Publication Date:
2023-06-05
Description:
We are presenting an attempt to evaluate the spatial variability of geotechnical parameters in the upper
Pleistocene–Holocene alluvial deposits of Roma (Italy) by means of multivariate geostatistics.
The upper Pleistocene–Holocene alluvial deposits of Roma are sensitive to high levels of geohazard. They
occupy a sizable and significant part of the city, being the foundation for many monuments, historical
neighborhoods, and archaeological areas, and the main host of the present and future subway lines. We have
stored information from more than 2000 geotechnical boreholes crossing the alluvial deposits into a
relational database. For the present study, only the boreholes with lithologic/textural interpretation and
geotechnical information were selected. The set includes 283 boreholes and 719 samples, which have a set of
geotechnical information comprising physical properties and mechanical parameters.
Techniques of multivariate statistics and geostatistics were combined and compared to evaluate the
estimation methods of the mechanical parameters, with special reference to the drained friction angle from
direct shear test (φ′). Principal Component Analysis was applied to the dataset to highlight the relationships
between the geotechnical parameters. Through cross-validation analysis, multiple linear regression, kriging,
and cokriging were tested as estimators of φ′. Cross-validation demonstrates that the cokriging with
granulometries as auxiliary variables is the most suitable method to estimate φ′. In addition to proving that
cokriging is a good estimator of φ′, cross-validation demonstrates that input data are coherent and this
allows us to use them for estimation of geotechnical parameters, although they come from different
laboratories and different vintages.
Nevertheless, to get the same good results of cross-validation in estimation, it is necessary for granulometries
to be available at grid points. Since this information being not available at all grid points, it is expected that, in
the future, textural information can be derived in an indirect way, i.e., from lithologic/textural spatial
reconstructions.
Description:
Published
Description:
251-268
Description:
2.3. TTC - Laboratori di chimica e fisica delle rocce
Description:
JCR Journal
Description:
open
Keywords:
Alluvial deposits
;
Geotechnical properties
;
Principal Component Analysis
;
Multivariate geostatistics
;
Roma
;
05. General::05.01. Computational geophysics::05.01.04. Statistical analysis
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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