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Slow-moving landslide-prone areas (SLAs) are unstable objects on the terrestrial surface that can collapse rapidly when provoked by earthquakes, leading to infrastructure damage. It is critical to identify SLAs prior to earthquake events and assess their hazard-causing probabilities when triggered. An assessment approach of earthquake-triggered geohazards is proposed in this paper by combining interferometric synthetic aperture radar (InSAR) derived SLAs and geological and geomorphological factors. Taking the Ms6.8 Luding earthquake, which occurred in the Sichuan Province of southwestern China on September 5, 2022, as an example, 1320 scenes of Sentinel-1 SAR data in western Sichuan were processed using the small baseline subset (SBAS) InSAR technique before the earthquake. After the earthquake, hazard probability assessment was performed in real-time by filtering the SLAs using a spatial analysis technique with geological and geomorphological factors, e.g., real-time peak ground acceleration (PGA), slope, distance to fault (DTF), and distance to the river (DTR) data. The results show that 11 SLAs were classified into high-risk zones. As verified by the Luding co-seismic landslide dataset from visual interpretation of optical remote sensing images, 142 coseismic landslides were triggered by the earthquake in these high-risk regions. In these areas, an ancient landslide, with high pre-earthquake displacement rates (−50 mm/year) on the scarp was reactivated under the Luding earthquake forces. This method can provide a scientific tool for disaster mitigation and rapid response emergency management. [ABSTRACT FROM AUTHOR]

Typhoons are recurring meteorological phenomena in the southeastern coastal area of China, frequently triggering debris flows and other forms of slope failures that result in significant economic damage and loss of life in densely populated and economically active regions. Accurate prediction of typhoon-triggered debris flows and identification of high-risk zones are imperative for effective risk management. Surprisingly, little attention has been devoted to the construction of physical vulnerability curves in typhoon-affected areas, as a basis for risk assessment. To address this deficiency, this paper presents a quantitative method for developing physical vulnerability curves for buildings by modeling debris flow intensity and building damage characteristics. In this study, we selected the Wangzhuangwu watershed, in Zhejiang Province of China, which was impacted by a debris flow induced by Typhoon Lekima on August 10, 2019. We conducted detailed field surveys after interpreting remote sensing imagery to analyze the geological features and the mechanism of the debris flow and constructed a comprehensive database of building damage characteristics. To model the 2019 debris flow initiation, entrainment, and deposition processes, we applied the Soil Conservation Service-Curve Number (SCS-CN) approach and a two-dimensional debris flow model (FLO-2D). The reconstructed debris flow depth and extent were validated using observed debris flow data. We generated physical vulnerability curves for different types of building structures, taking into account both the degree of building damage and the modeled debris flow intensity, including flow depth and impact pressure. Based on calibrated rheological parameters, we modeled the potential intensity of future debris flows while considering various recurrence frequencies of triggering rainfall events. Subsequently, we calculated the vulnerability index and economic risk associated with buildings for different frequencies of debris flow events, employing diverse vulnerability functions that factored in uncertainty in both intensity indicators and building structures. We observed that the vulnerability function utilizing impact pressure as the intensity indicator tends to be more conservative than the one employing flow depth as a parameter. This comprehensive approach efficiently generated physical vulnerability curves and a debris flow risk map, providing valuable insights for effective disaster prevention in areas prone to debris flows. [ABSTRACT FROM AUTHOR]

Landslides frequently disrupt roadway networks in mountainous regions worldwide. Because of the relatively long roadway extension and low roadway density in mountainous regions, the occurrence of a landslide hazard along a local road segment will cause traffic paralysis on the individual roadway and will further impact regional roadway network accessibility. This paper establishes an integrative risk assessment framework based on risk theory and complex network theory to combine the results of landslide susceptibility mapping along roadways and impact assessment on the roadway network. Through an analysis of the relationship between various geo-environmental conditioning factors and historical landslides along roadways, the support vector machine (SVM) model is used to assess landslide susceptibility across the regional roadway network. Both topological connectivity of the entire roadway network and transport accessibility between local residents are considered in the impact assessment on roadway networks. To illustrate the effectiveness of the proposed risk assessment framework, a case study of the roadway network in Fengjie County, China, which is prone to landslide occurrence, is conducted. The resulting landslide risk heatmap of Fengjie County's roadway network is generated using ArcGIS software. The most critical road segments are identified as being highly susceptible to landslides, and if they are disrupted, the entire roadway network will suffer significant performance loss. The results can support adaptive strategies for landslide mitigation, preparedness, and emergency response services, as well as improve roadway plans to reduce exposure and associated consequences by adding new links to the existing roadway network. [ABSTRACT FROM AUTHOR]

