論文

査読有り
2017年6月

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

LANDSLIDES
  • Chi-Wen Chen
  • ,
  • Hitoshi Saito
  • ,
  • Takashi Oguchi

14
3
開始ページ
1031
終了ページ
1041
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s10346-016-0788-1
出版者・発行元
SPRINGER HEIDELBERG

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.

リンク情報
DOI
https://doi.org/10.1007/s10346-016-0788-1
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000401697900018&DestApp=WOS_CPL
ID情報
  • DOI : 10.1007/s10346-016-0788-1
  • ISSN : 1612-510X
  • eISSN : 1612-5118
  • Web of Science ID : WOS:000401697900018

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