Monitoring time evolution of self-potential anomaly sources by a new global optimization approach. Application to organic contaminant transport

Abstract

Complex interactions among organic contaminant, soil and water change the electrical properties of the subsurface often causing strong self-potential (SP) anomalies, whose monitoring is proposed as a useful tool to determine the temporal evolution of the contaminant plumes. In the present study, we focus on the problem of organic contaminant transport related to olive oil mill wastes (OOMWs), which represent an important environmental problem in Mediterranean countries. The diffusion of the contaminants into the subsurface is studied by using a global optimization procedure on SP data measured, at different times, in a well-studied contaminated pilot area located next to the Keritis river in western Crete island (Greece). Despite the complex hydrogeological conditions related to the proximity to both the Keritis river and a small seasonal stream, the analysis of five SP datasets acquired along the same profile shows that the proposed hybrid Genetic-Price algorithm is able to reproduce the main features of the SP signals, thus identifying probable multiple SP anomaly sources and their changes over time. In particular, preferential horizontal pathways of OOMW and their migration in the vadose zone during the summer season were identified, providing some useful insights for future planning of remediation actions.