Articles | Volume 23, issue 9
https://doi.org/10.5194/nhess-23-3079-2023
https://doi.org/10.5194/nhess-23-3079-2023
Research article
 | 
20 Sep 2023
Research article |  | 20 Sep 2023

Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications

Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi

Related authors

Brief communication: Post-wildfire rockfall risk in the eastern Alps
Sandra Melzner, Nurit Shtober-Zisu, Oded Katz, and Lea Wittenberg
Nat. Hazards Earth Syst. Sci., 19, 2879–2885, https://doi.org/10.5194/nhess-19-2879-2019,https://doi.org/10.5194/nhess-19-2879-2019, 2019
Short summary

Related subject area

Landslides and Debris Flows Hazards
Identifying unrecognised risks to life from debris flows
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
Nat. Hazards Earth Syst. Sci., 25, 647–656, https://doi.org/10.5194/nhess-25-647-2025,https://doi.org/10.5194/nhess-25-647-2025, 2025
Short summary
Predicting the thickness of shallow landslides in Switzerland using machine learning
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci., 25, 467–491, https://doi.org/10.5194/nhess-25-467-2025,https://doi.org/10.5194/nhess-25-467-2025, 2025
Short summary
Unraveling landslide failure mechanisms with seismic signal analysis for enhanced pre-survey understanding
Jui-Ming Chang, Che-Ming Yang, Wei-An Chao, Chin-Shang Ku, Ming-Wan Huang, Tung-Chou Hsieh, and Chi-Yao Hung
Nat. Hazards Earth Syst. Sci., 25, 451–466, https://doi.org/10.5194/nhess-25-451-2025,https://doi.org/10.5194/nhess-25-451-2025, 2025
Short summary
Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025,https://doi.org/10.5194/nhess-25-183-2025, 2025
Short summary
Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025,https://doi.org/10.5194/nhess-25-169-2025, 2025
Short summary

Cited articles

Agliardi, F., Crosta, G. B., and Frattini, P.: Integrating rockfall risk assessment and countermeasure design by 3D modelling techniques, Nat. Hazards Earth Syst. Sci., 9, 1059–1073, https://doi.org/10.5194/nhess-9-1059-2009, 2009. 
Antonini, G., Ardizzone, F., Cardinali, C., Galli, M., Guzzetti, F., and Reichenbach, P.: Surface deposits and landslide inventory map of the area affected by the 1997 Umbria-Marche earthquakes, Boll. Soc. Geol. Lt., 1, 843–853, 2002. 
Brown, R. L., Durbin, J., and Evans, J. M.: Techniques for Testing the Constancy of Regression Relationships over Time, J. Roy. Stat. Soc. Ser. B, 37, 149–192, 1975. 
Chau, K. T., Wong, R. H. C., Liu, J., and Lee, C. F.: Rockfall Hazard Analysis for Hong Kong Based on Rockfall Inventory, Rock Mech. Rock Eng., 36, 383–408, https://doi.org/10.1007/s00603-002-0035-z, 2003. 
Corominas, J., Mavrouli, O., and Ruiz-Carulla, R.: Magnitude and frequency relations: are there geological constraints to the rockfall size?, Landslides, 15, 829–845, https://doi.org/10.1007/s10346-017-0910-z, 2017. 
Download
Short summary
The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Share
Altmetrics
Final-revised paper
Preprint