Book contents
- An Introduction to Solute Transport in Heterogeneous Geologic Media
- An Introduction to Solute Transport in Heterogeneous Geologic Media
- Copyright page
- Contents
- Preface
- 1 Fundamental Concepts
- 2 Well-Mixed Models for Surface Water Quality Analysis
- 3 Well-Mixed Models for Subsurface Water Quality Analysis
- 4 Molecular Diffusion
- 5 Numerical Methods for Advection–Diffusion Equations
- 6 Shear Flow Dispersion
- 7 Solute Transport in Soil Columns
- 8 Parameter Estimation
- 9 Solute Transport in Field-Scale Aquifers
- 10 Field-Scale Solute Transport Experiments under Natural Gradient
- 11 Forced Gradient Field-Scale Tracer Experiments
- 12 High-Resolution Characterization (Tomographic Surveys)
- References
- Index
8 - Parameter Estimation
Published online by Cambridge University Press: 02 February 2023
- An Introduction to Solute Transport in Heterogeneous Geologic Media
- An Introduction to Solute Transport in Heterogeneous Geologic Media
- Copyright page
- Contents
- Preface
- 1 Fundamental Concepts
- 2 Well-Mixed Models for Surface Water Quality Analysis
- 3 Well-Mixed Models for Subsurface Water Quality Analysis
- 4 Molecular Diffusion
- 5 Numerical Methods for Advection–Diffusion Equations
- 6 Shear Flow Dispersion
- 7 Solute Transport in Soil Columns
- 8 Parameter Estimation
- 9 Solute Transport in Field-Scale Aquifers
- 10 Field-Scale Solute Transport Experiments under Natural Gradient
- 11 Forced Gradient Field-Scale Tracer Experiments
- 12 High-Resolution Characterization (Tomographic Surveys)
- References
- Index
Summary
This chapter introduces simple graphical methods to estimate advection velocity and dispersivity of solute migration through soil columns, using one-dimensional ADE presented in previous chapters. Methods of spatial and temporal moments are also introduced for solute concentration breakthroughs in one-dimensional transport and snapshots of the multi-dimensional solute migrations, respectively. Unlike automatic nonlinear regression analysis, these methods use physical insights and analytical solutions to illustrate logical approaches to estimate these parameters. The automatic regression analysis (such as Microsoft Excel introduced in Chapter 1) may find the parameters that fit the solution to the data well. However, the parameter values may not be physically possible if the estimation problem is poorly constrained (see examples in Chapter 11).
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- Publisher: Cambridge University PressPrint publication year: 2023