Search

Strong earthquakes in mountainous areas can trigger a large number of landslides that generate deposits of loose and unconsolidated debris across the landscape. These deposits can be easily remobilised by rainfalls, with their movement frequently evolving into catastrophic debris flows and avalanches. This has been the fate of many of the 200,000 co-seismic deposits generated by the 2008 Mw 7.9 Wenchuan earthquake in Sichuan, China. Here we present one of the first studies on the post-seismic patterns of landsliding through a detailed multi-temporal inventory that covers a large portion of the epicentral area (462.5 km2). We quantify changes of size-frequency distribution, active volumes and type of movement. We analyse the possible factors controlling landslide activity and we discuss the significance of mapping uncertainties. We observe that the total number of active landslides decreased with time significantly (from 9189 in 2008 to 221 in 2015), and that post-seismic remobilisations soon after the earthquake (2008-2011) occurred stochastically with respect to the size of the co-seismic deposits. Subsequently (2013-2015), landslide rates remained higher in larger deposits than in smaller ones, particularly in proximity to the drainage network, with channelised flows becoming comparatively more frequent than hillslope slides. However, most of the co-seismic debris remained along the hillslopes and are largely stabilised, urging to rethink the way we believe that seismic activity affects the erosion patterns in mountain ranges. [ABSTRACT FROM AUTHOR]

We release two datasets that track the enhanced landsliding induced by the Mw 7.9 2008 Wenchuan earthquake over a portion of the Longmen mountains, at the eastern margin of the Tibetan plateau (Sichuan, China). The first dataset is a geo-referenced multi-temporal polygon-based inventory of pre- and coseismic landslides, post-seismic remobilisations of coseismic landslide debris, and post-seismic landslides (new failures). The inventory covers 462.5 km² in the earthquake's epicentral area, from 2005 to 2015. The second dataset records the debris flows that occurred from 2008 to 2017 in a larger area (~ 17,000 km²), together with information on their triggering rainfalls recorded by a network of rain gauges. For some well-monitored event, we provide detailed information on rainfall, discharge, flow depth and density. The datasets can be used to analyse, at various scales, the patterns of enhanced landsliding caused by the earthquake. They can be compared to inventories relative to past or new earthquakes or other triggers to reveal common or distinctive controlling factors. To our knowledge, no other inventories that track the temporal evolution of earthquake-induced mass wasting have been made freely available thus far. Our datasets are available at https://doi.org/10.5281/zenodo.1405490. We also encourage other researchers to share their datasets to facilitate research on post-seismic geological hazards. [ABSTRACT FROM AUTHOR]

On 8th August 2017, a magnitude Ms 7.0 earthquake struck the County of Jiuzhaigou, in Sichuan Province, China. It was the third Ms ≥ 7.0 earthquake in the Longmenshan area in the last decade, after the 2008 Ms 8.0 Wenchuan earthquake and the 2013 Ms 7.0 Lushan earthquake. The event did not produce any evident surface rupture but triggered significant mass wasting. Based on a large set of pre- and post-earthquake high-resolution satellite images (SPOT-5, Gaofen-1 and Gaofen-2) as well as on 0.2-m-resolution UAV photographs, a polygon-based interpretation of the coseismic landslides was carried out. In total, 1883 landslides were identified, covering an area of 8.11 km2, with an estimated total volume in the order of 25-30 × 106 m3. The total landslide area was lower than that produced by other earthquakes of similar magnitude with strike-slip motion, possibly because of the limited surface rupture. The spatial distribution of the landslides was correlated statistically to a number of seismic, terrain and geological factors, to evaluate the landslide susceptibility at regional scale and to identify the most typical characteristics of the coseismic failures. The landslides, mainly small-scale rockfalls and rock/debris slides, occurred mostly along two NE-SW-oriented valleys near the epicentre. Comparatively, high landslide density was found at locations where the landform evolves from upper, broad valleys to lower, deep-cut gorges. The spatial distribution of the coseismic landslides did not seem correlated to the location of any known active faults. On the contrary, it revealed that a previously-unknown blind fault segment—which is possibly the north-western extension of the Huya fault—is the plausible seismogenic fault. This finding is consistent with what hypothesised on the basis of field observations and ground displacements. [ABSTRACT FROM AUTHOR]

The rock avalanche that destroyed the village of Xinmo in Sichuan, China, on June 24th, 2017, brought the issue of landslide risk and disaster chain management in highly seismic regions back into the spotlight. The long-term post-seismic behaviour of mountain slopes is complex and hardly predictable. Nevertheless, the integrated use of field monitoring, remote sensing and real-time predictive modelling can help to set-up effective early warning systems, provide timely alarms, optimize rescue operations and perform secondary hazard assessments. We believe that a comprehensive discussion on post-seismic slope stability and on its implications for policy makers can no longer be postponed. [ABSTRACT FROM AUTHOR]

Evaluating physical properties and mechanical parameters of rock slopes and their spatial variability is challenging, particularly at locations inaccessible for fieldwork. This obstacle can be bypassed by acquiring spatially-distributed field data indirectly. InfraRed Thermography (IRT) has emerged as a promising technology to statistically infer rock properties and inform slope stability models. Here, we explore the use of Cooling Rate Indices (CRIs) to quantify the thermal response of a granodiorite rock wall within the recently established Požáry Test Site in Czechia. We observe distinct cooling patterns across different segments of the wall, compatible with the different degrees of weathering evaluated in the laboratory and suggested by IRT observations of cored samples. Our findings support previous examinations of the efficacy of this method and unveil correlations between cooling phases in the field and in the laboratory. We discuss the scale-dependency of the Informative Time Window (ITW) of the CRIs, noting that it may serve as a reference for conducting systematic IRT field surveys. We contend that our approach not only represents a viable and scientifically robust strategy for characterising rock slopes but also holds the potential for identifying unstable areas., (© 2024. The Author(s).)