Luca Schiliró

Dr. Luca Schiliró

National Research Council - CNR
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2016 in Science of The Total Environment
Verified
Journal Article
Closed access
LSLuca Schiliró
Luca Schiliró
LMLorella Montrasio
Lorella Montrasio
GMGabriele Scarascia Mugnozza
Gabriele Scarascia Mugnozza

8 April 2019 in Landslides
Verified
Journal Article
Closed access
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Salvatore MartinoSalvatore Martino
Salvatore Martino
FBF. Bozzano
F. Bozzano
PCP. Caporossi
P. Caporossi
DDD. D’aNgiò
D. D’aNgiò
MSM. Della Seta
M. Della Seta
CVC. Varone
C. Varone

2 October 2015 in Landslides
Verified
Journal Article
Closed access
PDF file
LML. Montrasio
L. Montrasio
LSLuca Schiliró
Luca Schiliró
ATA. Terrone
A. Terrone

18 September 2015 in Natural Hazards and Earth System Sciences
Verified
Journal Article
Open access
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LSLuca Schiliró
Luca Schiliró
CECarlo Esposito
Carlo Esposito
GMG. Scarascia Mugnozza
G. Scarascia Mugnozza
Rainfall-induced shallow landslides are a widespread phenomenon that frequently causes substantial damage to property, as well as numerous casualties. In recent~years a wide range of physically based models have been developed to analyze the triggering process of these events. Specifically, in this paper we propose an approach for the evaluation of different shallow landslide-triggering scenarios by means of the TRIGRS (transient rainfall infiltration and grid-based slope stability) numerical model. For the validation of the model, a back analysis of the landslide event that occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on 1 October 2009 was performed, by using different methods and techniques for the definition of the input parameters. After evaluating the reliability of the model through comparison with the 2009 landslide inventory, different triggering scenarios were defined using rainfall values derived from the rainfall probability curves, reconstructed on the basis of daily and hourly historical rainfall data. The results emphasize how these phenomena are likely to occur in the area, given that even short-duration (1–3 h) rainfall events with a relatively low return period (e.g., 10–20~years) can trigger numerous slope failures. Furthermore, for the same rainfall amount, the daily simulations underestimate the instability conditions. The high susceptibility of this area to shallow landslides is testified by the high number of landslide/flood events that have occurred in the past and are summarized in this paper by means of archival research. Considering the main features of the proposed approach, the authors suggest that this methodology could be applied to different areas, even for the development of landslide early warning systems.

1 January 2018 in Geomatics, Natural Hazards and Risk
Verified
Journal Article
Open access
LSLuca Schiliró
Luca Schiliró
ACAndrea CEVASCO
Andrea CEVASCO
CECarlo Esposito
Carlo Esposito
GMGabriele Scarascia Mugnozza
Gabriele Scarascia Mugnozza
In the last years, great efforts have been made to improve the assessment of the temporal and spatial occurrence of rainfall-induced shallow landslides. Therefore, in this paper we used a physically based stability model (TRIGRS) in order to reproduce the landslide event occurred in the Monterosso catchment (Cinque Terre, Eastern Liguria, Italy) on 25 October 2011. The input parameters of the numerical model have been evaluated taking into account the land-use setting and paying specific attention to the evaluation of the spatial variation of soil thickness on terraced areas. The resulting safety factor maps have been compared with the inventory map of the landslides triggered during the event. The simulation results, which have been obtained also considering four different spatial resolutions of the digital terrain model, emphasize the influence of land use in shallow landslide occurrence and indicate the importance of a realistic spatial variation of soil thickness to enhance the reliability of the model. Finally, different triggering scenarios have been defined using hourly rainfall values statistically derived from historical data. The results indicate the proneness of the area to shallow landsliding, given that rainfall events with a relatively low return period (e.g. 25 years) can trigger numerous slope failures.

31 January 2020 in Landslides
Verified
Journal Article
Closed access
PDF file
Salvatore MartinoSalvatore Martino
Salvatore Martino
BAB. Antonielli
B. Antonielli
FBF. Bozzano
F. Bozzano
PCP. Caprari
P. Caprari
MDMarco Emanuele Discenza
Marco Emanuele Discenza
LSLuca Schiliró
Luca Schiliró