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dc.contributor.authorDe Silva, N.M.T-
dc.description.abstractRecent population growth and developments taking place close to landslides prone hilly areas increase their vulnerability. Climate change impacts further raise the potential of landslide hazard. Therefore, to prevent loss of lives and damage to property, proper observation and analysis of unstable slope behavior is crucial. Landslide flow path forecasting is important for determining a landslide flow route and it is an essential element in hazard mapping. However, due to the complex nature of the phenomenon and the uncertainties of associated parameters flow path prediction is a challenging task. In this work, the major landslide incident at Aranayaka area in Kegalle district is taken as the case study to model the flow path. At the location, potential source areas were identified on the basis of the Digital Elevation Model. Spreading area assessment was based on two flow directional algorithms namely D8 and Multiple Direction Flow Algorithm. Using this prototype model, a user can interactively get landslide specific statistics such as the maximum width of the slide, runout distance, and slip surface area. Results obtained by the model were compared with the actual Aranayaka landslide data set the landslide hazard map of the area. Landslide flow paths generated from the implemented tool using D8 algorithm shows more than 65% agreement and Multiple Direction Flow Algorithm shows more than 69% agreement with the actual flow paths and other related statistics. Also, the generated flow path directions and predicted possible landslide initiation points fit inside the actual landslide boundary with good agreement.en_US
dc.titleLandslide flow path modelling A Case Study on Aranayaka Landslideen_US
Appears in Collections:2018

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