Rainfall infiltration in unsaturated slopes alters the effective stress through pore water pressure changes, thus causing ground deformation. Although important to assess the timescale over which the margin of safety of a slope decreases, such coupled processes are rarely accounted in the context of spatially distributed hazard assessment procedures. In this paper, a physically based, spatially distributed model accounting for full hydro-mechanical coupling is discussed. The model relies on a vectorized finite element (FE) solver to calculate the stability of deformable unsaturated infinite slopes subjected to transient flow. First, the FE solver is used to study the response of individual slopes to a prolonged rainfall for three scenarios (i.e., rigid, swelling, and collapsible soil). Then, the model is used in the context of spatially distributed computations to assess spatiotemporal variations of factor of safety over a large area. For this purpose, a series of shallow landslides occurred in a mountainous landscape covered by collapsible loess deposits in northwestern China was used as test site. The analyses show that hydro-mechanical couplings affect the performance of the model in terms of computed failure time and areal extent of the unstable zones. Specifically, volume collapse due to suction decrease is found to reduce the time of failure compared with uncoupled computations obtained for a rigid soil scenario. The most substantial advantages of using coupled analyses have been reported with reference to gentle slopes, for which the higher rate of suction reduction driven by volume change was crucial to capture landslide source areas that would otherwise be overlooked by uncoupled analyses. The proposed methodology offers a complete tool for landslide hazard assessment, in that it incorporates sources of coupling between hydrology and mechanics that are crucial to replicate the physics of landslide initiation. [ABSTRACT FROM AUTHOR]

An Ms 6.5 earthquake shocked the Ludian County, Yunnan Province, China, on 3 August 2014 and triggered the Hongshiyan landslide dam. The dam, with a height of 83 m and a lake capacity of 260 × 10 m, threatened more than 10,000 people. A unique feature of this landslide dam was that it formed between a man-made dam and a hydropower plant. An existing drainage tunnel connecting the lake and the hydropower plant became a natural drainage conduit for the landslide dam, which played an important role in the mitigation of the landslide dam risks. This paper reports a quantitative risk assessment for the Hongshiyan landslide dam considering both engineering and non-engineering risk mitigation measures. The risk assessment is divided into three stages according to the implementation of two engineering measures: construction of a diversion channel and excavation of a branch drainage tunnel. The dam breaching hydrographs, flood zones, population at risk, and likely fatalities in each of the three stages are analysed. The optimum evacuation strategy in each stage is also studied based on the principle of minimum total consequence. It is found that the diversion channel decreases the dam breaching peak discharge and the associated risks significantly. The branch drainage tunnel prevent the landslide dam from overtopping failure in non-flooded period; however, the landslide dam may fail by overtopping in a future flood if the inflow rate is larger than the outflow rate through the drainage tunnels, resulting in serious losses of lives and properties. The dam breaching risks in all the three stages could be largely reduced by the optimal evacuation decision, which shows that timely evacuation is vital to save life and properties. The study provides a scientific basis for decision making in landslide dam risk management. [ABSTRACT FROM AUTHOR]

In tectonically active steep mountain belts, such as those in west Sichuan in China, frequent landslide disasters can occur during the rainy season. High-locality landslides often initiate with the failure of fractured rock masses or regolith near the ridge of a high and steep slope. Often, these events occur suddenly in the sense that people downslope are caught by surprise. High-locality landslides can be destructive owing to the large momentum and entrainment potential of the moving mass. Increasing attention has been given to these events since the 2008 Wenchuan earthquake. Indeed, slope ridges are particularly susceptible of topographic amplification of the seismic shaking, resulting in mechanical weakening that predisposes them to enhanced weathering and rain-triggered failures years or decades after the mainshock. Risk reduction in such cases must begin with a systematic surveying of the ridges to identify criticalities. Then, quantitative (numerical) approaches must be used to evaluate volumes and describe the movement. Risk assessments can then be produced, and mitigations suggested. Here, we describe the Tonghua landslide in Li County, which is currently in a creeping stage but threatens critical infrastructures and dwellings. We monitored the site for 3 years and identified additional potentially unstable areas before performing physically based modeling and hazard zonation. Our results could be useful in decision-making for risk reduction. [ABSTRACT FROM AUTHOR]

An accurate and timely inventory for major landslides triggered by seismic events is essential for hazard assessment and risk governance. Sentinel-2 MultiSpectral Instrument (MSI) data have been increasingly used for co-seismic landslide mapping in recent years. However, there have been few studies exploring the full use of Sentinel-2 near infrared (NIR) narrow, red-edge, and short-wave infrared (SWIR) bands for landslide mapping. In this study, Sentinel-2 10-m fused NIR narrow, red-edge-1, SWIR-1, and SWIR-2 bands were incorporated into the change detection-based Markov random field (CDMRF) that considers the spectral, spatial, and contextual information of landslides. The effectiveness of the developed method was proved in mapping co-seismic landslides triggered by two major earthquakes in the Yarlung Tsangpo Grand Canyon, China, in 2017 and Hokkaido, Japan, in 2018. The results demonstrated that the mapping performances with the fused Sentinel-2 bands were significantly improved for both seismic events. Such improvement is mainly attributed to the more abundant spectral information provided by the fused Sentinel-2 red-edge, NIR narrow, and SWIR bands. The novelties of this study are (1) the preliminary attempt to use the Sentinel-2 10-m fused bands for landslide mapping, and (2) the synergy of Sentinel-2 red-edge, NIR narrow, and SWIR bands for more reliable landslide mapping. [ABSTRACT FROM AUTHOR]