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Limited by the independence and its defects of each general software package, simultaneous analysis of runoff, seepage, and large-deformation analysis is still an inevitable challenge. Generally, one of seepage, landslide-related large-deformation, and runoff is ignored or indirectly assessed during unsaturated soil landslide runout simulation. To provide a brand new solution, this paper declares a local shear strength (LSS) method to evaluate rainfall/runoff-induced reduction of the unsaturated soil shear strength. After that, a hybrid coupled hydro-mechanical framework is proposed to simulate rainfall/runoff-induced landslide runout within an unsaturated soil slope. The decrease in local shear strength corresponding to the decrease in matric suction is defined by shifting the Mohr-Coulomb (M-C) failure envelope towards compressive stress space during rainfall/runoff infiltration. Based on the proposed local shear strength method, the variable matric suction obtained from the bidirectionally coupled runoff and seepage analysis in FEM is unidirectionally transferred to the variable local shear strength for each soil material point in MPM (i.e., this is a FEM-MPM hybrid coupled model). Then, the correctness of the proposed hybrid coupled hydro-mechanical framework is effectively verified by a hypothetical homogeneous slope model. The results show that the slope stable/unstable state simulated by the proposed hybrid coupled hydro-mechanical framework has a good consistency with that simulated by the shear strength reduction technique (SSRT) and limit-equilibrium method (LEM). Afterward, combined with a case study of a natural landslide in Hokkaido, Japan, it is proved to be effective for simulating landslide runout subjected to rainfall/runoff infiltration by using the proposed hybrid coupled hydro-mechanical framework in an unsaturated soil slope.

River-damming by landslides is a widespread phenomenon around the world. Recent advances in remote sensing technology and the rising commercial availability of their products enable the assemblage of increasingly more complete inventories and improve monitoring efforts. On the ground, multi-method dating campaigns enhance our understanding of the timelines of dam formation and failure. In comparison to single-dating methods, they reduce uncertainty by using different materials from the landslide deposit, facilitate the advantages of each method, and consider the deposit and the source area. They can pin dates on the time of lake drainage where backwater sediments are included in the dating campaign and thus inform about dam longevity. Geophysical methods provide non-invasive and rapid methods to investigate the properties and interior conditions of landslide dams. By identifying, e.g. evolving zones of weakness and saturation they can aid in the monitoring of a dam in addition to providing information on interior stratification for scientific research. To verify results from geophysical campaigns, and to add details of dam interior structures and geotechnical properties, knowledge of their sedimentology is essential. This information is gathered at sections from breached dams, other (partially) eroded landslide deposits, and through laboratory testing of sampled material. Combining the knowledge gained from all these methods with insights from blast-fill and embankment dam construction, physical and numerical modelling in multi-disciplinary research projects is the way forward in landslide dam research, assessment and monitoring. This review offers a broad, yet concise overview of the state-of-the-art in the aforementioned research fields. It completes the review of Fan et al. (2020) on the formation and impact on landslide dams.

In 2005, the Japanese government launched a new nationwide early warning system for predicting debris flow and slope failure disasters based on rainfall intensity and the Soil Water Index (SWI). However, the Japanese government has not set early warning criteria in many mountain areas. In addition, the existing early warning criteria in some areas are much higher than realistic ones, and snowmelt water is not considered in the calculation of the SWI. These two factors have been the cause of many slope failures in seasonally cold regions, induced by rainfall and/or snowmelt, which were not predicted. Therefore, this study attempts to propose a new determination method for setting early warning criteria for rainfall- and/or snowmelt-induced slope failures in seasonally cold regions. For this purpose, the study firstly proposes a combination model for estimating snow density that incorporates the hourly snowmelt water into the Japanese early warning system more accurately by using meteorological monitoring data and modeled snow density. Next, based on case studies and parametric analyses for slope stability assessment, new early warning criteria are proposed for predicting three different patterns of slope failures under two typical types of precipitation (rainfall and snowmelt) conditions. Finally, a new determination method for setting early warning criteria in seasonally cold regions is proposed by referring to the existing early warning criteria near the target area, in accordance with the precipitation types and the local ground conditions of the slopes. Since the existing early warning criteria near the target area already take the effects of the variations in local geology and geography into account, the new determination method for early warning criteria can be applied to arbitrary areas in seasonally cold regions, without directly considering the local soil properties, in the actual design and maintenance works.

