• Journal of Korean Society of Forest Science
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• v.103 no.2
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• pp.218-225
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• 2014

Landslides, one of earth's natural disasters, increase every year due to heavy rainfall, and cause damage to human life and assets. This study used the SHALSTAB to predict places at risk of landslides, in accordance with the intensity of rainfall. The parameter value of transmissivity was $19.58m^2/day$, the internal friction angle $36.3^{\circ}$, and the saturated unit weight $2.03t/m^3$. The slope stability status was classified into four categories, namely: unconditionally stable, stable, unstable and unconditionally unstable. In order to evaluate the applicability of the SHALSTAB, actual landslide areas were checked, with the unstable area under 263 mm rainfall. 85.1% of them were consistent. And so we can identify the distribution of places at risk of landslides, on the basis of the intensity of rainfall by means of SHALSTAB.

• Journal of The Geomorphological Association of Korea
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• v.18 no.4
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• pp.193-202
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• 2011

Kompsat EOC-1 imagery, high resolution air-photo imagery and Shalstab model were used to analyze the geomorphic characteristics of the place of debris flow occurred by typhon "RUSA" in 2002, Macheon-Myen, Gyeongsang prefecture, Republic of Korea. On gully-head over 35 degree of slope angle, almost debris flow started, where slope angle is more than internal friction angle. The result simulated by Shalstab model presented larger vulnerable area to debris flow than the area where debris flow really occurred, this error would be attributed to the assumption for steady-state condition with full saturated surface. To predict the debris flow accurately, further study for rainfall and soil water flow will be needed.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.281-281
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• 2015

Shallow landslide often occurs in areas of this topography where subsurface soil water flow paths give rise to excess pore-water pressures downslope. Recent hillslope hydrology studies have shown that subsurface topography has a strong impact in controlling the connectivity of saturated areas at the soil-bedrock interface. In this study, the physically based SHALSTAB model was used to evaluate the effects of three soil thicknesses (i.e. average soil layer, soil thickness to weathered soil and soil thickness to bedrock soil layer) and subsurface flow reflecting three soil thicknesses on shallow landslide prediction accuracy. Three digital elevation models (DEMs; i.e. ground surface, weathered surface and bedrock surface) and three soil thicknesses (average soil thickness, soil thickness to weathered rock and soil thickness to bedrock) at a small hillslope site in Jinbu, Kangwon Prefecture, eastern part of the Korean Peninsula, were considered. Each prediction result simulated with the SHALSTAB model was evaluated by receiver operating characteristic (ROC) analysis for modelling accuracy. The results of the ROC analysis for shallow landslide prediction using the ground surface DEM (GSTO), the weathered surface DEM and the bedrock surface DEM (BSTO) indicated that the prediction accuracy was higher using flow accumulation by the BSTO and weathered soil thickness compared to results. These results imply that 1) the effect of subsurface flow by BSTO on shallow landslide prediction especially could be larger than the effects of topography by GSTO, and 2) the effect of weathered soil thickness could be larger than the effects of average soil thickness and bedrock soil thickness on shallow landslide prediction. Therefore, we suggest that using BSTO dem and weathered soil layer can improve the accuracy of shallow landslide prediction, which should contribute to more accurately predicting shallow landslides.