Debris Run-Out Modeling Without Site-Specific Data

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. However, current methodologies of determining the flow direction of landslides require costly site-specific 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 76% agreement, and MDF showed greater than 87% agreement with the actual flow paths and other related statistics such as maximum width of the slide, run-out distance, and slip surface area.

@article{Silva2020,
  title     = {Debris Run-Out Modeling Without Site-Specific Data},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {10},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {NMT De Silva and Prasad Wimalaratne},
  doi       = {10.14569/IJACSA.2020.0111015},
  url       = {https://doi.org/10.14569/IJACSA.2020.0111015}
}