Abstract:
Recent population growth and actions near hilly
areas increase the vulnerability of occurring landslides. The
effects of climate change further increase the likelihood of
landslide danger. Therefore, accurate analysis of unstable slope
behavior is crucial to prevent loss of life and destruction to
property. Predicting landslide flow path is essential in identifying
the route of debris, and it is essential necessary component in
hazard mapping. Horvever, current methodologies of
determining the flow direction of landslides require costly sitespecific
data such as surface soil type, categories of underground
soil layers, and other related field characteristics. This paper
demonstrates an approach to predict the flow direction without
site-specific data, taking a large landslide incident in Sri Lanka
at Araranyaka region in the district of Kegalle as a case study.
Spreading area assessment was based on deterministic eight-node
(D8) and Multiple Direction Flow (MDF) flow directional
.algorithms. Results acquired by the model were compared with
the real Aranayaka landslide data set and the landslide hazard
map of the area. Debris paths generated from the proof of
concept software tool using the D8 algorithm showed greater
than 760/o agreement, and MDF showed greater than 87oh
agreement with the actual flow paths and other related statistics
such as maximum width of the slide, run-out distance, and slip
surface area.
