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Monitoring groundwater‐surface water interaction using time‐series and time‐frequency analysis of transient three‐dimensional electrical resistivity changes
Author(s) -
Johnson T. C.,
Slater L. D.,
Ntarlagiannis D.,
DayLewis F. D.,
Elwaseif M.
Publication year - 2012
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2012wr011893
Subject(s) - groundwater , electrical resistivity tomography , plume , surface water , geology , groundwater flow , electrical resistivity and conductivity , hydrology (agriculture) , time series , environmental science , soil science , aquifer , meteorology , geotechnical engineering , engineering , physics , electrical engineering , computer science , machine learning , environmental engineering
Time‐lapse resistivity imaging is increasingly used to monitor hydrologic processes. Compared to conventional hydrologic measurements, surface time‐lapse resistivity provides superior spatial coverage in two or three dimensions, potentially high‐resolution information in time, and information in the absence of wells. However, interpretation of time‐lapse electrical tomograms is complicated by the ever‐increasing size and complexity of long‐term, three‐dimensional (3‐D) time series conductivity data sets. Here we use 3‐D surface time‐lapse electrical imaging to monitor subsurface electrical conductivity variations associated with stage‐driven groundwater‐surface water interactions along a stretch of the Columbia River adjacent to the Hanford 300 near Richland, Washington, USA. We reduce the resulting 3‐D conductivity time series using both time‐series and time‐frequency analyses to isolate a paleochannel causing enhanced groundwater‐surface water interactions. Correlation analysis on the time‐lapse imaging results concisely represents enhanced groundwater‐surface water interactions within the paleochannel, and provides information concerning groundwater flow velocities. Time‐frequency analysis using the Stockwell (S) transform provides additional information by identifying the stage periodicities driving groundwater‐surface water interactions due to upstream dam operations, and identifying segments in time‐frequency space when these interactions are most active. These results provide new insight into the distribution and timing of river water intrusion into the Hanford 300 Area, which has a governing influence on the behavior of a uranium plume left over from historical nuclear fuel processing operations.