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Debris-flow monitoring and warning: Review and examples
Open accessAbstract
Abstract Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ∼10 km2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.
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Iverson, R. M. (1997) · Reviews of Geophysics · doi:10.1029/97rg00426 · Cited by 3,092
Cited by
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Pellegrini, S., Rizzelli, G., Barla, M., & Gaudino, R. (2023) · IEEE Photonics Journal · doi:10.1109/jphot.2023.3281670 · Cited by 21
Enhancing Debris Flow Warning via Machine Learning Feature Reduction and Model Selection
Zhou, Q., Tang, H., Hibert, C., Chmiel, M., Walter, F., Dietze, M., & Turowski, J. M. (2025) · Journal of Geophysical Research: Earth Surface · doi:10.1029/2024jf008094 · Cited by 20
Metadata
- Authors
- Hürlimann, M., Coviello, V., Bel, C., Guo, X., Berti, M., Graf, C., Hübl, J., Miyata, S., Smith, J. B., & Yin, H.-Y.
- Venue
- Earth-Science Reviews
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 199
- Pages
- 102981
- ISSN
- 0012-8252 (ISSN-L)
- OpenAlex
- W2981386717
- Cited by
- 297
- References
- 1
- FWCI
- 25.44
- Type
- journal article
- Language
- en
- Open access
- green
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- Hürlimann, M., Coviello, V., Bel, C., Guo, X., Berti, M., Graf, C., Hübl, J., Miyata, S., Smith, J. B., & Yin, H.-Y. (2019). Debris-flow monitoring and warning: Review and examples. Earth-Science Reviews. https://doi.org/10.1016/j.earscirev.2019.102981
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