Articles | Volume 21, issue 5
https://doi.org/10.5194/nhess-21-1467-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-1467-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Invited perspectives: Landslide populations – can they be predicted?
Fausto Guzzetti
CORRESPONDING AUTHOR
Dipartimento della Protezione Civile, Presidenza del Consiglio dei
Ministri, via Vitorchiano 2, 00189 Rome, Italy
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, via della Madonna Alta 126, 06129 Perugia, Italy
Related authors
Flavia Ferriero, Fausto Guzzetti, and Warner Marzocchi
EGUsphere, https://doi.org/10.5194/egusphere-2026-1624, https://doi.org/10.5194/egusphere-2026-1624, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Landslides cause thousands of deaths and billions in damages yearly, yet predicting them remains a major challenge. We developed a Bayesian method that estimates landslide probability as a function of rainfall, explicitly accounting for uncertainty. Applied in southern Italy, landslide probability increases gradually with rainfall, with no sharp thresholds in the triggering conditions. This approach supports a more uncertainty-aware landslide risk management.
This article is included in the Encyclopedia of Geosciences
Silvia Peruccacci, Stefano Luigi Gariano, Massimo Melillo, Monica Solimano, Fausto Guzzetti, and Maria Teresa Brunetti
Earth Syst. Sci. Data, 15, 2863–2877, https://doi.org/10.5194/essd-15-2863-2023, https://doi.org/10.5194/essd-15-2863-2023, 2023
Short summary
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ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue) is the largest catalogue of rainfall-induced landslides accurately located in space and time available in Italy. ITALICA currently lists 6312 landslides that occurred between January 1996 and December 2021. The information was collected using strict objective and homogeneous criteria. The high spatial and temporal accuracy makes the catalogue suitable for reliably defining the rainfall conditions capable of triggering future landslides.
This article is included in the Encyclopedia of Geosciences
Flavia Ferriero, Fausto Guzzetti, and Warner Marzocchi
EGUsphere, https://doi.org/10.5194/egusphere-2026-1624, https://doi.org/10.5194/egusphere-2026-1624, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Landslides cause thousands of deaths and billions in damages yearly, yet predicting them remains a major challenge. We developed a Bayesian method that estimates landslide probability as a function of rainfall, explicitly accounting for uncertainty. Applied in southern Italy, landslide probability increases gradually with rainfall, with no sharp thresholds in the triggering conditions. This approach supports a more uncertainty-aware landslide risk management.
This article is included in the Encyclopedia of Geosciences
Silvia Peruccacci, Stefano Luigi Gariano, Massimo Melillo, Monica Solimano, Fausto Guzzetti, and Maria Teresa Brunetti
Earth Syst. Sci. Data, 15, 2863–2877, https://doi.org/10.5194/essd-15-2863-2023, https://doi.org/10.5194/essd-15-2863-2023, 2023
Short summary
Short summary
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue) is the largest catalogue of rainfall-induced landslides accurately located in space and time available in Italy. ITALICA currently lists 6312 landslides that occurred between January 1996 and December 2021. The information was collected using strict objective and homogeneous criteria. The high spatial and temporal accuracy makes the catalogue suitable for reliably defining the rainfall conditions capable of triggering future landslides.
This article is included in the Encyclopedia of Geosciences
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Short summary
This is a perspective based on personal experience on whether a large number of landslides caused by a single trigger (e.g. an earthquake, an intense rainfall, a rapid snowmelt event) or by multiple triggers in a period can be predicted, in space and time, considering the consequences of slope failures.
This is a perspective based on personal experience on whether a large number of landslides...
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