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
Be 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
, 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.
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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•Large-scale understanding of landslide dynamics is lacking for risk mitigation.•We propose a method to detect recurrent and persistent landslides.•86 % of landslide areas were persistent or recurrent in the Himalaya.•22 % of landslide areas experienced at least three episodes of landslides in 30 years.•Transboundary landslide patterns related to anthropogenic, climate, and seismic factors
We present a monitoring technique tailored to analysing change from near-continuously collected, high-resolution 3-D data. Our aim is to fully characterise geomorphological change typified by an ...event magnitude–frequency relationship that adheres to an inverse power law or similar. While recent advances in monitoring have enabled changes in volume across more than 7 orders of magnitude to be captured, event frequency is commonly assumed to be interchangeable with the time-averaged event numbers between successive surveys. Where events coincide, or coalesce, or where the mechanisms driving change are not spatially independent, apparent event frequency must be partially determined by survey interval.The data reported have been obtained from a permanently installed terrestrial laser scanner, which permits an increased frequency of surveys. Surveying from a single position raises challenges, given the single viewpoint onto a complex surface and the need for computational efficiency associated with handling a large time series of 3-D data. A workflow is presented that optimises the detection of change by filtering and aligning scans to improve repeatability. An adaptation of the M3C2 algorithm is used to detect 3-D change to overcome data inconsistencies between scans. Individual rockfall geometries are then extracted and the associated volumetric errors modelled. The utility of this approach is demonstrated using a dataset of ∼ 9 × 103 surveys acquired at ∼ 1 h intervals over 10 months. The magnitude–frequency distribution of rockfall volumes generated is shown to be sensitive to monitoring frequency. Using a 1 h interval between surveys, rather than 30 days, the volume contribution from small (< 0.1 m3) rockfalls increases from 67 to 98 % of the total, and the number of individual rockfalls observed increases by over 3 orders of magnitude. High-frequency monitoring therefore holds considerable implications for magnitude–frequency derivatives, such as hazard return intervals and erosion rates. As such, while high-frequency monitoring has potential to describe short-term controls on geomorphological change and more realistic magnitude–frequency relationships, the assessment of longer-term erosion rates may be more suited to less-frequent data collection with lower accumulative errors.
Earthquakes trigger landslides in mountainous regions. Recent research suggests that the stability of hillslopes during and after a large earthquake is influenced by legacy effects of previous ...seismic activity. However, the shear strength and strain response of ductile hillslope materials to sequences of earthquake ground shaking of varying character is poorly constrained, inhibiting our ability to fully explain the nature of earthquake‐triggered landslides. We used geotechnical laboratory testing to simulate earthquake loading of hillslopes and to assess how different sequences of ground shaking influence hillslope stability prior to, during, and following an earthquake mainshock. Ground‐shaking events prior to a mainshock that do not result in high landslide strain accumulation can increase bulk density and interparticle friction. This strengthens a hillslope, reducing landslide displacement during subsequent seismicity. By implication, landscapes in different tectonic settings will likely demonstrate different short‐ and long‐term responses to single earthquakes due to differences in the magnitude, frequency, and sequencing of earthquakes.
Key Points
We used laboratory testing to simulate the effects of earthquake sequences of different character on landslide shear strength and behavior
Ground shaking that does not cause high strain accumulation in landslides can increase bulk density in ductile hillslope materials
This increases interparticle contact and so strengthens a landslide, reducing susceptibility to subsequent seismicity
Rockfalls commonly exhibit power law volume‐frequency distributions, where fewer large events are observed relative to more numerous small events. Within most inventories, the smallest rockfalls are ...the most difficult to detect and so may not be adequately represented. A primary challenge occurs when neighboring events within a single monitoring interval are recorded as one, producing ambiguity in event location, timing, volume, and frequency. Identifying measurement intervals that minimize these uncertainties is therefore essential. To address this, we use an hourly data set comprising 8,987 3‐D point clouds of a cliff that experiences frequent rockfalls. Multiple rockfall inventories are derived from this data set using change detections for the same 10‐month period, but over different monitoring intervals. The power law describing the probability distribution of rockfall volumes is highly sensitive to monitoring interval. The exponent, β, is stable for intervals >12 hr but increases nonlinearly over progressively short timescales. This change is manifested as an increase in observed rockfall numbers, from 1.4 × 103 (30 day intervals) to 1.4 × 104 (1 hr intervals), and a threefold reduction in mean rockfall volume. When the monitoring interval exceeds 4 hr, the geometry of detected rockfalls becomes increasingly similar to that of blocks defined by rock mass structure. This behavior change reveals a time‐dependent component to rockfall occurrence, where smaller rockfalls (identifiable from more frequent monitoring) are more sensitive to progressive deformation of the rock mass. Acquiring complete inventories and attributing discrete controls over rockfall occurrence may therefore only be achievable with high‐frequency monitoring, dependent upon local lithology.
