• The Journal of Engineering Geology
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• v.22 no.3
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• pp.283-291
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• 2012

Various studies regarding the prediction of landslides are underway internationally. Research into disaster prevention with regard to debris flows is a particular focus of research because this type of landslide can cause enormous damage over a short period. The objective of this study is to determine the hazard susceptibility of debris flow via predictions of surface water concentrations based on the concept that a debris flow is similar to a surface water flow, as it is influenced by mountain topography. This study considered urban areas affected by large debris flows or landslides. Digital mapping (including the slope and upslope contributing areas) and the wetness index were used to determine the relevant topographic factors and the hydrology of the area. We determined the hazard susceptibility of debris flow by predicting the surface water concentration based on the topography of the surrounding mountainous terrain. Results obtained using the distinct element method were used to derive a correlation equation between the weight and the impact force of the debris flow. We consider that in using a correlation equation, this method could assist in the effective installation of debris-flow-prevention structures.

• Journal of the Korean Geographical Society
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• v.44 no.2
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• pp.122-145
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• 2009

Terrain parameters calculated from digital elevation models (DEM) have become increasingly important in current spatially distributed models of earth surface processes. This paper investigated how the ability of upslope area for predicting the spatial distribution of soil properties varies depending on the selection of spatial resolutions of DEM and algorithms. Four soil attributes from eight soil-terrain data sets collected from different environments were used. Five different methods of calculating upslope area were first compared for their dependency on different grid sizes of DEM. Multiple flow algorithms produced the highest correlation coefficients for most soil attributes and the lowest variations amongst different DEM resolutions and soil attributes. The high correlation coefficient remained unchanged at resolutions from 15 m to 50 m. Considering decreasing topographical details with increasing grid size, we suggest that the size of 15-30 m may be most suitable for soil-landscape analysis purposes in our study areas.