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Prof. Stefano Bernardinetti
GEOexplorer Impresa Sociale S.r.l.

Basic Info


Research Keywords & Expertise

0 Geophysics
0 Exploration Geophysics
0 Hydrogeochemistry and geochemical modelling of groundwater
0 Data mining and pattern recognition
0 Neural network and machine learning

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Short Biography

Stefano Bernardinetti is an environmental engineer expert in applied geophysics for the exploration and geological-geotechnical characterization of the subsoil, the hydrogeological characterization and for investigations related to the interaction of current and past anthropic activities. Since 2019 he has had a PhD in Applied Geophysics, Disciplinary Sector GEO / 11, obtained at the Doctoral School of the University of Cagliari. Since 2015, he has been part of the Center for GeoTechnologies of University of Siena, where he mainly deals with geophysical surveys and research projects related to the study of the water resource and characterization of aquifers: over the years he has developed integrated methods of hydrogeophysical characterizations aimed at the zoning of aquifers both from one point from a geophysical and hydrogeochemical point of view.

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Journal article
Published: 18 August 2021 in Applied Sciences
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The hydrogeochemical characteristics of the significant subterranean water body between “Cecina River and San Vincenzo” (Italy) was evaluated using multivariate statistical analysis methods, like principal component analysis and self-organizing maps (SOMs), with the objective to study the spatiotemporal relationships of the aquifer. The dataset used consisted of the chemical composition of groundwater samples collected between 2010 and 2018 at 16 wells distributed across the whole aquifer. For these wells, all major ions were determined. A self-organizing map of 4 × 8 was constructed to evaluate spatiotemporal changes in the water body. After SOM clustering, we obtained three clusters that successfully grouped all data with similar chemical characteristics. These clusters can be viewed to reflect the presence of three water types: (i) Cluster 1: low salinity/mixed waters; (ii) Cluster 2: high salinity waters; and (iii) Cluster 3: low salinity/fresh waters. Results showed that the major ions had the greater influence over the groundwater chemistry, and the difference in their concentrations allowed the definition of three clusters among the obtained SOM. Temporal changes in cluster assignment were only observed in two wells, located in areas more susceptible to changes in the water table levels, and therefore, hydrodynamic conditions. The result of the SOM clustering was also displayed using the classical hydrochemical approach of the Piper plot. It was observed that these changes were not as easily identified when the raw data were used. The spatial display of the clustering results, allowed the evaluation in a hydrogeological context in a quick and cost-effective way. Thus, our approach can be used to quickly analyze large datasets, suggest recharge areas, and recognize spatiotemporal patterns.

ACS Style

Alessia Bastianoni; Enrico Guastaldi; Alessio Barbagli; Stefano Bernardinetti; Andrea Zirulia; Mariantonietta Brancale; Tommaso Colonna. Multivariate Analysis Applied to Aquifer Hydrogeochemical Evaluation: A Case Study in the Coastal Significant Subterranean Water Body between “Cecina River and San Vincenzo”, Tuscany (Italy). Applied Sciences 2021, 11, 7595 .

AMA Style

Alessia Bastianoni, Enrico Guastaldi, Alessio Barbagli, Stefano Bernardinetti, Andrea Zirulia, Mariantonietta Brancale, Tommaso Colonna. Multivariate Analysis Applied to Aquifer Hydrogeochemical Evaluation: A Case Study in the Coastal Significant Subterranean Water Body between “Cecina River and San Vincenzo”, Tuscany (Italy). Applied Sciences. 2021; 11 (16):7595.

Chicago/Turabian Style

Alessia Bastianoni; Enrico Guastaldi; Alessio Barbagli; Stefano Bernardinetti; Andrea Zirulia; Mariantonietta Brancale; Tommaso Colonna. 2021. "Multivariate Analysis Applied to Aquifer Hydrogeochemical Evaluation: A Case Study in the Coastal Significant Subterranean Water Body between “Cecina River and San Vincenzo”, Tuscany (Italy)." Applied Sciences 11, no. 16: 7595.

Journal article
Published: 11 February 2021 in Geosciences
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In this paper, we present results of tectonic and geophysical investigations in the Kenya Rift valley, in the Nakuru area. We compiled a detailed geological map of the area based on published earlier works, well data and satellite imagery. The map was then integrated with original fieldwork and cross sections were constructed. In key areas, we then performed geophysical survey using Electrical Resistivity Tomography (ERT), Hybrid Source Audio MagnetoTelluric (HSAMT), and single station passive seismic measurements (HVSR). In the study area, a volcano-sedimentary succession of the Neogene-Quaternary age characterized by basalts, trachytes, pyroclastic rocks, and tephra with intercalated lacustrine and fluvial deposits crops out. Faulting linked with rift development is evident and occurs throughout the area crosscutting all rock units. We show a rotation of the extension in this portion of the Kenya rift with the NE–SW extension direction of a Neogene-Middle Pleistocene age, followed by the E–W extension direction of an Upper Pleistocene-Present age. Geophysical investigations allowed to outline main lithostratigraphic units and tectonic features at depth and were also useful to infer main cataclasites and fractured rock bodies, the primary paths for water flow in rocks. These investigations are integrated in a larger EU H2020 Programme aimed to produce a geological and hydrogeological model of the area to develop a sustainable water management system.

