The Secret to Successful Solute-Transport Modeling
Article first published online: 29 OCT 2010
Journal compilation © 2010 National Ground Water Association. No claim to original US government works
Volume 49, Issue 2, pages 144–159, March/April 2011
How to Cite
Konikow, L. F. (2011), The Secret to Successful Solute-Transport Modeling. Groundwater, 49: 144–159. doi: 10.1111/j.1745-6584.2010.00764.x
- Issue published online: 22 FEB 2011
- Article first published online: 29 OCT 2010
- Received May 2010, accepted September 2010.
Modeling subsurface solute transport is difficult—more so than modeling heads and flows. The classical governing equation does not always adequately represent what we see at the field scale. In such cases, commonly used numerical models are solving the wrong equation. Also, the transport equation is hyperbolic where advection is dominant, and parabolic where hydrodynamic dispersion is dominant. No single numerical method works well for all conditions, and for any given complex field problem, where seepage velocity is highly variable, no one method will be optimal everywhere. Although we normally expect a numerically accurate solution to the governing groundwater-flow equation, errors in concentrations from numerical dispersion and/or oscillations may be large in some cases. The accuracy and efficiency of the numerical solution to the solute-transport equation are more sensitive to the numerical method chosen than for typical groundwater-flow problems. However, numerical errors can be kept within acceptable limits if sufficient computational effort is expended. But impractically long simulation times may promote a tendency to ignore or accept numerical errors. One approach to effective solute-transport modeling is to keep the model relatively simple and use it to test and improve conceptual understanding of the system and the problem at hand. It should not be expected that all concentrations observed in the field can be reproduced. Given a knowledgeable analyst, a reasonable description of a hydrogeologic framework, and the availability of solute-concentration data, the secret to successful solute-transport modeling may simply be to lower expectations.