Articles | Volume 15, issue 7
https://doi.org/10.5194/essd-15-2863-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-2863-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
11 Jul 2023
Data description article |
| 11 Jul 2023
| 11 Jul 2023
The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy
Silvia Peruccacci
CORRESPONDING AUTHOR
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Stefano Luigi Gariano
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Massimo Melillo
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Monica Solimano
Agenzia Regionale per la Protezione dell'Ambiente Ligure, Genoa, 16149, Italy
Fausto Guzzetti
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Presidenza del Consiglio dei Ministri, Dipartimento della Protezione Civile, Rome, 00189, Italy
Maria Teresa Brunetti
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, 06128, Italy
Related authors
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
Short summary
Short summary
We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci
Hydrol. Earth Syst. Sci., 25, 3267–3279, https://doi.org/10.5194/hess-25-3267-2021, https://doi.org/10.5194/hess-25-3267-2021, 2021
Short summary
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.
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.
Stefano Luigi Gariano and Olga Petrucci
EGUsphere, https://doi.org/10.5194/egusphere-2026-621, https://doi.org/10.5194/egusphere-2026-621, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Long-term changes in rainfall conditions triggering landslides in Calabria (Southern Italy) over 1921–2020 are analysed through a dynamic approach in rainfall threshold definition. Shifts in seasonality and a decreasing trend in triggering rainfall are observed over the years, suggesting an increased propensity of the territory to generate landslides, even with less severe triggering rainfall in recent decades. The work highlights the essential role of landslide data collection and archiving.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
Short summary
Short summary
We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci
Hydrol. Earth Syst. Sci., 25, 3267–3279, https://doi.org/10.5194/hess-25-3267-2021, https://doi.org/10.5194/hess-25-3267-2021, 2021
Short summary
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.
Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 21, 1467–1471, https://doi.org/10.5194/nhess-21-1467-2021, https://doi.org/10.5194/nhess-21-1467-2021, 2021
Short summary
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.
Cited articles
Andres, N. and Badoux, A.:
The Swiss flood and landslide damage database: Normalisation and trends, J. Flood Risk Manag., 12, e12510, https://doi.org/10.1111/jfr3.12510, 2019.
Belair, G. M., Jones, E. S., Slaughter, S. L., and Mirus, B. B.:
Landslide Inventories across the United States version 2, Geological Survey data release, https://doi.org/10.5066/P9FZUX6N, 2022.
Berti, M., Martina, M. L. V., Franceschini, S., Pignone, S., Simoni, A., and Pizziolo, M.:
Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach, J. Geophys. Res.-Earth, 117, F04006, https://doi.org/10.1029/2012JF002367, 2012.
Bianchi, C. and Salvati, P.:
Rapporto Periodico sul Rischio posto alla Popolazione italiana da Frane e Inondazioni. Anno 2022, Istituto di Ricerca per la Protezione Idrogeologica (IRPI), Consiglio Nazionale delle Ricerche (CNR), https://doi.org/10.30437/REPORT2021, 2023 (in Italian).
Bíl, M., Raška, P., Dolák, L., and Kubeček, J.:
CHILDA – Czech Historical Landslide Database, Nat. Hazards Earth Syst. Sci., 21, 2581–2596, https://doi.org/10.5194/nhess-21-2581-2021, 2021.
Brunetti, M. T., Melillo, M., Gariano, S. L., Guzzetti, F., Bartolini, D., Brutti, F., Bianchi, C., Calzolari, C., Denti, B., Gioia, E., Luciani, S., Martinotti, M. E., Palladino, M. R., Pisano, L., Roccati, A., Solimano, M., Vennari, C., Vessia, G., Viero, A., and Peruccacci, S.:
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue), Zenodo [data set], https://doi.org/10.5281/zenodo.8009366, 2023.
Calvello, M. and Pecoraro, G.:
FraneItalia: a catalog of recent Italian landslides, Geoenvironmental Disasters, 5, 13, https://doi.org/10.1186/s40677-018-0105-5, 2018.
Corominas, J., Einstein, H., Davis, T., Strom, A., Zuccaro, G., Nadim, F., and Verdel, T.:
Glossary of Terms on Landslide Hazard and Risk, in: Engineering Geology for Society and Territory – Volume 2, edited by: Lollino, G., Giordan, D., Crosta, G. B., Corominas, J., Azzam, R., Wasowski, J., and Sciarra, N., Springer International Publishing, Cham, 1775–1779, https://doi.org/10.1007/978-3-319-09057-3_314, 2015.
Cruden, D. and Varnes, D.:
Landslide Types and Processes, Chapter 3 in Landslides: Investigation and Mitigation. Special Report 247, National Research Council, Spec. Rep. Natl. Res. Counc. Transp. Res. Board, Washington, DC, 36–75, 1996.
Damm, B. and Klose, M.:
Landslide Database for the Federal Republic of Germany: A Tool for Analysis of Mass Movement Processes, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer Cham, 787–792, https://doi.org/10.1007/978-3-319-05050-8_121, 2014.
