Ricerc@Sapienza

This paper deals with monitoring systems to manage the risk due to fast slope failures
that involve rock masses, in which important elements (such as infrastructures or cultural heritages,
among the others) are exposed. Three different approaches for data analysis were here compared
to evaluate their suitability for detecting mutual relations among destabilising factors, acting on
different time windows, and induced strain effects on rock masses: (i) an observation-based approach
(OBA), (ii) a statistics-based approach (SBA) and (iii) a semi-empirical approach (SEA). For these
purposes, a test-site has been realised in an abandoned quarry in Central Italy by installing a
multi-parametric monitoring sensor network on a rock wall able to record strain effects induced by
natural and anthropic forcing actions (like as temperature, rainfall, wind and anthropic vibrations).
The comparison points out that the considered approaches allow one to identify forcing actions,
responsible for the strain effects on the rock mass over several time windows, regarding a specific
size (i.e., rock block dimensional scale). The OBA was more suitable for computing the relations over
short- to medium time windows, as well as the role of impulsive actions (i.e., hourly to seasonal
and/or instantaneous). The SBA was suitable for computing the relations over medium- to long time
windows (i.e., daily to seasonal), also returning the time lag between forcing actions and induced
strains using the cross-correlation statistical function. Last, the SEA was highly suitable for detecting
irreversible strain effects over long- to very long-time windows (i.e., plurennial).