Shallow slope failures occur almost every year during the rainy season. Continuous observation of the meteorological parameters and hydrological characteristics is required to more clearly understand the triggering mechanisms of shallow slope failure. In addition, influential factors, such as type of relative permeability models, air flow, and variation of hydraulic conductivity associated with stress–strain behavior of soil, have significant effects on the actual mechanism of rainfall infiltration. Real-time data including hourly rainfall and pore water pressure in response to rainfall was recorded by devices; then, the change in pore pressure from the devices was compared to the results from the infiltration analysis with applications of three relative permeability models, air flow, and the coupled hydro-mechanical analysis to examine an appropriate site-specific approach to a rainfall infiltration analysis. The infiltration and stability analyses based on the site-specific hydrologic characteristics were utilized to create maps of safety factors that depend on the cumulative rainfall. In regions vulnerable to landslides, rainfall forecast information and safety factor maps built by applying various rainfall scenarios can be useful in preparing countermeasures against disasters during the rainy season.

Over 160 shallow landslides resulted from heavy rainfall that occurred in 26–27 July 2011 at Umyeon Mountain, Seoul, South Korea. To accurately reflect the fluid flow mechanism in the void spaces of soils, we considered the two-phase flow of water and air for rainfall infiltration analysis using available historical rainfall data, topographic maps, and geotechnical/hydrological properties. Variations in pore water and air pressure from the infiltration analysis are used for slope stability assessment. By comparing the results from numerical models applying single- and two-phase flow models, we observed that air flow changes the rate of increase in pore water pressure, influencing the safety factor on slopes with a low infiltration capacity, where ponding is more likely to occur during heavy rainfall. Finally, several slope failure assessments were conducted to evaluate the usefulness of using the two-phase flow model in forecasting slope stability in conditions of increased rainfall sums. We observed that the two-phase flow model reduces the tendency of over-prediction compared to the single-phase model. The results from the two-phase flow model revealed good agreement with actual landslide events.

A regional-scale landslide early warning system was developed in collaboration with a city government. The structure and distinctive features of the system are described in detail. This system employs the principles of the sequential evaluation method that consecutively applies three different evaluation stages: statistical, physically based, and geomorphological evaluations. Based on this method, the system determines five phases of warning levels with improved levels of certainty and credibility. In particular, the warning levels are systematically derived to enable the discrimination of slope failures and debris flows. To provide intuitive and pragmatic information regarding the warning capabilities of the system, a comprehensive performance analysis was conducted. Early warning level maps were generated and a historical landslide database was established for the study period from 2009 to 2016. As a result, 81% of historical slope failures and 86% of historical debris flows were correctly predicted by high-class warning levels. Miscellaneous details associated to the timing efficiency of warnings were also investigated. Most notably, five high-class warning level events and four landslide events were recorded for a study region during the eight-year period. The four landslide events were all successfully captured by four out of the five warning events.