How landslide-triggering rainfall conditions vary with geology is unclear. The effects of three different geological conditions (gneiss, GN; granite, GR; sedimentary rock, SR) on variations in intensity–duration (I-D) conditions and rainfall characteristics responsible for initiating shallow landslides were examined using data from 476 landslides in South Korea from 1963 to 2018 and detailed statistical analyses. Results from quantile regression and one-way analysis of variance analyses clearly showed that impermeable SR slopes result in smaller critical rainfall than permeable GN and GR slopes do, indicating a relatively high occurrence exceedance probability and susceptibility to landslides in SR slope. These findings suggest that geological conditions, particularly the relatively high susceptibility of SR slopes, should be considered when establishing rainfall information-based landslide warning criteria for South Korea. Our findings can contribute to the assessment of landslide susceptibility and probability based on geological conditions; however, they should be further investigated through in situ observations.

This study aimed to determine the depositional effect and improve the identification of debris flow risk zones. To accomplish this goal, we developed a two-dimensional debris flow model (Deb2D) based on a hyperbolic conservation form of the mass and the momentum balance equation with consideration of the erosion–entrainment effect as well as the depositional effect. In this model, we implemented a widely-used rheological equation—the Voellmy equation—and a quadtree adaptive grid-based shallow-water equation. This model was applied to two study sites to assess the depositional effect. The impact area, volume of soil loss, maximum velocity, inundated depth, and erosion depth resulting from the debris-flow modeling were compared with the field data. The simulation results with/without deposition were evaluated using the receiver operating characteristic method. The implementation results of the erosion–entrainment model with deposition showed superior accuracy when estimating the damage range and flow time.

The main purpose of this study is to develop an optimal river dredging management model by applying MCDA (Multi-Criteria Decision Analysis) technique specifically in Korea where river dredging research are scarce. This model supports the decision making by providing weight factors covering dredging cost, and social and environmental impacts. This model requires various input data which are dredging points, dredging machines, dewatering machines, disposal sites. Furthermore, for the model development, the researcher applied imaginary dredging project area for model assessment and analysis. We used a total of 5 cases of weight factors combination. It can classify weight factors combination in 2 categories. The first category is weight factors combination for single-objective optimization and another category is weight factors combination for multi-objective optimization. The single-objective optimization is same that one weight factor is 1.0 and other weight factor is 0.0. The multi-objective optimization is used equality weight factors combination or weight factors from previous study. According to model simulation, it shows that cost of dredging is different approximately 18% due to weight factors. Besides, the maximum cost is obtained when weight factor of social impact is 1.0. In contrast, minimum cost of dredging projects is discovered when weight factor of cost is 1.0. From the weight factors in previous study, it illustrates that there are about 2% beyond the minimum cost of dredging projects, and approximately 18% less than maximum cost. Next study will be used real river dredging areas or simulation results of bed changes. The results of this study can be efficiently applied to 4 major rivers in Korea where periodical river dredging is necessary

To build a comprehensive understanding of long-term hydro-mechanical processes that lead to shallow landslide hazards, this study explicitly monitored the volumetric water content (VWC) and rainfall amount for a weathered granite soil slope over a four year period. From the 12 operational landslide monitoring stations installed across South Korea, the Songnisan station was selected as the study site. VWC sensors were placed in the subsurface with a grid-like arrangement at depths of 0.5 and 1.0 m. Shallow landslide hazards were evaluated by applying an infinite slope stability model that adopted a previously proposed unified effective stress concept. By analyzing the variations in the monitored VWC values, the derived matric suctions and suction stresses, and the calculated factor of safety values, we were able to obtain numerous valuable insights. In particular, the seasonal effects of drainage and evapotranspiration on the slope moisture conditions and slope stability were addressed. Preliminary test results indicated that continuous rainfall successfully represented the derived matric suction conditions at a depth of 1.0 m in the lower slope, although this was not the case for the upper and middle slopes. The significance of a future study on cumulative field monitoring data from various sites in different geological conditions is highlighted.