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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.
Shrinking glaciers in the Hindu Kush-Karakoram-Himalaya-Nyainqentanglha (HKKHN) region have formed several thousand moraine-dammed glacial lakes(1-3), some of these having grown rapidly in past decades(3,4). This growth may promote more frequent and potentially destructive glacial lake outburst floods (GLOFs)(5-7). Testing this hypothesis, however, is confounded by incomplete databases of the few reliable, though selective, case studies. Here we present a consistent Himalayan GLOF inventory derived automatically from all available Landsat imagery since the late 1980s. We more than double the known GLOF count and identify the southern Himalayas as a hotspot region, compared to the more rarely affected Hindu Kush-Karakoram ranges. Nevertheless, the average annual frequency of 1.3 GLOFs has no credible posterior trend despite reported increases in glacial lake areas in most of the HKKHN3,8, so that GLOF activity per unit lake area has decreased since the late 1980s. We conclude that learning more about the frequency and magnitude of outburst triggers, rather than focusing solely on rapidly growing glacial lakes, might improve the appraisal of GLOF hazards.
Deforestation is a prominent anthropogenic cause of erosive overland flow and slope instability, boosting rates of soil erosion and concomitant sediment flux. Conventional methods of gauging or estimating post-logging sediment flux often focus on annual timescales but overlook potentially important process response on shorter intervals immediately following timber harvest. We resolve such dynamics with non-parametric quantile regression forests (QRF) based on high-frequency (3 min) discharge measurements and sediment concentration data sampled every 30-60 min in similar-sized (similar to 0.1 km(2)) forested Chilean catchments that were logged during either the rainy or the dry season. The method of QRF builds on the random forest algorithm, and combines quantile regression with repeated random sub-sampling of both cases and predictors. The algorithm belongs to the family of decision-tree classifiers, which allow quantifying relevant predictors in high-dimensional parameter space. We find that, where no logging occurred, similar to 80% of the total sediment load was transported during extremely variable runoff events during only 5% of the monitoring period. In particular, dry-season logging dampened the relative role of these rare, extreme sediment-transport events by increasing load efficiency during more efficient moderate events. We show that QRFs outperform traditional sediment rating curves (SRCs) in terms of accurately simulating short-term dynamics of sediment flux, and conclude that QRF may reliably support forest management recommendations by providing robust simulations of post-logging response of water and sediment fluxes at high temporal resolution.
Reconstructing how rivers respond to changes in runoff or sediment supply by incising or aggrading has been pivotal in gauging the role of the Indian Summer Monsoon (ISM) as a geomorphic driver in the Himalayas. Here we present new chronological data for fluvial aggradation and incision from the Donga alluvial fan and the upper Alaknanda River, as well as a compilation of previous work. In addition to conventional OSL-SAR (Single-Aliquot Regenerative-Dose) dating method, we have tested and applied pulsed OSL (POSL) dating for quartz samples that include K-rich feldspar inclusions, which is expected to improve the applicability and validity of OSL ages in the Lesser Himalaya. For previously dated deposits, our OSL ages are shown to be systematically older than previously reported ages. These results suggest periods of aggradation in the Alaknanda and Dehradun Valleys mainly between similar to 25 and 35 ka. This most likely reflects decreased stream power during periods of weakened monsoon. In addition, in-situ cosmogenic beryllium-10 was used to infer bedrock surface exposure ages, which are interpreted as episodes of active fluvial erosion. Resulting exposure ages span from 3 to 6 ka, suggesting that strath terraces were exposed relatively recently, and incision was dominant through most of the Holocene. In combination, our results support precipitation-driven fluvial dynamics, which regulates the balance between stream power and sediment supply. On a larger spatial scale, however, fluvial dynamics are probably not spatially homogeneous as aggradation could have been taking place in adjacent catchments while incision dominated in the study area. (C) 2018 Elsevier Ltd. All rights reserved.
In this study, we investigate how immersive 3D geovisualization can be used in higher education. Based on MacEachren and Kraak's geovisualization cube, we examine the usage of immersive 3D geovisualization and its usefulness in a research-based learning module on flood risk, called GEOSimulator. Results of a survey among participating students reveal benefits, such as better orientation in the study area, higher interactivity with the data, improved discourse among students and enhanced motivation through immersive 3D geovisualization. This suggests that immersive 3D visualization can effectively be used in higher education and that 3D CAVE settings enhance interactive learning between students.
