Characterization of alpine rockslides using statistical analysis of seismic signals

摘要: [1] Seismic data analysis is a powerful tool for remote characterization of rock slope failures. Here we develop quantitative estimates fundamental rockslide properties (e.g., volume) based solely on from an existing regional seismic network. We assembled set twenty known rockslides in the central Alps (with volumes between 1,000 and 2,000,000 m3) analyzed their corresponding seismograms. Common signal characteristics include emergent onsets, slowly decaying tails, triangular spectrogram shape. The main component energy contained frequencies below ∼3–4 Hz, while higher-frequency signals may be caused by block impacts. Location were generated using automatic arrival time picks resulted mean location error 10.9 km. A linear relationship detection limit as function volume was identified our station To estimate volume, runout distance, drop height, potential energy, Fahrboschung (angle reach), extracted five simple metrics each seismogram: duration, peak value ground velocity envelope, envelope area, risetime, average velocity. Using multivariate regression, combination velocity, area best estimated event parameters, with r2 values ranging 0.8 0.88. Three new then used to validate method, runout, within correct order magnitude. When provided suitable events, method can easily adapted other regions networks.