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, all...

Fiber optics passive monitoring of groundwater temperature reveals three-dimensional structures in heterogeneous aquifers

Furlanetto D.;Camporese M.
;
Schenato L.;Costa L.;Salandin P.
2024

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, all...
2024
Inglese
Inglese
14
1
NATURE PORTFOLIO
8430
smart monitoring
open
Furlanetto, D.; Camporese, M.; Schenato, L.; Costa, L.; Salandin, P.
01 CONTRIBUTO IN RIVISTA::01.01 - Articolo in rivista
info:eu-repo/semantics/article
5
262
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3512402
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