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Characterizing Stream‐Aquifer Exchanges with Self‐Potential Measurements
Author(s) -
Valois Remi,
Cousquer Yohann,
Schmutz Myriam,
Pryet Alexandre,
Delbart Célestine,
Dupuy Alain
Publication year - 2017
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/gwat.12594
Subject(s) - aquifer , electrokinetic phenomena , hydraulic conductivity , groundwater , groundwater flow , flow (mathematics) , hydrology (agriculture) , soil science , geology , streams , environmental science , geotechnical engineering , computer science , mechanics , soil water , chemistry , computer network , physics
Characterizing the interactions between streams and aquifers is a major challenge in hydrology. Electrical self‐potential (SP) is sensitive to groundwater flow through the electrokinetic effect, which is proportional to Darcy velocity. SP surveys have been extensively used for the characterization of seepage flow in a variety of contexts. But to our knowledge, a model coupling SP and groundwater flow has never been implemented for the study of stream‐aquifer interactions. To address the issue, we first implemented a two‐dimensional model to a synthetic stream‐aquifer cross section. Results underline the very distinct nature of SP profiles in gaining or losing stream conditions. Second, we presented a field application in a transect crossing a stream in losing conditions. The coupled model successfully reproduced the observed SP profile. This inverse modeling of the SP signal provides quantitative data on hydrodynamic parameters (hydraulic conductivity, hydraulic heads) and geophysical parameters (coupling coefficient). Nevertheless, all relevant parameters cannot be uniquely estimated without precise prior information on at least some of these parameters. Our results confirm the potential of SP surveys on the characterization of stream‐aquifer exchanges. Recommendations on the collection of high‐quality data are also provided, along with a description of the contexts in which the methodology is likely to perform well.