Articles | Volume 21, issue 9
https://doi.org/10.5194/nhess-21-2773-2021
https://doi.org/10.5194/nhess-21-2773-2021
Research article
 | 
10 Sep 2021
Research article |  | 10 Sep 2021

Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment

Jacob Hirschberg, Alexandre Badoux, Brian W. McArdell, Elena Leonarduzzi, and Peter Molnar

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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Cited articles

Abancó, C., Hürlimann, M., Moya, J., and Berenguer, M.: Critical rainfall conditions for the initiation of torrential flows. Results from the Rebaixader catchment (Central Pyrenees), J. Hydrol., 541, 218–229, https://doi.org/10.1016/j.jhydrol.2016.01.019, 2016. a, b, c
Badoux, A., Graf, C., Rhyner, J., Kuntner, R., and McArdell, B. W.: A debris-flow alarm system for the Alpine Illgraben catchment: Design and performance, Nat. Hazards, 49, 517–539, https://doi.org/10.1007/s11069-008-9303-x, 2009. a, b, c, d
Badoux, A., Turowski, J. M., Mao, L., Mathys, N., and Rickenmann, D.: Rainfall intensity–duration thresholds for bedload transport initiation in small Alpine watersheds, Nat. Hazards Earth Syst. Sci., 12, 3091–3108, https://doi.org/10.5194/nhess-12-3091-2012, 2012. a, b
Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747–2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016. a
Bel, C., Liébault, F., Navratil, O., Eckert, N., Bellot, H., Fontaine, F., and Laigle, D.: Rainfall control of debris- flow triggering in the Réal Torrent, Southern French Prealps, Geomorphology, 291, 17–32, https://doi.org/10.1016/j.geomorph.2016.04.004, 2017. a, b, c, d, e, f, g, h, i, j
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Debris-flow prediction is often based on rainfall thresholds, but uncertainty assessments are rare. We established rainfall thresholds using two approaches and find that 25 debris flows are needed for uncertainties to converge in an Alpine basin and that the suitable method differs for regional compared to local thresholds. Finally, we demonstrate the potential of a statistical learning algorithm to improve threshold performance. These findings are helpful for early warning system development.
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