The critical zone (CZ) represents the most-shallow subsurface, where the bio-, hydro-, and geospheres interact with anthropogenic activity. To characterize the thickness and lateral variations of the CZ, here we focus on the Eastern Betic Shear Zone (EBSZ), one of the most tectonically active regions in the Iberian Peninsula. Within the EBSZ, the Guadalentín Depression is a highly populated area with intensive agricultural activity, where the characterization of the CZ would provide valuable assets for land use management and seismic hazard assessments. To achieve this, we have conducted an interdisciplinary geophysical study along the eastern border of the Guadalentín Depression to characterize the CZ and the architecture of the shallow subsurface. The datasets used include Electrical Resistivity Tomography (ERT), first-arrival travel time seismic tomography, and multichannel analysis of surface waves (MASW). The geophysical datasets combined help to constrain the high-resolution structure of the subsurface and image active fault systems along four transects. The resulting geophysical models have allowed us to interpret the first ~150 m of the subsurface and has revealed: (i) the variable thickness of the CZ; (ii) the CZ relationship between the fault zone and topographic slope; and (iii) the differences in CZ thickness associated with the geological units. Our results provide a method for studying the shallow subsurface of active faults, complementing previous geological models based on paleo-seismological trenches, and can be used to improve the CZ assessment of tectonically active regions.
The geophysical data used in this study consisted of two datasets, namely electrical resistivity data and seismic data. Resistivity data were obtained from the Electrical Resistivity Tomography (ERT) method, while seismic data (Vp and Vs) were obtained from the multi-channel analysis of surface waves (MASW) and P-wave travel time tomography. The resistivity and seismic data used in this study were acquired within the INTER GEO research project, which was funded by the Spanish national research program.
Funding: J.A. is funded by grant IJC2018-036074-I and by MCIN/AEI /10.13039/501100011033. I.P. is funded by the Spanish Government and the Universidad de Salamanca (Beatriz Galindo grant BEGAL 18/00090). This project was funded by Grant 2017SGR1022 (GREG) from the Generalitat de Catalunya (AGAUR); EU (H2020) 871121 (EPOS-SP); and EIT-RawMaterias 17024 from the European Institute of Technology (EIT) (SIT4ME).
Horizon 2020 Framework Programme 871121, EIT-RawMaterias 17024
Agència de Gestió d'Ajuts Universitaris i de Recerca
Universidad de Salamanca 2017SGR1022, BEGAL 18/00090
European Institute of Technology SIT4ME
Spanish national research program
Agencia Estatal de Investigación
Generalitat de Catalunya