limited capabilities of analytical solutions and the powerful, but demanding capabilities of numerical solutions. The Gaussian plume model also extends the working medium for the model. Both numerical models and the more complex analytical models (such as three-dimensional solutions) are difficult to program using spreadsheet software. The Gaussian approach can be easily implemented in spreadsheet form, bringing to the user the full range of options and utilities available with current spreadsheets, including extensive graphical and statistical capabilities.

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