Imaging Rainfall Infiltration Processes with the Time-Lapse Electrical Resistivity Imaging Method

Gang Zhang, Gui Bin Zhang, Chien chih Chen, Ping Yu Chang, Tzu Pin Wang, Horng Yuan Yen, Jia Jyun Dong, Chuen Fa Ni, Su Chin Chen, Chao Wei Chen, Zheng yuan Jia

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Electrical Resistivity Imaging (ERI) was carried out continuously for 10 days to map the subsurface resistivity distribution along a potentially hazardous hillslope at the Jieshou Junior High School in Taoyuan, Taiwan. The reliability of the inverted resistivity structures down to about 25 m depth was examined with synthetic modeling using the same electrode arrangements installed on land surface as in field surveys, together with a DOI (depth-of-investigation) index calculated from the ERI data. The subsurface resistivity distribution is consistent with results from well logging. These ERI recordings were taken daily and provided highly resolved imagery of the resistivity distribution underground and illustrated the dynamical fluid-flow behavior due to heavy rainfall infiltration. Using Archie’s law, the resistivity distribution was transformed into a map of relative water saturation (RWS), which is strongly correlated with the rainfall infiltration process. We then found that the averaged RWS is significantly correlated with daily precipitation. Our observations indicate that time-lapse ERI is effective in monitoring subterraneous rainfall infiltration; moreover, the preferential flow paths can be delineated according to the changes in averaged RWS derived from the ERI data.

Original languageEnglish
Pages (from-to)2227-2239
Number of pages13
JournalPure and Applied Geophysics
Volume173
Issue number6
DOIs
StatePublished - 1 Jun 2016

Keywords

  • Archie’s law
  • depth-of-investigation
  • Electrical resistivity imaging
  • preferential path
  • rainfall infiltration

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