Statistical approach to storm event-induced landslides susceptibility

For the interpretation of the storm event-induced landslide distribution for an area, deterministic methods are frequently used, while a region's landslide susceptibility is commonly predicted via a statistical approach based upon multi-temporal landslide inventories and environmental facto...

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Main Authors: C.-T. Lee, C.-C. Huang, J.-F. Lee, K. -L. Pan, M.-L. Lin, J.-J. Dong
Format: Article
Language:English
Published: Copernicus Publications 2008-08-01
Series:Natural Hazards and Earth System Sciences
Online Access:http://www.nat-hazards-earth-syst-sci.net/8/941/2008/nhess-8-941-2008.pdf
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spelling doaj-e3f42bfa9519420ca24a24283b3627532020-11-24T21:11:09ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812008-08-0184941960Statistical approach to storm event-induced landslides susceptibilityC.-T. LeeC.-C. HuangJ.-F. LeeK. -L. PanM.-L. LinJ.-J. DongFor the interpretation of the storm event-induced landslide distribution for an area, deterministic methods are frequently used, while a region's landslide susceptibility is commonly predicted via a statistical approach based upon multi-temporal landslide inventories and environmental factors. In this study we try to use an event-based landslide inventory, a set of environmental variables and a triggering factor to build a susceptibility model for a region which is solved using a multivariate statistical method. Data for shallow landslides triggered by the 2002 typhoon, Toraji, in central western Taiwan, are selected for training the susceptibility model. The maximum rainfall intensity of the storm event is found to be an effective triggering factor affecting the landslide distribution and this is used in the model. The model is built for the Kuohsing region and validated using data from the neighboring Tungshih area and a subsequent storm event – the 2004 typhoon, Mindulle, which affected both the Kuohsing and the Tungshih areas. The results show that we can accurately interpret the landslide distribution in the study area and predict the occurrence of landslides in the neighboring region in a subsequent typhoon event. The advantage of this statistical method is that neither hydrological data, strength data, failure depth, nor a long-period landslide inventory is needed as input. http://www.nat-hazards-earth-syst-sci.net/8/941/2008/nhess-8-941-2008.pdf
collection DOAJ
language English
format Article
sources DOAJ
author C.-T. Lee
C.-C. Huang
J.-F. Lee
K. -L. Pan
M.-L. Lin
J.-J. Dong
spellingShingle C.-T. Lee
C.-C. Huang
J.-F. Lee
K. -L. Pan
M.-L. Lin
J.-J. Dong
Statistical approach to storm event-induced landslides susceptibility
Natural Hazards and Earth System Sciences
author_facet C.-T. Lee
C.-C. Huang
J.-F. Lee
K. -L. Pan
M.-L. Lin
J.-J. Dong
author_sort C.-T. Lee
title Statistical approach to storm event-induced landslides susceptibility
title_short Statistical approach to storm event-induced landslides susceptibility
title_full Statistical approach to storm event-induced landslides susceptibility
title_fullStr Statistical approach to storm event-induced landslides susceptibility
title_full_unstemmed Statistical approach to storm event-induced landslides susceptibility
title_sort statistical approach to storm event-induced landslides susceptibility
publisher Copernicus Publications
series Natural Hazards and Earth System Sciences
issn 1561-8633
1684-9981
publishDate 2008-08-01
description For the interpretation of the storm event-induced landslide distribution for an area, deterministic methods are frequently used, while a region's landslide susceptibility is commonly predicted via a statistical approach based upon multi-temporal landslide inventories and environmental factors. In this study we try to use an event-based landslide inventory, a set of environmental variables and a triggering factor to build a susceptibility model for a region which is solved using a multivariate statistical method. Data for shallow landslides triggered by the 2002 typhoon, Toraji, in central western Taiwan, are selected for training the susceptibility model. The maximum rainfall intensity of the storm event is found to be an effective triggering factor affecting the landslide distribution and this is used in the model. The model is built for the Kuohsing region and validated using data from the neighboring Tungshih area and a subsequent storm event – the 2004 typhoon, Mindulle, which affected both the Kuohsing and the Tungshih areas. The results show that we can accurately interpret the landslide distribution in the study area and predict the occurrence of landslides in the neighboring region in a subsequent typhoon event. The advantage of this statistical method is that neither hydrological data, strength data, failure depth, nor a long-period landslide inventory is needed as input.
url http://www.nat-hazards-earth-syst-sci.net/8/941/2008/nhess-8-941-2008.pdf
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