ACS Style

Paolo Conti; Marco Pistis; Stefano Bernardinetti; Alessio Barbagli; Andrea Zirulia; Lisa Serri; Tommaso Colonna; Enrico Guastaldi; Giorgio Ghiglieri. Tectonic Setting of the Kenya Rift in the Nakuru Area, Based on Geophysical Prospecting. Geosciences 2021, 11, 80 .

AMA Style

Paolo Conti, Marco Pistis, Stefano Bernardinetti, Alessio Barbagli, Andrea Zirulia, Lisa Serri, Tommaso Colonna, Enrico Guastaldi, Giorgio Ghiglieri. Tectonic Setting of the Kenya Rift in the Nakuru Area, Based on Geophysical Prospecting. Geosciences. 2021; 11 (2):80.

Chicago/Turabian Style

Paolo Conti; Marco Pistis; Stefano Bernardinetti; Alessio Barbagli; Andrea Zirulia; Lisa Serri; Tommaso Colonna; Enrico Guastaldi; Giorgio Ghiglieri. 2021. "Tectonic Setting of the Kenya Rift in the Nakuru Area, Based on Geophysical Prospecting." Geosciences 11, no. 2: 80.

Journal article
Published: 30 June 2017 in Acque Sotterranee - Italian Journal of Groundwater
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The need to obtain a detailed hydrogeological characterization of the subsurface and its interpretation for the groundwater resources management, often requires to apply several and complementary geophysical methods. The goal of the approach in this paper is to provide a unique model of the aquifer by synthesizing and optimizing the information provided by several geophysical methods. This approach greatly reduces the degree of uncertainty and subjectivity of the interpretation by exploiting the different physical and mechanic characteristics of the aquifer. The studied area, into the municipality of Laterina (Arezzo, Italy), is a shallow basin filled by lacustrine and alluvial deposits (Pleistocene and Olocene epochs, Quaternary period), with alternated silt, sand with variable content of gravel and clay where the bottom is represented by arenaceous-pelitic rocks (Mt. Cervarola Unit, Tuscan Domain, Miocene epoch). This shallow basin constitutes the unconfined superficial aquifer to be exploited in the nearly future. To improve the geological model obtained from a detailed geological survey we performed electrical resistivity and P wave refraction tomographies along the same line in order to obtain different, independent and integrable data sets. For the seismic data also the reflected events have been processed, a remarkable contribution to draw the geologic setting. Through the k-means algorithm, we perform a cluster analysis for the bivariate data set to individuate relationships between the two sets of variables. This algorithm allows to individuate clusters with the aim of minimizing the dissimilarity within each cluster and maximizing it among different clusters of the bivariate data set. The optimal number of clusters “K”, corresponding to the individuated geophysical facies, depends to the multivariate data set distribution and in this work is estimated with the Silhouettes. The result is an integrated tomography that shows a finite number of homogeneous geophysical facies, which therefore permits to distinguish and interpret the porous aquifer in a quantitative and objective way.

ACS Style

Stefano Bernardinetti; Stefano Maraio; Pier Paolo Gennaro Bruno; Valentina Cicala; Serena Minucci; Miriana Giannuzzi; Marilena Trotta; Francesco Curedda; Simone Febo; Matteo Vacca; Enrico Guastaldi; Tommaso Colonna; Filippo Bonciani; Emanuele Tufarolo; Fabio Brogna; Andrea Zirulia; Omar Milighetti. Potential shallow aquifers characterization through an integrated geophysical method: multivariate approach by means of k-means algorithms. Acque Sotterranee - Italian Journal of Groundwater 2017, 6, 1 .

AMA Style

Stefano Bernardinetti, Stefano Maraio, Pier Paolo Gennaro Bruno, Valentina Cicala, Serena Minucci, Miriana Giannuzzi, Marilena Trotta, Francesco Curedda, Simone Febo, Matteo Vacca, Enrico Guastaldi, Tommaso Colonna, Filippo Bonciani, Emanuele Tufarolo, Fabio Brogna, Andrea Zirulia, Omar Milighetti. Potential shallow aquifers characterization through an integrated geophysical method: multivariate approach by means of k-means algorithms. Acque Sotterranee - Italian Journal of Groundwater. 2017; 6 (2):1.

Chicago/Turabian Style

Stefano Bernardinetti; Stefano Maraio; Pier Paolo Gennaro Bruno; Valentina Cicala; Serena Minucci; Miriana Giannuzzi; Marilena Trotta; Francesco Curedda; Simone Febo; Matteo Vacca; Enrico Guastaldi; Tommaso Colonna; Filippo Bonciani; Emanuele Tufarolo; Fabio Brogna; Andrea Zirulia; Omar Milighetti. 2017. "Potential shallow aquifers characterization through an integrated geophysical method: multivariate approach by means of k-means algorithms." Acque Sotterranee - Italian Journal of Groundwater 6, no. 2: 1.