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A lab-fabricated ocean bottom seismometer was modified and deployed terrestrially to detect low-frequency (<10 Hz) ground vibrations produced by debris flows. A frequency–response test of the new seismometer revealed that it can detect seismic signals at frequencies of 0.3–120 Hz. Its seismic ground motion detection ability was investigated by comparing its measurements of seismic signals produced by rockfalls with those of a geophone. Two new seismometers were deployed at the Aiyuzi Stream, Nantou County, Taiwan, in September 2012. Seismic signals produced by two local earthquakes, two teleseisms, and three debris flows detected by the seismometer in 2013 and 2014 were discussed. The seismic signal frequencies of the local earthquakes and teleseisms (both approximately 1800 km apart) were 0.3–30 and <1 Hz, respectively. Moreover, seismometer measurements revealed that seismic signals generated by debris flows can have minimum frequencies as low as 2 Hz. Time-matched CCD camera images revealed that debris flow surge fronts with larger rocks have lower minimum frequencies. Finally, because the seismometer can detect low-frequency seismic waves with low spatial decay rates, it was able to detect one debris flow approximately 3 min and 40 s before it arrived. [ABSTRACT FROM AUTHOR]

Landslide-generated seismic waves (landslide-quakes), exhibiting distinctive waveforms and frequency characteristics, can be recorded by nearby seismometers. Implementing an automatic classifier for landslide-quakes could help provide objective and accurate initiation times of landslides with efficiency. This study collected and analyzed the time information of 214 landslide seismic records due to 33 documented landslide events, from the Broadband Array in Taiwan for Seismology (BATS). In addition, equal numbers of earthquake and noise signals were also incorporated. The 642 seismic signals and time information were carefully examined using the random forest algorithm to create an automatic landslide-quake classifier. By validating the signal attributes of the landslide, earthquake, and noise events, specifically in the time and frequency domains, it was shown that the proposed classifier can reach an accuracy (the proportion of all correctly classified events to the total number of events) of 91.3%. To further evaluate the applicability of the automatic classifier, landslide-quakes generated during the devastating Typhoon Morakot (2009) and Typhoon Soudelor (2015) were also verified, showing that the sensitivity of the classifier is higher than 98%. [ABSTRACT FROM AUTHOR]

This work presents a novel fiber-optic sensing system, capable of monitoring debris flows or other natural hazards that produce ground vibrations. The proposed sensing system comprises a demodulator (BraggSCOPE, FS5500), which includes a broadband light source and a data logger, a four-port coupler and four Fiber Bragg Grating (FBG) accelerometers. Based on field tests, the performance of the proposed fiber-optic sensing system is compared with that of a conventional sensing system that includes a geophone or a microphone. Following confirmation of the reliability of the proposed sensing system, the fiber-optic sensing systems are deployed along the Ai-Yu-Zi and Chu-Shui Creeks in Nautou County of central Taiwan for monitoring debris flows. Sensitivity test of the deployed fiber-optic sensing system along the creek banks is also performed. Analysis results of the seismic data recorded by the systems reveal in detail the frequency characteristics of the artificially generated ground vibrations. Results of this study demonstrate that the proposed fiber-optic sensing system is highly promising for use in monitoring natural disasters that generate ground vibrations.