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The Tibetan Plateau, the world's largest orogenic plateau, hosts thousands of lakes that play prominent roles as water resources, environmental archives, and sources of natural hazards such as glacier lake outburst floods. Previous studies have reported that the size of lakes on the Tibetan Plateau has changed rapidly in recent years, possibly because of atmospheric warming. Tracking these changes systematically with remote sensing data is challenging given the different spectral signatures of water, the potential for confusing lakes with glaciers, and difficulties in classifying frozen or partly frozen lakes. Object-based image analysis (OBIA) offers new opportunities for automated classification in this context, and we have explored this method for mapping lakes from LANDSAT images and Shuttle Radar Topography Mission (SRTM) elevation data. We tested our algorithm for most of the Tibetan Plateau, where lakes in tectonic depressions or blocked by glaciers and sediments have different surface colours and seasonal ice cover in images obtained in 1995 and 2015. We combined a modified normalised difference water index (MNDWI) with OBIA and local topographic slope data in order to classify lakes with an area > 10 km(2). Our method derived 323 water bodies, with a total area of 31,258 km(2), or 2.6% of the study area (in 2015). The same number of lakes had covered only 24,892 km(2) in 1995; lake area has increased by -26% in the past two decades. The classification had estimated producer's and user's accuracies of 0.98, with a Cohen's kappa and F-score of 0.98, and may thus be a useful approximation for quantifying regional hydrological budgets. We have shown that our method is flexible and transferable to detecting lakes in diverse physical settings on several continents with similar success rates.
Large earthquakes initiate chains of surface processes that last much longer than the brief moments of strong shaking. Most moderate‐ and large‐magnitude earthquakes trigger landslides, ranging from small failures in the soil cover to massive, devastating rock avalanches. Some landslides dam rivers and impound lakes, which can collapse days to centuries later, and flood mountain valleys for hundreds of kilometers downstream. Landslide deposits on slopes can remobilize during heavy rainfall and evolve into debris flows. Cracks and fractures can form and widen on mountain crests and flanks, promoting increased frequency of landslides that lasts for decades. More gradual impacts involve the flushing of excess debris downstream by rivers, which can generate bank erosion and floodplain accretion as well as channel avulsions that affect flooding frequency, settlements, ecosystems, and infrastructure. Ultimately, earthquake sequences and their geomorphic consequences alter mountain landscapes over both human and geologic time scales. Two recent events have attracted intense research into earthquake‐induced landslides and their consequences: the magnitude M 7.6 Chi‐Chi, Taiwan earthquake of 1999, and the M 7.9 Wenchuan, China earthquake of 2008. Using data and insights from these and several other earthquakes, we analyze how such events initiate processes that change mountain landscapes, highlight research gaps, and suggest pathways toward a more complete understanding of the seismic effects on the Earth's surface.
Rock glaciers in semiarid mountains contain large amounts of ice and might be important water stores aside from glaciers, lakes, and rivers. Yet whether and how rock glaciers interact with river channels in mountain valleys remains largely unresolved. We examine the potential for rock glaciers to block or disrupt river channels, using a new inventory of more than 2000 intact rock glaciers that we mapped from remotely sensed imagery in the Karakoram (KR), Tien Shan (TS), and Altai (ALT) mountains. We find that between 5% and 14% of the rock glaciers partly buried, blocked, diverted or constricted at least 95 km of mountain rivers in the entire study area. We use a Bayesian robust logistic regression with multiple topographic and climatic inputs to discern those rock glaciers disrupting mountain rivers from those with no obvious impacts. We identify elevation and potential incoming solar radiation (PISR), together with the size of feeder basins, as dominant predictors, so that lower-lying and larger rock glaciers from larger basins are more likely to disrupt river channels. Given that elevation and PISR are key inputs for modelling the regional distribution of mountain permafrost from the positions of rock-glacier toes, we infer that river-blocking rock glaciers may be diagnostic of non-equilibrated permafrost. Principal component analysis adds temperature evenness and wet-season precipitation to the controls that characterise rock glaciers impacting on rivers. Depending on the choice of predictors, the accuracy of our classification is moderate to good with median posterior area-under-the-curve values of 0.71-0.89. Clarifying whether rapidly advancing rock glaciers can physically impound rivers, or fortify existing dams instead, deserves future field investigation. We suspect that rock-glacier dams are conspicuous features that have a polygenetic history and encourage more research on the geomorphic coupling between permafrost lobes, river channels, and the sediment cascades of semiarid mountain belts. (c) 2018 John Wiley & Sons, Ltd.