Roads at risk
(2015)
Globalisation and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g. road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load, expressed as vehicle kilometres, because of debris-flow-related road closures. We present two scenarios demonstrating the impact of debris flows on the road network and quantify the associated path-failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and north-western part of the study area are associated with high link-failure risk. Yet options for detours on major routes are manifold and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying on speedy delivery of services and goods.
Supra-glacial deposition and flux of catastrophic rock-slope failure debris, south-central Alaska
(2013)
The ongoing debate over the effects of global environmental change on Earth's cryosphere calls for detailed knowledge about process rates and their variability in cold environments. In this context, appraisals of the coupling between glacier dynamics and para-glacial erosion rates in tectonically active mountains remain rare. We contribute to filling this knowledge gap and present an unprecedented regional-scale inventory of supra-glacial sediment flux and hillslope erosion rates inferred from an analysis of 123 large (> 0 center dot 1km2) catastrophic bedrock landslides that fell onto glaciers in the Chugach Mountains, Alaska, as documented by satellite images obtained between 1972 to 2008. Assuming these supra-glacial landslide deposits to be passive strain markers we infer minimum decadal-scale sediment yields of 190 to 7400tkm-2yr-1 for a given glacier-surface cross-section impacted by episodic rock-slope failure. These rates compare to reported fluvial sediment yields in many mountain rivers, but are an order of magnitude below the extreme sediment yields measured at the snouts of Alaskan glaciers, indicating that the bulk of debris discharged derives from en-glacial, sub-glacial or ice-proximal sources. We estimate an average minimum para-glacial erosion rate by large, episodic rock-slope failures at 0 center dot 5-0 center dot 7mmyr-1 in the Chugach Mountains over a 50-yr period, with earthquakes likely being responsible for up to 73% of this rate. Though ranking amongst the highest decadal landslide erosion rates for this size of study area worldwide, our inferred rates of hillslope erosion in the Chugach Mountains remain an order of magnitude below the pace of extremely rapid glacial sediment export and glacio-isostatic surface uplift previously reported from the region.
Quantifying volumes and rates of delivery of terrestrial sediment from island arcs to subduction zones is indispensable for refining estimates of the thickness of trench fills that may eventually control the location and timing of submarine landslides and tsunami-generating mega-earthquakes. Despite these motivating insights, knowledge about the rates of erosion and sediment export from the Japanese islands to their Pacific subduction zones remains patchy regardless of the increasing availability of highly resolved data on surface deformation, climate, geology, and topography. Traditionally, natural erosion rates across the island arc have been estimated from regression of topographic catchment metrics and reservoir sedimentation rates that were recorded over several years to decades. We review current research in this context, correct for a systematic bias in one of the most widely used predictions, and present new estimates of decadal to millennial-scale erosion rates of Japan's terrestrial inner forearc. We draw on several independent and unprecedented inventories of mass wasting, reservoir sedimentation, and concentrations of cosmogenic Be-10 in river sands. We find that natural Be-10-derived denudation rates of several mm yr(-1) in the Japanese Alps have been sustained over several centuries to millennia, and are, within error, roughly consistent with sediment yields inferred from artificial reservoir sedimentation. Local exceptions may likely result from release of sediment storage or regional landsliding episodes that trigger transient sediment pulses. Our synopsis further reveals that catchments draining Japan's eastern seaboard differ distinctly in their tectonic, lithological, topographic, and climatic characteristics between the Tohoku, Japanese Alps, and Nankai inner forearc segments, which is underscored by a marked asymmetric pattern of erosion rates along the island arc. Erosion rates are highest (up to at least 3 mm yr(-1)) in the Japanese Alps that mark the collision of two subduction zones, where high topographic relief, hillslope and bedrock-channel steepness foster rapid denudation by mass wasting. Comparable, if slightly lower, erosion rates characterise the Nankai inner forearc in southwest Japan, most likely due to higher typhoon-driven rainfall totals and variability rather than its high topographic relief. In contrast, our estimated erosion and flux rates are lowest in the Tohoku inner forearc catchments that feed sediment into the Japan Trench. We conclude that collisional mountain building of the Japanese Alps drives some of the highest erosion rates in the island arc despite similar uplift and precipitation controls in southwest Japan. We infer that, prior to extensive river damming, reservoir construction, and coastal works, the gross of Japan's total sediment export to the Pacific Ocean entered the accretionary margin of the Nankai Trough as opposed to the comparatively sediment-starved Japan Trench. Compared to documented contemporary rates of sediment flux from mountainous catchments elsewhere in the Pacific, the rivers draining Japan's inner forearc take an intermediate position despite high relief, steep slopes, very high seismicity, and frequent rainstorms. However, the average rates of millennial-scale denudation in the Japanese Alps particularly are amongst the highest reported worldwide.
