Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 22, issue 4
Articles | Volume 22, issue 4
https://doi.org/10.5194/nhess-22-1151-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-1151-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 4
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, David J. Peres, Pietro Scandura, and Antonino Cancelliere

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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.
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