Increased landslide activity on forested hillslopes following two recent volcanic eruptions in Chile
(2019)
Large explosive eruptions can bury landscapes beneath thick layers of tephra. Rivers subsequently overloaded with excess pyroclastic sediments have some of the highest reported specific sediment yields. Much less is known about how hillslopes respond to tephra loads. Here, we report a pulsed and distinctly delayed increase in landslide activity following the eruptions of the Chaiten (2008) and Puyehue-Cordon Caulle (2011) volcanoes in southern Chile. Remote-sensing data reveal that land-slides clustered in densely forested hillslopes mostly two to six years after being covered by tephra. This lagged instability is consistent with a gradual loss of shear strength of decaying tree roots in areas of high tephra loads. Surrounding areas with comparable topography, forest cover, rainfall and lithology maintained landslide rates roughly ten times lower. The landslides eroded the landscape by up to 4.8 mm on average within 30 km of both volcanoes, mobilizing up to 1.6 MtC at rates of about 265 tC km(-2) yr(-1). We suggest that these yields may reinforce the elevated river loads of sediment and organic carbon in the decade after the eruptions. We recommend that studies of post-eruptive mass fluxes and hazards include lagged landslide responses of tephra-covered forested hillslopes, to avoid substantial underestimates.
Mountain rivers respond to strong earthquakes by rapidly aggrading to accommodate excess sediment delivered by co-seismic landslides. Detailed sediment budgets indicate that rivers need several years to decades to recover from seismic disturbances, depending on how recovery is defined. We examine three principal proxies of river recovery after earthquake-induced sediment pulses around Pokhara, Nepal's second largest city. Freshly exhumed cohorts of floodplain trees in growth position indicate rapid and pulsed sedimentation that formed a fan covering 150 km2 in a Lesser Himalayan basin with tens of metres of debris between the 11th and 15th centuries AD. Radiocarbon dates of buried trees are consistent with those of nearby valley deposits linked to major medieval earthquakes, such that we can estimate average rates of re-incision since. We combine high-resolution digital elevation data, geodetic field surveys, aerial photos, and dated tree trunks to reconstruct geomorphic marker surfaces. The volumes of sediment relative to these surfaces require average net sediment yields of up to 4200 t km–2 yr–1 for the 650 years since the last inferred earthquake-triggered sediment pulse. The lithological composition of channel bedload differs from that of local bedrock, confirming that rivers are still mostly evacuating medieval valley fills, locally incising at rates of up to 0.2 m yr–1. Pronounced knickpoints and epigenetic gorges at tributary junctions further illustrate the protracted fluvial response; only the distal portions of the earthquake-derived sediment wedges have been cut to near their base. Our results challenge the notion that mountain rivers recover speedily from earthquakes within years to decades. The valley fills around Pokhara show that even highly erosive Himalayan rivers may need more than several centuries to adjust to catastrophic perturbations. Our results motivate some rethinking of post-seismic hazard appraisals and infrastructural planning in active mountain regions.
Glacial lakes in the Hindu Kush–Karakoram–Himalayas–Nyainqentanglha (HKKHN) region have grown rapidly in number and area in past decades, and some dozens have drained in catastrophic glacial lake outburst floods (GLOFs). Estimating regional susceptibility of glacial lakes has largely relied on qualitative assessments by experts, thus motivating a more systematic and quantitative appraisal. Before the backdrop of current climate-change projections and the potential of elevation-dependent warming, an objective and regionally consistent assessment is urgently needed. We use an inventory of 3390 moraine-dammed lakes and their documented outburst history in the past four decades to test whether elevation, lake area and its rate of change, glacier-mass balance, and monsoonality are useful inputs to a probabilistic classification model. We implement these candidate predictors in four Bayesian multi-level logistic regression models to estimate the posterior susceptibility to GLOFs. We find that mostly larger lakes have been more prone to GLOFs in the past four decades regardless of the elevation band in which they occurred. We also find that including the regional average glacier-mass balance improves the model classification. In contrast, changes in lake area and monsoonality play ambiguous roles. Our study provides first quantitative evidence that GLOF susceptibility in the HKKHN scales with lake area, though less so with its dynamics. Our probabilistic prognoses offer improvement compared to a random classification based on average GLOF frequency. Yet they also reveal some major uncertainties that have remained largely unquantified previously and that challenge the applicability of single models. Ensembles of multiple models could be a viable alternative for more accurately classifying the susceptibility of moraine-dammed lakes to GLOFs.
Quaternary glaciations have repeatedly shaped large tracts of the Andean foreland. Its spectacular large glacial lakes, staircases of moraine ridges, and extensive outwash plains have inspired generations of scientists to reconstruct the processes, magnitude, and timing of ice build-up and decay at the mountain front. Surprisingly few of these studies noticed many dozens of giant (≥108 m3) mass-wasting deposits in the foreland. We report some of the world's largest terrestrial landslides in the eastern piedmont of the Patagonian Ice Sheet (PIS) along the traces of the former Lago Buenos Aires and Lago Puyerredón glacier lobes and lakes. More than 283 large rotational slides and lateral spreads followed by debris slides, earthflows, rotational and translational rockslides, complex slides and few large rock avalanches detached some 164 ± 56 km3 of material from the slopes of volcanic mesetas, lake-bounding moraines, and river-gorge walls. Many of these landslide deposits intersect with well-dated moraine ridges or former glacial-lake shorelines, and offer opportunities for relative dating of slope failure. We estimate that >60% of the landslide volume (∼96 km3) detached after the Last Glacial Maximum (LGM). Giant slope failures cross-cutting shorelines of a large Late Glacial to Early Holocene lake (“glacial lake PIS”) likely occurred during successive lake-level drop between ∼11.5 and 8 ka, and some of them are the largest hitherto documented landslides in moraines. We conclude that 1) large portions of terminal moraines can fail catastrophically several thousand years after emplacement; 2) slopes formed by weak bedrock or unconsolidated glacial deposits bordering glacial lakes can release extremely large landslides; and 3) landslides still occur in the piedmont, particularly along postglacial gorges cut in response to falling lake levels.
