Articles | Volume 22, issue 4
Nat. Hazards Earth Syst. Sci., 22, 1151–1157, 2022
Nat. Hazards Earth Syst. Sci., 22, 1151–1157, 2022
Brief communication
04 Apr 2022
Brief communication | 04 Apr 2022

Brief communication: Introducing rainfall thresholds for landslide triggering based on artificial neural networks

Pierpaolo Distefano et al.

Related authors

Potential improvements of landslide prediction by hydro-meteorological thresholds: an investigation based on reanalysis soil moisture data and principal component analysis
Nunziarita Palazzolo, David Johnny Peres, Enrico Creaco, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci. Discuss.,,, 2022
Preprint under review for NHESS
Short summary
Brief communication: Key papers of 20 years in Natural Hazards and Earth System Sciences
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993,,, 2022
Short summary
Evaluation of EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment for the Euro-Mediterranean area) historical simulations by high-quality observational datasets in southern Italy: insights on drought assessment
David J. Peres, Alfonso Senatore, Paola Nanni, Antonino Cancelliere, Giuseppe Mendicino, and Brunella Bonaccorso
Nat. Hazards Earth Syst. Sci., 20, 3057–3082,,, 2020
Short summary
Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds
David J. Peres, Antonino Cancelliere, Roberto Greco, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 18, 633–646,,, 2018
Short summary
Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach
D. J. Peres and A. Cancelliere
Hydrol. Earth Syst. Sci., 18, 4913–4931,,, 2014
Short summary

Related subject area

Landslides and Debris Flows Hazards
Landslide susceptibility assessment in the rocky coast subsystem of Essaouira, Morocco
Abdellah Khouz, Jorge Trindade, Sérgio C. Oliveira, Fatima El Bchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud
Nat. Hazards Earth Syst. Sci., 22, 3793–3814,,, 2022
Short summary
Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764,,, 2022
Short summary
Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700,,, 2022
Short summary
Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661,,, 2022
Short summary
Earthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influences
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci., 22, 3361–3384,,, 2022
Short summary

Cited articles

Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39,, 2018. 
Caine, N.: The Rainfall Intensity-Duration Control of Shallow Landslides and Debris Flows, Soc. Swedish Ann. Geogr. Geogr. Phys., 62, 23–27, 1980. 
Calvello, M. and Pecoraro, G.: FraneItalia: a catalog of recent Italian landslides, Geoenviron. Disast., 5, 13,, 2018. 
Calvello, M. and Pecoraro, G.: The FraneItalia database, FraneItalia [data set],, last access: 17 November 2021. 
Conrad, J. L., Morphew, M. D., Baum, R. L., and Mirus, B. B.: HydroMet: A New Code for Automated Objective Optimization of Hydrometeorological Thresholds for Landslide Initiation, Water, 13, 1752,, 2021. 
Short summary
In the communication, we introduce the use of artificial neural networks (ANNs) for improving the performance of rainfall thresholds for landslide early warning. Results show how ANNs using rainfall event duration and mean intensity perform significantly better than a classical power law based on the same variables. Adding peak rainfall intensity as input to the ANN improves performance even more. This further demonstrates the potentialities of the proposed machine learning approach.
Final-revised paper