, Volume 13, Issue 5, pp 1181–1196 | Cite as

Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals

  • A. SchimmelEmail author
  • J. Hübl
Original Paper


Processes like landslides, debris flows, or bed load transport, at the intersection between the natural environment and human activity, constitute an increasing threat to people and property. The ability to detect these processes prematurely is an essential task for mitigating these hazards. Past studies have shown that debris flows and debris floods emit detectable signals in the low-frequency infrasonic spectrum and induce characteristically seismic signals. A number of monitoring devices and detection methods to identify debris flows using these signals have been developed, but up to date, no warning system based on a combination of seismic and infrasound sensors has been considered. Previous studies have already shown that seismic and infrasonic signals of alpine mass movements are correlated and complementary and that the combination of these two sensor types can serve as basis for an error-resistant detection and warning system. So this work aims to develop a detection system for detecting debris flows and debris floods by analyzing the seismic and infrasound waves. The system is build up on a minimum of one seismic and one infrasound sensor which are co-located and a microcontroller which runs a detection algorithm to detect debris flows and debris floods with high accuracy in real time directly on-site. The detection algorithm is based on an analysis of the evolution in time of the frequency content of the mass movement signal and has been tested with debris flows and debris flood signals monitored at different test sites in Austria and Switzerland. This paper describes the current version of the detection system and gives an example of event detection at the Tyrolese test sites Lattenbach, Dristenau, and Farstrinne.


Debris flows Debris floods Early detection system Infrasound signals Seismic signals 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Institute of Mountain Risk EngineeringUniversity of Natural Resources and Life SciencesViennaAustria

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