Abstract
The estimation of debris-flow velocity and volume is a fundamental task for the development of early warning systems, the design of control structures and other mitigation measures. Previous analysis of the seismic energy produced by debris flows showed that the peak amplitudes are representative of the kinetic energy of each surge and debris-flow discharge can be therefore estimated based on seismic signals. Also, the debris-flow velocity can be calculated using seismic data recorded at two spatial separated stations located along the channel by the use of cross-correlation. This work provide a first approach for estimating the total volume of debris flows based on the seismic signal detected with simple, low-cost geophones installed along the debris-flow channel. The developed methods was applied to seismic data collected on three different test sites in the Alps: Gadria (IT), Lattenbach (AT), and Cancia (IT). An adaptable cross-correlation time window was used, which can offer a better estimation of the velocity compared to a constant window length. The analyses of the seismic data of 14 debris flows that occurred from 2014 to 2018 shows the strong control of the sampling rate and the sensor-distance on the velocity estimation. A simple approach based on a linear relation between square of the seismic amplitude and the event magnitude is proposed for a first order estimation of the debris-flow magnitude.
Highlights
With the rapid socio-economic development of European mountain areas, the automatic detection and identification of mass 15 movements like landslides, debris flows, and avalanches become of paramount importance for risk mitigation
Previous analysis of the seismic energy produced by debris flows showed that the peak amplitudes are representative of the kinetic energy of each surge and debris-flow discharge can be estimated based on seismic signals
The developed methods was applied to seismic data collected on three different test sites in the Alps: Gadria (IT), Lattenbach (AT), and Cancia (IT)
Summary
With the rapid socio-economic development of European mountain areas, the automatic detection and identification of mass 15 movements like landslides, debris flows, and avalanches become of paramount importance for risk mitigation. Several investigations 20 have already addressed signal processing and detection methods based on seismic (e.g., Coviello et al, 2018; Walter et al, 2017; Burtin et al, 2016) or infrasound sensors (e.g., Zhang et al, 2004; Ulivieri et al, 2012; Marchetti et al, 2019). For developing an efficient warning system, the detection of events is important and the identification of the event type (e.g. debris flow vs debris flood) and the estimation of its magnitude and velocity. An early approach to estimate the process velocity based on seismic data and cross-correlation was proposed by Arattano 25 and Marchi (2005). Havens et al (2014) and Marchetti et al (2015) used arrays of infrasound sensors to estimate the velocity of snow avalanches.
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