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Titel |
Statistical Patterns of Triggered Landslide Events and their Application to Road Networks |
VerfasserIn |
Faith E. Taylor, Bruce D. Malamud, Michele Santangelo, Ivan Marchesini, Fausto Guzzetti |
Konferenz |
EGU General Assembly 2015
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 17 (2015) |
Datensatznummer |
250110030
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Publikation (Nr.) |
EGU/EGU2015-9992.pdf |
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Zusammenfassung |
In the minutes to weeks after a landslide trigger such as an earthquake or heavy rainfall, as
part of a triggered landslide event, one individual to tens of thousands of landslides may
occur across a region. If in the region, one or more roads become blocked by landslides, this
can cause extensive detours and delay rescue and recovery operations. In this paper, we show
the development, application and confrontation with real data of a model to simulate
triggered landslide events and their impacts upon road networks. This is done by creating a
‘synthetic’ triggered landslide event inventory by randomly sampling landslide areas and
shapes from already established statistical distributions. These landslides are then
semi-randomly dropped across a given study region, conditioned by that region’s
landslide susceptibility. The resulting synthetic triggered landslide event inventory is
overlaid with the region’s road network map and the number, size, location and
network impact of road blockages and landslides near roads calculated. This process
is repeated hundreds of times in a Monte Carlo type simulation. The statistical
distributions and approaches used in the model are thought to be generally applicable for
low-mobility triggered landslides in many medium to high-topography regions
throughout the world. The only local data required to run the model are a road
network map, a landslide susceptibility map, a map of the study area boundary and a
digital elevation model. Coupled with an Open Source modelling approach (in
GRASS-GIS), this model may be applied to many regions where triggered landslide events
are an issue. We present model results and confrontation with observed data for
two study regions where the model has been applied: Collazzone (Central Italy)
where rapid snowmelt triggered 413 landslides in January 1997 and Oat Mountain
(Northridge, USA), where the Northridge Earthquake triggered 1,356 landslides in
January 1994. We find that when the landslide susceptibility map is adjusted along
road corridors to take into account interactions between landslides and roads, the
model reasonably well matches the two observed results. In Collazzone (length of
road = 153 km, landslide density = 5.2 landslides km-2), the median number of
road blockages over 100 model runs was 5.0 (±2.5 s.d.), compared to the observed
number of 5 road blocks. In Northridge (length of road = 780 km, landslide density =
8.7 landslides km-2), the median number of road blockages over 100 model runs
was 28.0.* (±14.4 s.d.) compared to the observed number of 48.0 road blocks. We
are now working on applying the model to other locations and developing more
sophisticated network impact analysis tools to improve the applicability of the model. |
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