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...
Main Authors: | , , , , , |
---|---|
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 |
id |
doaj-e3f42bfa9519420ca24a24283b362753 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT ctlee statisticalapproachtostormeventinducedlandslidessusceptibility AT cchuang statisticalapproachtostormeventinducedlandslidessusceptibility AT jflee statisticalapproachtostormeventinducedlandslidessusceptibility AT klpan statisticalapproachtostormeventinducedlandslidessusceptibility AT mllin statisticalapproachtostormeventinducedlandslidessusceptibility AT jjdong statisticalapproachtostormeventinducedlandslidessusceptibility |
_version_ |
1716754336756793344 |