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Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-126
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 29 Jun 2018

Research article | 29 Jun 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Evaluating critical rainfall conditions for large-scale landslides by detecting event times from seismic records

Hsien-Li Kuo1, Guan-Wei Lin1, Chi-Wen Chen2, Hitoshi Saito3, Ching-Weei Lin1, Hongey Chen2,4, and Wei-An Chao5 Hsien-Li Kuo et al.
  • 1Department of Earth Sciences, National Cheng Kung University, No. 1, University Road, Tainan City, 70101, Taiwan
  • 2National Science and Technology Center for Disaster Reduction, No. 200, Sec. 3, Beixin Road, Xindin District, New Taipei City, 23143, Taiwan
  • 3College of Economics, Kanto Gakuin University, 1-50-1 Mutsuura-higashi, Kanazawa-ku, Yokohama, 236-8501, Japan
  • 4Department of Geosciences, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei, 10617, Taiwan
  • 5Department of Civil Engineering, National Chiao Tung University, No. 1001, Daxue Rd., Hsinchu, 30010, Taiwan

Abstract. One of the purposes of slope disaster research is to establish an early warning method for rainfall-induced landslides. The insufficient observational records of the past, however, have inhibited the analysis of critical rainfall conditions. This dilemma may be resolved by extracting the times of landslide occurrences from the seismic signals recorded by adjacent seismic stations. In this study, the seismic records of the Broadband Array in Taiwan for Seismology (BATS) were examined to identify the ground motion triggered by large-scale landslides occurring from 2005 to 2014. After the signals from local and teleseismic earthquakes were eliminated, 62 landslide-induced seismic signals were identified. The seismic signals provided the occurrence times of the landslides for assessment of the rainfall conditions, including rainfall intensity (I, mm/h), duration (D, h), and cumulated rainfall (R, mm). Comparison of three common rainfall threshold models (ID, IR, and RD) revealed duration and cumulated rainfall to be the crucial factors in developing a forecast warning model. In addition, a critical volume of water model, (I1.04)·D=452mm, combining statistical and deterministic approaches was established through analysis of rainfall information from the 62 large-scale landslides that occurred.

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Short summary
Building an early warning method for rainfall-induced landslides has been an aim of landslide studies to prevent or mitigate the impact of disasters. The time information of landslides is the linchpin; however, it has been difficult to get the time information. In the study, we applied the observation of landslide-induced seismic signals to extract the occurrence times of numerous large landslides. Furthermore, the common estimations of the rainfall thresholds for landslides were performed.
Building an early warning method for rainfall-induced landslides has been an aim of landslide...
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