Plain Language Summary
Rockfall inventories are required to model erosion, such as along coastlines or in mountain landscapes, and hazard from rockfall activity. The frequency distribution of rockfall volumes, commonly termed “magnitude‐frequency”, is important for this modeling and for our understanding of how rockfalls occur and what drives them. For rockfalls and landslides in general, these distributions typically follow a power law, with relatively few larger rockfalls as compared to more numerous small events. Advances in hardware and algorithms have considerably improved the spatial resolution and precision with which a given rock face can be monitored using LiDAR. This has in turn improved our ability to detect small rockfalls, which in sum contribute significantly to overall volume loss from rock slopes in this setting. The improvement in spatial resolution has, however, considerably outpaced improvements in the temporal resolution of monitoring. If the interval between surveys is greater than the return interval of rockfalls, neighboring rockfalls within a single monitoring interval are recorded as one, producing ambiguity in event, timing, and volume. For the latter, this effect may amount to an order of magnitude variation. Our research aimed to examine the timescales over which rockfalls occur, allowing us to identify suitable monitoring intervals to discretize rockfalls. While conventional monitoring campaigns tend to acquire surveys at monthly intervals or longer, we draw upon a 1 hr resolution data set acquired over 10 months. We find that the interval of monitoring has a considerable impact on the probability distribution of measured rockfall volumes. An order of magnitude increase in rockfall numbers and a threefold decrease in mean rockfall volume are observed over timescales (monitoring intervals) of 1 hr, rather than 30 days. This is represented by a change in the power law exponent of the magnitude‐frequency relationship, which increases nonlinearly below timescales of ~12 hr. Interestingly, above ~12 hr, the exponent is stable, suggesting that changes in monitoring interval above this timescale will attain almost identical rockfall inventories. We explain this change in behavior by relating the geometry of rockfalls to the geometry of the blocks from which they are released. The average size of rockfalls identified over timescales below ~4 hr is comparable to the scale of individual discontinuities, indicating that fragmented detachments are more likely to control the increase in small events. As the timescale of rockfall monitoring increases, detachments become more similar to the rock mass structure, indicating structural control on failure. This behavior change suggests that smaller rockfalls are more sensitive to progressive deformation of the rock mass. This type of analysis is required to constrain the timescales over which this process occurs, which is necessary to understand prior to attributing specific drivers (such as storms) to rockfall occurrence.
Key Points
The magnitude‐frequency distribution of rockfall inventories is highly sensitive to the time interval between monitoring surveys
Monitoring intervals below ~12 hr yield a nonlinear increase in the number of rockfalls observed and a decrease in mean rockfall volume
At monitoring intervals above ~12 hr, the distribution is stable and rockfall geometry converges with that defined by rock mass structure
Debris-flow fans form a ubiquitous record of past debris-flow activity in mountainous areas, and may be useful for inferring past flow characteristics and consequent future hazard. Extracting ...information on past debris flows from fan records, however, requires an understanding of debris-flow deposition and fan surface evolution; field-scale studies of these processes have been very limited. In this paper, we document the patterns and timing of debris-flow deposition on the surface of the large and exceptionally active Illgraben fan in southwestern Switzerland. We use terrain analysis, radiocarbon dating of sediment fill in the Illgraben catchment, and cosmogenic 10Be and 36Cl exposure dating of debris-flow deposits on the fan to constrain the temporal evolution of the sediment routing system in the catchment and on the fan during the past 3200years. We show that the fan surface preserves a set of debris-flow lobes that were predominantly deposited after the occurrence of a large rock avalanche near the fan apex at about 3200years ago. This rock avalanche shifted the apex of the fan and impounded sediment within the Illgraben catchment. Subsequent evolution of the fan surface has been governed by both lateral and radial shifts in the active depositional lobe, revealed by the cosmogenic radionuclide dates and by cross-cutting geometrical relationships on the fan surface. This pattern of frequent avulsion and fan surface occupation provides field-scale evidence of the type of large-scale compensatory behavior observed in experimental sediment routing systems.
•First documentation of timing and patterns of debris-flow deposition on the Illgraben fan since 3200yr ago•Fan surface shows evidence for repeated lateral and radial shifts in the active depositional lobe.•Rock avalanche deposition has shifted the fan apex location by c. 500m.•Field evidence of repeated avulsion, backstepping of deposits, and fan-head incision•Direct correlation between fan deposition and climate change may be complicated by short-term variations in sediment supply.
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