Abstract
Alluvial aquifers often exhibit highly conductive embedded formations that can act as preferential pathways for the transport of solutes. In this context, a detailed subsurface characterization becomes crucial for an effective monitoring of groundwater quality and early detection of contaminants. However, small-scale heterogeneities are seldom detected by traditional nondestructive investigations. Heat propagation in porous media can be a relatively inexpensive tracer for groundwater flow, potentially offering valuable information in various applications. In this study, we applied passive Fiber Optics Distributed Temperature Sensing (FO-DTS) to a group of observation wells in a highly heterogeneous phreatic aquifer to uncover structures with different hydraulic conductivity, relying on their response to temperature fluctuations triggered by natural and anthropogenic forcings. A comprehensive data analysis approach, combining statistical methods and physics-based numerical modeling, allowed for a three-dimensional characterization of the subsurface at the experimental site with unprecedentedly high resolution.