Glacial lakes in the Hindu Kush–Karakoram–Himalayas–Nyainqentanglha (HKKHN) region have grown rapidly in number and area in past decades, and some dozens have drained in catastrophic glacial lake outburst floods (GLOFs). Estimating regional susceptibility of glacial lakes has largely relied on qualitative assessments by experts, thus motivating a more systematic and quantitative appraisal. Before the backdrop of current climate-change projections and the potential of elevation-dependent warming, an objective and regionally consistent assessment is urgently needed. We use an inventory of 3390 moraine-dammed lakes and their documented outburst history in the past four decades to test whether elevation, lake area and its rate of change, glacier-mass balance, and monsoonality are useful inputs to a probabilistic classification model. We implement these candidate predictors in four Bayesian multi-level logistic regression models to estimate the posterior susceptibility to GLOFs. We find that mostly larger lakes have been more prone to GLOFs in the past four decades regardless of the elevation band in which they occurred. We also find that including the regional average glacier-mass balance improves the model classification. In contrast, changes in lake area and monsoonality play ambiguous roles. Our study provides first quantitative evidence that GLOF susceptibility in the HKKHN scales with lake area, though less so with its dynamics. Our probabilistic prognoses offer improvement compared to a random classification based on average GLOF frequency. Yet they also reveal some major uncertainties that have remained largely unquantified previously and that challenge the applicability of single models. Ensembles of multiple models could be a viable alternative for more accurately classifying the susceptibility of moraine-dammed lakes to GLOFs.
Flash floods and debris flows are iconic hazards inmountainous regions with steep relief, high rainfall intensities, rapid snowmelt events, and abundant sediments. The cuesta landscapes of southern Germany hardly come to mind when dealing with such hazards. A series of heavy rainstorms dumping up to 140mm in 2 h caused destructive flash floods and debris flows in May 2016. The most severe damage occurred in the Braunsbach municipality, which was partly buried by 42,000 m(3) of boulders, gravel, mud, and anthropogenic debris from the small catchment of Orlacher Bach (similar to 6 km(2)). We analysed this event by combining rainfall patterns, geological conditions, and geomorphic impacts to estimate an average sediment yield of 14,000 t/km(2) that mostly (similar to 95%) came from some 50 riparian landslides and channel-bed incision of similar to 2 m. This specific sediment yield ranks among the top 20% globally, while the intensity-duration curve of the rainstormis similarly in the upper percentile range of storms that had triggered landslides. Compared to similar-sized catchments in the greater region hit by the rainstorms, we find that the Orlacher Bach is above the 95th percentile in terms of steepness, storm-rainfall intensity, and topographic curvatures. The flash flood transported a sediment volume equal to as much as 20-40% of the Pleistocene sediment volume stored in the Orlacher Bach fan, andmay have had several predecessors in the Holocene. River control structures from 1903 and records of a debris flow in the 1920s in a nearby catchment indicate that the local inhabitants may have been aware of the debris-flow hazards earlier. Such recurring and destructive events elude flood-hazard appraisals in humid landscapes of gentle relief, and broaden mechanistic views of how landslides and debris flows contribute to shaping small and deeply cut tributaries in the southern Germany cuesta landscape.
Several thousands of moraine-dammed and supraglacial lakes spread over the Hindu Kush Himalayan (HKH) region, and some have grown rapidly in past decades due to glacier retreat. The sudden emptying of these lakes releases large volumes of water and sediment in destructive glacial lake outburst floods (GLOFs), one of the most publicised natural hazards to the rapidly growing Himalayan population. Despite the growing number and size of glacial lakes, the frequency of documented GLOFs is remarkably constant. We explore this possible reporting bias and offer a new processing chain for establishing a more complete Himalayan GLOF inventory. We make use of the full seasonal archive of Landsat images between 1988 and 2016, and track automatically where GLOFs left shrinking water bodies, and tails of sediment at high elevations. We trained a Random Forest classifier to generate fuzzy land cover maps for 2491 images, achieving overall accuracies of 91%. We developed a likelihood-based change point technique to estimate the timing of GLOFs at the pixel scale. Our method objectively detected ten out of eleven documented GLOFs, and another ten lakes that gave rise to previously unreported GLOFs. We thus nearly doubled the existing GLOF record for a study area covering similar to 10% of the HKH region. Remaining challenges for automatically detecting GLOFs include image insufficiently accurate co-registration, misclassifications in the land cover maps and image noise from clouds, shadows or ice. Yet our processing chain is robust and has the potential for being applied on the greater HKH and mountain ranges elsewhere, opening the door for objectively expanding the knowledge base on GLOF activity over the past three decades.