Development of an empirical model for rainfall-induced hillside vulnerability assessment: a case study on Chen-Yu-Lan watershed, Nantou, Taiwan

Tsu-Chiang Lei (), Yi-Min Huang (), Bing-Jean Lee (), Meng-Hsun Hsieh () and Kuan-Ting Lin ()

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2014, vol. 74, issue 2, 373 pages

Abstract: In Taiwan, the hillside is about 70 % of total area. These areas also have steep topography and geological vulnerability. When an event of torrential rain comes during a typhoon, the landslide disasters usually occur at these areas due to the long duration and high intensity of rainfall. Therefore, a design which considers the potential landslide has become an important issue in Taiwan. In this study, a temporal characteristic of landslide fragility curve (LFC) was developed, based on the geomorphological and vegetation factors using landslides at the Chen-Yu-Lan watershed in Taiwan, during Typhoon Sinlaku (September 2008) and Typhoon Morakot (August 2009). This study addressed an effective landslide hazard assessment process, linking together the post-landslide damage and post-rainfall data for LFC model. The Kriging method was used to interpolate the rainfall indices (R 0 , R, I) for numerical analysis. Remote sensing data from SPOT images were applied to analyze the landslide ratio and vegetation conditions. The 40-m digital elevation model was used for slope variation analysis in the watershed, and the maximum likelihood estimate was conducted to determine the mean and standard deviation parameters of the proposed empirical LFC model. This empirical model can express the probability of exceeding a damage state for a certain classification (or conditions) of landslides by considering a specific hazard index for a given event. Finally, the vulnerability functions can be used to assess the loss from landslides, and, in the future, to manage the risk of debris flow in the watershed. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Landslide; Maximum likelihood method; Hazard analysis; Risk management (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11069-014-1219-z

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