| Issue |
E3S Web of Conf.
Volume 415, 2023
8th International Conference on Debris Flow Hazard Mitigation (DFHM8)
|
|
|---|---|---|
| Article Number | 07012 | |
| Number of page(s) | 3 | |
| Section | Needs of End Users | |
| DOI | https://doi.org/10.1051/e3sconf/202341507012 | |
| Published online | 18 August 2023 | |
A regional early warning system for debris flows
1 CIMA Foundation, Savona, Italia
2 Centro Funzionale della Valle d’Aosta, Dipartimento Protezione Civile, Valle d’Aosta, Italia
* Corresponding author: michelponziani@gmail.com
In this study, we have developed a predictive model for debris flows using machine learning techniques on a detailed dataset composed by a variety of geomorphological and hydro-meteorological variables. The variables of the dataset were collected from daily measured and modelled data for all of the drainage basins in which at least one debris-flow event was generated during the time period considered (2009-2019). The performances of the models obtained with different machine learning techniques were evaluated with the ROC analysis. The most suitable model was then experimentally implemented in the existing early warning system of the Aosta Valley Region. The model provides daily values of debris-flow probability (DFP) for individual basins, based on the input geo-morphological and hydro-meteorological variables. These results can be used to issue specific debris-flow alerts at the scale of the alert areas of the region.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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