GNGTS 2021 - Atti del 39° Convegno Nazionale

437 GNGTS 2021 S essione 3.2 The DC resistivity and chargeability models confirm the results of the fast ERT/IP inversion. The τ section (Fig. 3c) shows intermediate shorter decay times of ~ 0.5-0.7 s in the clayey sands and higher decay times in the clean sands, since the relaxation time increases with grain size (Binley et al., 2005). The frequency exponent (Fig. 3d) is relatively low (< 0.5) in the clayey sands, which correspond to a broader grain size distribution, while higher values are related to the high resistivity and low chargeability zones corresponding to clean sands, which are expected to have a narrow grain size distribution. Conclusion In this work TD DC/IP tomography is successfully applied for the assessment of salinization on coastal aquifers, with a case study located at the Pontina Plain (Central Italy). The saline intrusion was clearly identified by high-conductive (< 5 � m) layers retrieved at different depths and distances from the sea throughout the Plain. On the other hand, MN contributes to removing the ambiguity arising in the interpretation of the resistivity models. In fact, although there is some salinity dependence, the MN values are mostly influenced by the increase of clay content. The spectral inversion of TDIP data, though on a low-resolution model, confirms the evidence of the ERT/IP models and highlights lower relaxation time and frequency exponent values on clayey sands rather than on clean sands. The assessment of the combined effect of pore fluid chemistry, saturation degree and clay content on the IP response is beyond the scope of this paper as it will be the topic of further development of this research. Acknowledgements The authors wish to thank Francesco Pugliese (“Sapienza” University of Rome) for his help during field data acquisition and the Circeo National Park authorities (Reparto Carabinieri Biodiversità di Fogliano and Ente Parco Nazionale del Circeo) for their permission to the geophysical survey. References Binley A., Slater L.D., Fukes M. and Cassiani G.; 2005: Relationship between spectral induced polarization and hydraulic properties of saturated and unsaturated sandstone. Water Resour. Res., 41 (12), W12417 De Donno G. and Cardarelli E.; 2017: VEMI: a flexible interface for 3D tomographic inversion of time- and frequency-domain electrical data in EIDORS . Near Surf. Geophys. 15 , 43-58. De Franco R., Biella G., Tosi L., Teatini P., Lozej A., Chiozzotto B. and Bassan V.; 2009: Monitoring the saltwater intrusion by time-lapse electrical resistivity tomography: The Chioggia test site (Venice Lagoon, Italy) . J. Appl. Geophys., 69 (3-4), 117-130. Fiandaca G., Ramm J., Binley A., Gazoty A., Christiansen A.V. and Auken E.; 2012: Resolving spectral information from time domain induced polarization data through 2-D inversion . Geophys. J. Int., 192 (2), 631-646. Ingeman-Nielsen T. and Baumgartner F.; 2006: CR1Dmod: AMatlab program to model 1D complex resistivity effects in electrical and electromagnetic surveys . Comput. Geosci., 32 (9), 1411-1419. Kemna A., Binley A., Cassiani G., Niederleithinger E., Revil A., Slater L., Williams K.H., Flores-Orozco A., Haegel F.-H., Hördt A., Kruschwitz S., Leroux V. and Titov K.; 2012: An overview of the spectral induced polarization method for near-surface applications . Near Surf. Geophys., 10 (6), 453-468. Madsen L.M., Fiandaca G. and Auken E.; 2020: 3-D time-domain spectral inversion of resistivity and full- decay induced polarization data—full solution of Poisson’s equation and modelling of the current waveform . Geophys. J. Int., 223 (3), 2101-2116. Oldenburg D.W. and Li Y.; 1994: Inversion of induced polarization data . Geophys., 59 (9), 1327-1341.