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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 11 | Copyright
Nat. Hazards Earth Syst. Sci., 18, 2877-2891, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 06 Nov 2018

Research article | 06 Nov 2018

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, Xindian 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 purpose of landslide research is to establish early warning thresholds for rainfall-induced landslides. Insufficient observations of past events have inhibited the analysis of critical rainfall conditions triggering landslides. This difficulty may be resolved by extracting the timing of landslide occurrences through analysis of seismic signals. In this study, seismic records of the Broadband Array in Taiwan for Seismology were examined to identify ground motion triggered by large landslides that occurred in the years 2005 to 2014. A total of 62 landslide-induced seismic signals were identified. The seismic signals were analyzed to determine the timing of landslide occurrences, and the rainfall conditions at those times – including rainfall intensity (I), duration (D), and effective rainfall (Rt) – were assessed. Three common rainfall threshold models (ID, I–Rt, and Rt–D) were compared, and the crucial factors of a forecast warning model were found to be duration and effective rainfall. In addition, rainfall information related to the 62 landslides was analyzed to establish a critical height of water model, (I − 1.5) ⋅ D = 430.2. The critical height of water model was applied to data from Typhoon Soudelor of 2015, and the model issued a large landslide warning for southern Taiwan.

Publications Copernicus
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...