Preprints
https://doi.org/10.5194/nhessd-3-575-2015
https://doi.org/10.5194/nhessd-3-575-2015
20 Jan 2015
 | 20 Jan 2015
Status: this discussion paper is a preprint. It has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). The manuscript was not accepted for further review after discussion.

Predictive analysis of landslide susceptibility in the Kao-Ping watershed, Taiwan under climate change conditions

K. J. Shou, C. C. Wu, and J. F. Lin

Abstract. Among the most critical issues, climatic abnormalities caused by global warming also affect Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary Typhoon Morakot hit Southern Taiwan on 8 August 2009 and induced serious flooding and landslides. In this study, the Kao-Ping River watershed was adopted as the study area, and the typical events 2007 Krosa Typhoon and 2009 Morakot Typhoon were adopted to train the susceptibility model. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the Kao-Ping River watershed. The rainfall estimates were introduced in the landslide susceptibility model to produce the predictive landslide susceptibility for various rainfall scenarios, including abnormal climate conditions. These results can be used for hazard remediation, mitigation, and prevention plans for the Kao-Ping River watershed.

K. J. Shou, C. C. Wu, and J. F. Lin
K. J. Shou, C. C. Wu, and J. F. Lin
K. J. Shou, C. C. Wu, and J. F. Lin

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Short summary
This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling to estimate the temporal rainfall trends, distributions, and intensities in the Kao-Ping River watershed. The rainfall estimates were introduced in the landslide susceptibility model to produce the predictive landslide susceptibility for various rainfall scenarios, including abnormal climate conditions. The results can be used for hazard mitigation and management.
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