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Landslides

, Volume 14, Issue 3, pp 1031–1041 | Cite as

Analyzing rainfall-induced mass movements in Taiwan using the soil water index

  • Chi-Wen Chen
  • Hitoshi Saito
  • Takashi Oguchi
Original Paper

Abstract

This study applied the soil water index (SWI), which can represent the conceptual soil water contents as influenced by present and antecedent rainfall, for analyzing rainfall-induced mass movements in Taiwan. The SWI has been used in Japan for nationwide mass movement warnings. This study examined whether the SWI can be also applied to Taiwan, which has a climatic condition and high-relief topography similar to Japan. We used data for mass movements for 2006–2012 (n = 263) for the main analyses and those for 2013 (n = 19) for verification. The SWI values before the rainfall events that triggered mass movements were used as the indicator of the antecedent rainfall condition. We found that when SWI values before rainfall events increased from <17.5 to >35, the upper threshold of rainfall conditions needed for triggering mass movements significantly decreased. The mass movements in 2013 support this finding. We classified rainfall conditions for triggering mass movements into two types, short duration–high intensity (SH) and long duration–low intensity (LL), based on a principal component analysis (PCA). The SH type is associated with a rapid increase in SWI, and the LL type is associated with a gradual rise and subsequent constancy of SWI except in some extremely long rainfall events. Based on this result, we modeled the general trend of the time series changes in SWI for the two types, which was verified using the mass movements in 2013.

Keywords

Landslides Debris flows Short duration–high intensity (SH) Long duration–low intensity (LL) Warning system 

Notes

Acknowledgements

We would like to thank the Typhoon and Flood Research Institute (TTFRI) of Taiwan for providing rainfall data and the Soil and Water Conservation Bureau (SWCB) of Taiwan for providing information on mass movements. This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 15K12452.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Center for Spatial Information ScienceUniversity of TokyoKashiwaJapan
  2. 2.National Science and Technology Center for Disaster ReductionXindin DistrictTaiwan
  3. 3.College of EconomicsKanto Gakuin UniversityYokohamaJapan

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