High-velocity runoff generated in hillslopes during heavy rainfall caused by typhoon increases chances of instability of the embankment slopes at the exit of the gully. Such effects of high-velocity runoff are usually neglected in conventional rainfall-induced slope failure analysis. In order to consider the effects of runoff on the slope instability, this study attempts to simulate the runoff, infiltration, seepage, and slope instabilities on a small catchment-scale simultaneously. For this purpose, this study firstly proposes a coupled model of surface flow, subsurface flow, and soil mechanics based on shallow water equations, Richards's equation, Green-Ampt infiltration capacity model, and local factor of safety (LFS) approach. Next, to make the proposed coupled model effective in the practical analysis of runoff, a diffusion wave approximation of shallow water equations is validated by numerical simulations, and then it is used to replace shallow water equations in the proposed coupled model. Finally, the proposed coupled model is verified by Abdul and Gillham system and applied to a natural slope in Hokkaido, Japan inside a small catchment with an area of 0.4675 km(2). The numerical results highlight the influences of runoff from upstream on the embankment slope failure at the exit of the gully. Furthermore, the small catchment-scale slope instabilities assessment approach proposed in this study provides an effective approach for simulating heavy rainfall induced runoff and slope instabilities. The distribution map of the factor of safety (FOS) has significant implications for precisely determining the dangerous spots (instead of areas) on a small catchment-scale and accurately releasing early warning information to these dangerous spots.

In Hokkaido, Japan, soil slope failures occur frequently during the snow melting season. These slope failures are triggered by the excess amount of water derived from snowmelt and rainfall. For the prediction of snowmelt-induced soil slope failures in seasonally cold regions, an early warning criterion is required. The existing Japanese early warning criteria for sediment disasters, i.e., the relationship between the 60-min cumulative rainfall and the Soil Water Index (SWI), the effective rainfall index etc., consider the influence of rainfall and the time-dependent random moisture of the soil. However, these criteria do not consider the soil moisture contributed by the snowmelt water. In this study, therefore, the applicability of the existing early warning criteria to predict snowmelt-induced soil slope failures is examined. An empirical method to quantify the amount of snowmelt water is presented. Various scenarios of conceptual soil slope failures are studied using numerical simulations under different magnitudes of rainfall and snowmelt water. As a result, a revision is introduced for the SWI and the effective rainfall index, adding the amount of snowmelt water to that of rainfall, and slope failure scenarios are studied. Based on the results, a new early warning criterion, the Effective Precipitation (EP) index, is introduced. It is found that the new failure criterion performs well for the prediction of snowmelt-induced soil slope failures.

In Hokkaido Japan, soil slope failures along some of the national highways are reported frequently in recent years. A stability assessment method which can consider the impact of seasonal changes like freeze-thaw action, snow melt water infiltration etc. is of utmost importance and considered to be an immediate requirement for geotechnical practitioners, in order to properly predict the slope stability. In this study, a slope stability assessment approach based on two-dimensional numerical modelling is recommended which considers the water content changes of the soil induced by the seasonal climatic effects i.e. freeze-thaw action, snowmelt water infiltration etc. Two case studies of slope failures in Hokkaido have been studied using the recommended approach. In order to visualise the climatic parameters of most influence on slope stability, parametric studies have been performed through which many useful results in view of the soil slope stability in seasonal cold regions have been obtained. It is found that the freeze-thaw action has a considerable impact on the soil water content and slope stability. On the other hand, the snowmelt water infiltration has a very significant impact on soil slope stability. The recommended numerical modelling approach is found to be very useful in analysing the soil slope stability in seasonal cold regions. (C) 2017 Elsevier B.V. All rights reserved.