http://www.cnr.it/ontology/cnr/individuo/prodotto/ID298803
Reconstruction of rainfall events responsible for landslides using an algorithm (Abstract in rivista)
- Type
- Label
- Reconstruction of rainfall events responsible for landslides using an algorithm (Abstract in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Alternative label
Massimo Melillo (1), Maria Teresa Brunetti (1,2), Stefano Luigi Gariano (2), Fausto Guzzetti (1), and Silvia
Peruccacci (1) (2014)
Reconstruction of rainfall events responsible for landslides using an algorithm
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Massimo Melillo (1), Maria Teresa Brunetti (1,2), Stefano Luigi Gariano (2), Fausto Guzzetti (1), and Silvia
Peruccacci (1) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- (1) CNR IRPI, via della Madonna Alta 126, 06128 Perugia, Italy
(2) Università degli Studi di Perugia, Piazza dell'Università 1, 06123 Perugia, Italy (literal)
- Titolo
- Reconstruction of rainfall events responsible for landslides using an algorithm (literal)
- Abstract
- In Italy, intense or prolonged rainfall is the primary trigger of damaging landslides. The identification of the
rainfall conditions responsible for the initiation of landslides is a crucial issue and may contribute to reduce
landslide risk. Objective criteria for the identification of rainfall conditions that could initiate slope failures are
still lacking or ambiguous. The reconstruction of rainfall events able to trigger past landslides is usually performed
manually by expert investigators. Here, we propose an algorithm that reconstructs automatically rainfall events
from a series of hourly rainfall data. The automatic reconstruction reproduces the actions performed by an expert
investigator that adopts empirical rules to define rainfall conditions that presumably initiated the documented
landslides. The algorithm, which is implemented in R (http://www.r-project.org), performs three actions on the
data series: (i) removes isolated events with negligible amount of rainfall and random noise generated by the rain
gauge; (ii) aggregates rainfall measurements in order to obtain a sequence of distinct rainfall events; (iii) identifies
single or multiple rainfall conditions responsible for the slope failures. In particular, the algorithm calculates the
duration, D, and the cumulated rainfall, E, for rainfall events, and for rainfall conditions that have resulted in
landslides. A set of input parameters allows the automatic reconstruction of rainfall events in different physical
settings and climatic conditions.
We tested the algorithm using rainfall and landslide information available to us for Sicily, Southern Italy, in the
period between January 2002 and December 2012. The algorithm reconstructed 13,537 rainfall events and 343
rainfall conditions as possible triggers of the 163 documented landslides. Most (87.7%) of the rainfall conditions
obtained manually were reconstructed accurately.
Use of the algorithm shall contribute to an objective and reproducible definition of rainfall conditions responsible
for landslides in different geographic areas, reducing the current subjectivity inherent in the manual treatment of
the rainfall and landslide data. (literal)
- Prodotto di
- Autore CNR
Incoming links:
- Autore CNR di
- Prodotto
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi