Time evolution of self-potential anomaly sources due to organic contaminant transport by different data inversion approaches

The infiltration of organic contaminants in the subsoil may cause major effect on groundwater quality. The employ of realtime monitoring of physical and/or chemical parameters as well as of simulation modelling has proved an useful tool for predicting the underground solute transport (Cassiani and Binley, 2005). Among the commonly used geophysical methods in hydrology, the electrical methods have proved the most effective techniques for detecting soil and/or groundwater pollution due to changes in soil electrical properties resulting from biodegradation processes (Ntarlagiannis et al., 2016 and references therein). In particular, this work is focused on modelling of the transport of olive oil mill wastes (OOMWs) by using different inversion approaches of selfpotential (SP) data acquired at different times in a pilot study area (i.e. an evaporation pond of OOMWs) located in western Crete (Greece). Specifically, five SP datasets acquired from May to July 2014 along a profile located about 15 m from Keritis river have been analyzed. Quantitative interpretations of selected SP anomaly sources, likely related to zones with contamination from OOMWs, are attempted by using simple polarized source models whose parameters have to be determined. In particular, three different methods based on high resolution spectral analysis, tomographic approach and global optimization, respectively, have been used to estimate the time evolution of the source depth. A validation of the obtained results has been provided by comparison with the electrical resistivity distributions coming from time-lapse resistivity tomography surveys performed along the SP measurement profile.