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Earthquake-triggered landslides show three important characteristics: they are often responsible for a considerable proportion of the damage sustained during mountain region earthquakes, they are non-randomly distributed across space, and they continue to evolve in the years after the earthquake. Despite this, planning for future earthquakes rarely takes into consideration either landslides or their evolution with time. Here we couple a unique timeseries of mapped landslides between 2014-2020 across the area of Nepal impacted by the 2015 Mw 7.8 Gorkha earthquake and a numerical landslide runout model overlain with building locations to examine how the distributions of both evolving landslide hazard and exposure intersect to generate a dynamic threat to buildings. The threat from landslide runout is shown to change in predictable ways after the earthquake, becoming more pronounced at mid- and lower-hillslope positions and remaining in the landscape for multiple years. Using the positions of our mapped landslides as a starting point, we can identify a priori the locations of 78% of buildings that were subsequently impacted by landslide debris. We show that landslide exposure and hazard vary from negligible to high, in relative terms, over lateral distances of as little as 10s of m. Our findings hold important implications for guiding reconstruction and for taking steps to reduce the risks from future earthquakes.
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Terremotos , Deslizamientos de Tierra , Nepal , Humanos , Modelos TeóricosRESUMEN
This paper presents a remote sensing-based method to efficiently generate multi-temporal landslide inventories and identify recurrent and persistent landslides. We used free data from Landsat, nighttime lights, digital elevation models, and a convolutional neural network model to develop the first multi-decadal inventory of landslides across the Himalaya, spanning from 1992 to 2021. The model successfully delineated >265,000 landslides, accurately identifying 83 % of manually mapped landslide areas and 94 % of reported landslide events in the region. Surprisingly, only 14 % of landslide areas each year were first occurrences, 55-83 % of landslide areas were persistent and 3-24 % had reactivated. On average, a landslide-affected pixel persisted for 4.7 years before recovery, a duration shorter than findings from small-scale studies following a major earthquake event. Among the recovered areas, 50 % of them experienced recurrent landslides after an average of five years. In fact, 22 % of landslide areas in the Himalaya experienced at least three episodes of landslides within 30 years. Disparities in landslide persistence across the Himalaya were pronounced, with an average recovery time of 6 years for Western India and Nepal, compared to 3 years for Bhutan and Eastern India. Slope and elevation emerged as significant controls of persistent and recurrent landslides. Road construction, afforestation policies, and seismic and monsoon activities were related to changes in landslide patterns in the Himalaya.
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An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Predicted sea-level rise and increased storminess are anticipated to lead to increases in coastal erosion. However, assessing if and how rocky coasts will respond to changes in marine conditions is difficult due to current limitations of monitoring and modelling. Here, we measured cosmogenic 10Be concentrations across a sandstone shore platform in North Yorkshire, UK, to model the changes in coastal erosion within the last 7 kyr and for the first time quantify the relative long-term erosive contribution of landward cliff retreat, and down-wearing and stripping of rock from the shore platform. The results suggest that the cliff has been retreating at a steady rate of 4.5 ± 0.63 cm yr-1, whilst maintaining a similar profile form. Our results imply a lack of a direct relationship between relative sea level over centennial to millennial timescales and the erosion response of the coast, highlighting a need to more fully characterise the spatial variability in, and controls on, rocky coast erosion under changing conditions.
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The ability to rapidly access optical satellite imagery is now an intrinsic component of managing the disaster response that follows a major earthquake. These images provide synoptic data on the impacts, extent, and intensity of damage, which is essential for mitigating further losses by feeding into the response coordination. However, whilst the efficiency of the response can be hampered when cloud cover limits image availability, spatio-temporal variations in cloud cover have never been considered as part of the design of effective disaster mapping. Here we show how annual variations in cloud cover may affect our capacity to respond rapidly throughout the year and consequently contribute to overall earthquake risk. We find that on a global scale when accounting for cloud, the worst time of year for an earthquake disaster is between June and August. During these months, 40% of the global population at risk from earthquakes are obscured from optical satellite view for >3 consecutive days. Southeastern Asia is particularly strongly affected, accounting for the majority of the population at risk from earthquakes that could be obscured by cloud in every month. Our results demonstrate the importance of the timing of earthquakes in terms of our capacity to respond effectively, highlighting the need for more intelligent design of disaster response that is not overly reliant on optical satellite imagery.
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Although the size-frequency distributions of icebergs can provide insight into how they disintegrate, our understanding of this process is incomplete. Fundamentally, there is a discrepancy between iceberg power-law size-frequency distributions observed at glacial calving fronts and lognormal size-frequency distributions observed globally within open waters that remains unexplained. Here we use passive seismic monitoring to examine mechanisms of iceberg disintegration as a function of drift. Our results indicate that the shift in the size-frequency distribution of iceberg sizes observed is a product of fracture-driven iceberg disintegration and dimensional reductions through melting. We suggest that changes in the characteristic size-frequency scaling of icebergs can be explained by the emergence of a dominant set of driving processes of iceberg degradation towards the open ocean. Consequently, the size-frequency distribution required to model iceberg distributions accurately must vary according to distance from the calving front.
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Shales play an important role in many earth system processes including coastal erosion, and they form the foundations of many engineering structures. The geobiology of the interior of pyrite-containing receding shale cliffs on the coast of northeast England was examined. The surface of the weathered shales was characterised by a thin layer of disordered authigenic iron oxyhydroxides and localised acicular, platy and aggregated gypsum, which was characterised by Raman spectroscopy, XAS and SEM. These chemical changes are likely to play an important role in causing rock weakening along fractures at the micron scale, which ultimately lead to coastal retreat at the larger scale. The surface of the shale hosts a novel, low-diversity microbial community. The bacterial community was dominated by Proteobacteria, with phylotypes closely associating with Methylocella and other members of the γ-subdivision. The second largest phylogenetic group corresponded to Nitrospira. The archaeal 16S rRNA phylotypes were dominated by a single group of sequences that matched phylotypes reported from South African gold mines and possessed ammonia monooxygenase (amoA) genes. Both the phylogenetic and the mineral data show that acidic microenvironments play an important role in shale weathering, but the shale has a higher microbial diversity than previously described pyritic acid mine drainage sites. The presence of a potentially biogeochemically active microbial population on the rock surface suggests that microorganisms may contribute to early events of shale degradation and coastal erosion.