Damm, B. and Klose, M.:
The landslide database for Germany: Closing the gap at national level, Geomorphology, 249, 82–93, https://doi.org/10.1016/j.geomorph.2015.03.021, 2015.
Devoli, G., Strauch, W., Chávez, G., and Høeg, K.:
A landslide database for Nicaragua: a tool for landslide-hazard management, Landslides, 4, 163–176, https://doi.org/10.1007/s10346-006-0074-8, 2007.
Fioravanti, G., Fraschetti, P., Lena, F., Perconti, W., Piervitali, E.:
I normali climatici 1991–2020 di temperatura e precipitazione in Italia, Stato dell'Ambiente 99/2022, ISPRA, Rome, Italy, ISBN 978-88-448-1120-4, 2022 (in Italian).
Foster, C., Pennington, C. V. L., Culshaw, M. G., and Lawrie, K.:
The national landslide database of Great Britain: development, evolution and applications, Environ. Earth Sci., 66, 941–953, https://doi.org/10.1007/s12665-011-1304-5, 2012.
Franceschini, R., Rosi, A., Catani, F., and Casagli, N.:
Exploring a landslide inventory created by automated web data mining: the case of Italy, Landslides, 19, 841–853, https://doi.org/10.1007/s10346-021-01799-y, 2022a.
Franceschini, R., Rosi, A., del Soldato, M., Catani, F., and Casagli, N.:
Integrating multiple information sources for landslide hazard assessment: the case of Italy, Sci. Rep., 12, 20724, https://doi.org/10.1038/s41598-022-23577-z, 2022b.
Froude, M. J. and Petley, D. N.:
Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
Guzzetti, F.:
Landslide fatalities and the evaluation of landslide risk in Italy, Eng. Geol., 58, 89–107, https://doi.org/10.1016/S0013-7952(00)00047-8, 2000.
Guzzetti, F. and Tonelli, G.:
Information system on hydrological and geomorphological catastrophes in Italy (SICI): a tool for managing landslide and flood hazards, Nat. Hazards Earth Syst. Sci., 4, 213–232, https://doi.org/10.5194/nhess-4-213-2004, 2004.
Guzzetti, F., Cardinali, M., and Reichenbach, P.:
The AVI project: A bibliographical and archive inventory of landslides and floods in Italy, Environ. Manage., 18, 623–633, https://doi.org/10.1007/BF02400865, 1994.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.:
Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., Marchesini, I., Rossi, M., and Melillo, M.:
Geographical landslide early warning systems, Earth-Sci. Rev., 200, 102973, https://doi.org/10.1016/j.earscirev.2019.102973, 2020.
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., and Melillo, M.:
Rainfall and landslide initiation, in: Rainfall, edited by: Morbidelli, R., Elsevier, 427–450, https://doi.org/10.1016/B978-0-12-822544-8.00012-3, 2022.
Haque, U., Blum, P., da Silva, P. F., Andersen, P., Pilz, J., Chalov, S. R., Malet, J.-P., Auflič, M. J., Andres, N., Poyiadji, E., Lamas, P. C., Zhang, W., Peshevski, I., Pétursson, H. G., Kurt, T., Dobrev, N., García-Davalillo, J. C., Halkia, M., Ferri, S., Gaprindashvili, G., Engström, J., and Keellings, D.:
Fatal landslides in Europe, Landslides, 13, 1545–1554, https://doi.org/10.1007/s10346-016-0689-3, 2016.
Herrera, G., Mateos, R. M., García-Davalillo, J. C., Grandjean, G., Poyiadji, E., Maftei, R., Filipciuc, T.-C., Jemec Auflič, M., Jež, J., Podolszki, L., Trigila, A., Iadanza, C., Raetzo, H., Kociu, A., Przyłucka, M., Kułak, M., Sheehy, M., Pellicer, X. M., McKeown, C., Ryan, G., Kopačková, V., Frei, M., Kuhn, D., Hermanns, R. L., Koulermou, N., Smith, C. A., Engdahl, M., Buxó, P., Gonzalez, M., Dashwood, C., Reeves, H., Cigna, F., Liščák, P., Pauditš, P., Mikulėnas, V., Demir, V., Raha, M., Quental, L., Sandić, C., Fusi, B., and Jensen, O. A.:
Landslide databases in the Geological Surveys of Europe, Landslides, 15, 359–379, https://doi.org/10.1007/s10346-017-0902-z, 2018.
Hess, J., Rickli, C., McArdell, B., and Stähli, M.:
Investigating and Managing Shallow Landslides in Switzerland, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer Cham, 805–808, https://doi.org/10.1007/978-3-319-05050-8_124, 2014.
Innocenzi, E., Greggio, L., Frattini, P., and de Amicis, M.:
A Web-Based Inventory of Landslides Occurred in Italy in the Period 2012–2015, in: Advancing Culture of Living with Landslides, edited by: Mikos, M., Tiwari, B., Yin, Y., and Sassa, K., Springer International Publishing, Cham, 1127–1133, https://doi.org/10.1007/978-3-319-53498-5_128, 2017.