Local mismatches between these late Holocene and modern rates emphasise the anthropogenic fingerprint on sediment retention that may have significantly reduced the island arc's mass flux to its subduction zones, as is the case elsewhere in east and southeast Asia. (C) 2014 Elsevier B.V. All rights reserved.
Modern natural hazards research requires dealing with several uncertainties that arise from limited process knowledge, measurement errors, censored and incomplete observations, and the intrinsic randomness of the governing processes. Nevertheless, deterministic analyses are still widely used in quantitative hazard assessments despite the pitfall of misestimating the hazard and any ensuing risks.
In this paper we show that Bayesian networks offer a flexible framework for capturing and expressing a broad range of uncertainties encountered in natural hazard assessments. Although Bayesian networks are well studied in theory, their application to real-world data is far from straightforward, and requires specific tailoring and adaptation of existing algorithms. We offer suggestions as how to tackle frequently arising problems in this context and mainly concentrate on the handling of continuous variables, incomplete data sets, and the interaction of both. By way of three case studies from earthquake, flood, and landslide research, we demonstrate the method of data-driven Bayesian network learning, and showcase the flexibility, applicability, and benefits of this approach.
Our results offer fresh and partly counterintuitive insights into well-studied multivariate problems of earthquake-induced ground motion prediction, accurate flood damage quantification, and spatially explicit landslide prediction at the regional scale. In particular, we highlight how Bayesian networks help to express information flow and independence assumptions between candidate predictors. Such knowledge is pivotal in providing scientists and decision makers with well-informed strategies for selecting adequate predictor variables for quantitative natural hazard assessments.
The 2008 eruption of Chaiten volcano in southern Chile severely impacted several densely forested river catchments by supplying excess pyroclastic sediment to the channel networks. Our aim is to substantiate whether and how channel geometry and forest stands changed in the Rayas River following the sudden input of pyroclastic sediment. We measured the resulting changes to channel geometry and riparian forest stands along 17.6 km of the impacted gravel-bed Rayas River (294 km(2)) from multiple high-resolution satellite images, aerial photographs, and fieldwork to quantify yield volume characteristics of the forest stands. Limited channel changes during the last 60 years before the eruption reflect a dynamic equilibrium condition of the river corridor, despite the high annual precipitation and the sediment supply from Chaiten and Michinmahuida volcanoes in the headwaters. Images taken in 1945, 2004, and 2005 show that total size of the vegetated channel islands nearly doubled between 1945 and 2004 and remained unchanged between 2004 and 2005. Pyroclastic sediment entering the Rayas River after the 2008 eruption caused only minor average channel widening (7%), but killed all island vegetation in the study reach. Substantial shifts in the size distribution of in-channel vegetation patches reflect losses in total island area of 46% from 2005 to 2009 and an additional 34% from 2009 to 2012. The estimated pulsed release of organic carbon into the channel, mainly in the form of large wood from obliterated island and floodplain forests, was 78-400 tC/km/y and surpasses most documented yields from small mountainous catchments with similar rainfall, forest cover, and disturbance history, while making up between 20% and 60% of the annual carbon burial rate of fluvial sediments in the northern Patagonian fjords. We conclude that the carbon footprint of the 2008 Chaiten eruption on the Rayas River was more significant than the measured geomorphic impacts on channel geometry for the first five years following disturbance. The modest post-eruptive geomorphic response in this river is a poor indicator of its biogeochemical response. (C) 2015 Elsevier B.V. All rights reserved.