Open AccessElectrical Resistivity for Characterization and Infiltration Monitoring beneath a Managed Aquifer Recharge Pond
Author(s) -
Mawer Chloe,
Kitanidis Peter,
Pidlisecky Adam,
Knight Rosemary
Publication year - 2013
Publication title -
vadose zone journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.036
H-Index - 81
ISSN - 1539-1663
DOI - 10.2136/vzj2011.0203
Subject(s) - infiltration (hvac) , hydraulic conductivity , groundwater recharge , aquifer , clogging , electrical resistivity and conductivity , soil science , vadose zone , spatial variability , logarithm , geology , inversion (geology) , hydrology (agriculture) , environmental science , groundwater , geotechnical engineering , soil water , geomorphology , meteorology , engineering , mathematics , geography , statistics , mathematical analysis , electrical engineering , archaeology , structural basin
Efficiency of managed aquifer recharge (MAR) via surface infiltration ponds relies heavily on the properties and processes of the unsaturated zone. The spatial and temporal resolutions needed in data for monitoring such processes are higher than typical hydrologic data can provide. Recently developed direct‐push resistivity probes can be located in the base of a MAR pond and used to obtain vertical electrical conductivity profiles with high spatial and temporal resolutions. In this study, we developed an inversion algorithm that uses a vertical electrical conductivity profile and auxiliary hydrologic data to estimate the van Genuchten parameters and saturated hydraulic conductivity of a homogeneous unsaturated zone. Using a synthetic case, we analyzed the method's accuracy and sensitivity to temporal and spatial resolutions in data. We then derived a new relationship for using the parameter estimation and electrical conductivity data to estimate infiltration rates and pond bottom clogging in situ in real time, extending electrical resistivity as a method for gaining qualitative infiltration information to a tool for quantitative infiltration rate monitoring. We found that we were able to best estimate the logarithm of the saturated hydraulic conductivity, which was within 5% of the true value for all cases. The van Genuchten parameter α was the least accurately predicted parameter, deviating at most 22% from the true value. We found that we could estimate infiltration rates and pond bottom clogging with a level of accuracy appropriate for use in modeling and management decisions, in most cases to within 11% of the true value.