Jaedicke, C., Lied, K., and Kronholm, K.:
Integrated database for rapid mass movements in Norway, Nat. Hazards Earth Syst. Sci., 9, 469–479, https://doi.org/10.5194/nhess-9-469-2009, 2009.
Kirschbaum, D., Stanley, T., and Zhou, Y.:
Spatial and temporal analysis of a global landslide catalog, Geomorphology, 249, 4–15, https://doi.org/10.1016/j.geomorph.2015.03.016, 2015.
Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., and Lerner-Lam, A.:
A global landslide catalog for hazard applications: method, results, and limitations, Nat. Hazards, 52, 561–575, https://doi.org/10.1007/s11069-009-9401-4, 2010.
Komac, M. and Hribernik, K.:
Slovenian national landslide database as a basis for statistical assessment of landslide phenomena in Slovenia, Geomorphology, 249, 94–102, https://doi.org/10.1016/j.geomorph.2015.02.005, 2015.
Luetzenburg, G., Svennevig, K., Bjørk, A. A., Keiding, M., and Kroon, A.:
A national landslide inventory for Denmark, Earth Syst. Sci. Data, 14, 3157–3165, https://doi.org/10.5194/essd-14-3157-2022, 2022.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., Roccati, A., and Guzzetti, F.:
A tool for the automatic calculation of rainfall thresholds for landslide occurrence, Environ. Model. Softw., 105, 230–243, https://doi.org/10.1016/j.envsoft.2018.03.024, 2018.
Mrozek, T., Kułak, M., Grabowski, D., and Wójcik, A.:
Landslide Counteracting System (SOPO): Inventory Database of Landslides in Poland, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer Cham, 815–820, https://doi.org/10.1007/978-3-319-05050-8_126, 2014.
Palladino, M. R., Viero, A., Turconi, L., Brunetti, M. T., Peruccacci, S., Melillo, M., Luino, F., Deganutti, A. M., and Guzzetti, F.:
Rainfall thresholds for the activation of shallow landslides in the Italian Alps: the role of environmental conditioning factors, Geomorphology, 303, 53–67, https://doi.org/10.1016/j.geomorph.2017.11.009, 2018.
Pennington, C., Freeborough, K., Dashwood, C., Dijkstra, T., and Lawrie, K.:
The National Landslide Database of Great Britain: Acquisition, communication and the role of social media, Geomorphology, 249, 44–51, https://doi.org/10.1016/j.geomorph.2015.03.013, 2015.
Peruccacci, S., Brunetti, M. T., Gariano, S. L., Melillo, M., Rossi, M., and Guzzetti, F.:
Rainfall thresholds for possible landslide occurrence in Italy, Geomorphology, 290, 39–57, https://doi.org/10.1016/j.geomorph.2017.03.031, 2017.
Rosser, B., Dellow, S., Haubrock, S., and Glassey, P.:
New Zealand's National Landslide Database, Landslides, 14, 1949–1959, https://doi.org/10.1007/s10346-017-0843-6, 2017.
Salvati, P., Bianchi, C., Rossi, M., and Guzzetti, F.:
Societal landslide and flood risk in Italy, Nat. Hazards Earth Syst. Sci., 10, 465–483, https://doi.org/10.5194/nhess-10-465-2010, 2010.
Salvati, P., Petrucci, O., Rossi, M., Bianchi, C., Pasqua, A. A., and Guzzetti, F.:
Gender, age and circumstances analysis of flood and landslide fatalities in Italy, Sci. Total Environ., 610–611, 867–879, https://doi.org/10.1016/j.scitotenv.2017.08.064, 2018.
Segoni, S., Rossi, G., Rosi, A., and Catani, F.:
Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity–duration thresholds, Comput. Geosci., 63, 123–131, https://doi.org/10.1016/j.cageo.2013.10.009, 2014.
Segoni, S., Piciullo, L., and Gariano, S. L.:
A review of the recent literature on rainfall thresholds for landslide occurrence, Landslides, 15, 1483–1501, https://doi.org/10.1007/s10346-018-0966-4, 2018.
Trigila, A., Iadanza, C., and Spizzichino, D.:
Quality assessment of the Italian Landslide Inventory using GIS processing, Landslides, 7, 455–470, https://doi.org/10.1007/s10346-010-0213-0, 2010.
Trigila, A., Iadanza, C., Lastoria, B., Bussettini, M., and Barbano, A.:
Dissesto idrogeologico in Italia: pericolosità e indicatori di rischio – Edizione 2021, Rapporti 356/2021, ISPRA, 2021 (in Italian).
Van Den Eeckhaut, M. and Hervás, J.:
State of the art of national landslide databases in Europe and their potential for assessing landslide susceptibility, hazard and risk, Geomorphology, 139–140, 545–558, https://doi.org/10.1016/j.geomorph.2011.12.006, 2012.
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.
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue) is the largest catalogue of...
Altmetrics
Final-revised paper
Preprint