Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method

As a landslide occurs, seismic signals generated by the mass sliding on the slope can be recorded by seismometers nearby. Using waveform inversion techniques, we can explore the dynamic processes (e.g., sliding direction, velocity, and runout distance) of a landslide with the inverted force–time fun...

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Main Authors: Guan-Wei Lin, Ching Hung
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/17/5872
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spelling doaj-513ed762fafc448893b8d06689301aba2020-11-25T03:11:30ZengMDPI AGApplied Sciences2076-34172020-08-01105872587210.3390/app10175872Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion MethodGuan-Wei Lin0Ching Hung1Department of Earth Sciences, National Cheng Kung University, No. 1, University Road, Tainan 701, TaiwanDepartment of Civil Engineering, National Cheng Kung University, No. 1, University Road, Tainan 701, TaiwanAs a landslide occurs, seismic signals generated by the mass sliding on the slope can be recorded by seismometers nearby. Using waveform inversion techniques, we can explore the dynamic processes (e.g., sliding direction, velocity, and runout distance) of a landslide with the inverted force–time function. In this study, the point force history (PFH) inversion method was applied to the Taimali landslide in Taiwan, which was triggered by a heavy rainstorm in 2009. The inverted force–time function for the landslide revealed the complicated dynamic processes. The time series of velocity indicated three different sliding directions during the landslide. Hence, three propagating stages of the Taimali landslide were determined and were consistent with an investigation using remote sensing images and a digital elevation model of the landslide. In addition, the PFH inversion was implemented using high-quality single-station records and maintained good performance compared with the inversion by multistation records.https://www.mdpi.com/2076-3417/10/17/5872dynamic processeslarge-scale landslidesseismic signalswaveform inversion
collection DOAJ
language English
format Article
sources DOAJ
author Guan-Wei Lin
Ching Hung
spellingShingle Guan-Wei Lin
Ching Hung
Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method
Applied Sciences
dynamic processes
large-scale landslides
seismic signals
waveform inversion
author_facet Guan-Wei Lin
Ching Hung
author_sort Guan-Wei Lin
title Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method
title_short Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method
title_full Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method
title_fullStr Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method
title_full_unstemmed Reconstructing the Dynamic Processes of the Taimali Landslide in Taiwan Using the Waveform Inversion Method
title_sort reconstructing the dynamic processes of the taimali landslide in taiwan using the waveform inversion method
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2020-08-01
description As a landslide occurs, seismic signals generated by the mass sliding on the slope can be recorded by seismometers nearby. Using waveform inversion techniques, we can explore the dynamic processes (e.g., sliding direction, velocity, and runout distance) of a landslide with the inverted force–time function. In this study, the point force history (PFH) inversion method was applied to the Taimali landslide in Taiwan, which was triggered by a heavy rainstorm in 2009. The inverted force–time function for the landslide revealed the complicated dynamic processes. The time series of velocity indicated three different sliding directions during the landslide. Hence, three propagating stages of the Taimali landslide were determined and were consistent with an investigation using remote sensing images and a digital elevation model of the landslide. In addition, the PFH inversion was implemented using high-quality single-station records and maintained good performance compared with the inversion by multistation records.
topic dynamic processes
large-scale landslides
seismic signals
waveform inversion
url https://www.mdpi.com/2076-3417/10/17/5872
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