Self-potentials in partially saturated media: the importance of explicit modeling of electrode effects

Details

Serval ID
serval:BIB_CFC28C37E85C
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Self-potentials in partially saturated media: the importance of explicit modeling of electrode effects
Journal
Vadose Zone Journal
Author(s)
Jougnot D., Linde N.
ISSN-L
1539-1663
Publication state
Published
Issued date
2013
Peer-reviewed
Oui
Volume
12
Pages
-
Language
english
Notes
Jougnot2013
Abstract
Self-potential (SP) data are of interest to vadose zone hydrology
because of their direct sensitivity to water flow and ionic transport.
There is unfortunately little consensus in the literature about how
to best model SP data under partially saturated conditions, and different
approaches (often supported by one laboratory data set alone) have
been proposed. We argue that this lack of agreement can largely be
traced to electrode effects that have not been properly taken into
account. A series of drainage and imbibition experiments were considered
in which we found that previously proposed approaches to remove electrode
effects were unlikely to provide adequate corrections. Instead, we
explicitly modeled the electrode effects together with classical
SP contributions using a flow and transport model. The simulated
data agreed overall with the observed SP signals and allowed decomposing
the different signal contributions to analyze them separately. After
reviewing other published experimental data, we suggest that most
of them include electrode effects that have not been properly taken
into account. Our results suggest that previously presented SP theory
works well when considering the modeling uncertainties presently
associated with electrode effects. Additional work is warranted to
not only develop suitable electrodes for laboratory experiments but
also to assure that associated electrode effects that appear inevitable
in longer term experiments are predictable, so that they can be incorporated
into the modeling framework.
Create date
25/11/2013 18:41
Last modification date
20/08/2019 15:50
Usage data