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Geomorphic footprints of past large Himalayan earthquakes are elusive, although they are urgently needed for gauging and predicting recovery times of seismically perturbed mountain landscapes. We present evidence of catastrophic valley infill following at least three medieval earthquakes in the Nepal Himalaya. Radiocarbon dates from peat beds, plant macrofossils, and humic silts in fine-grained tributary sediments near Pokhara, Nepal’s second-largest city, match the timing of nearby M > 8 earthquakes in ~1100, 1255, and 1344 C.E. The upstream dip of tributary valley fills and x-ray fluorescence spectrometry of their provenance rule out local sources. Instead, geomorphic and sedimentary evidence is consistent with catastrophic fluvial aggradation and debris flows that had plugged several tributaries with tens of meters of calcareous sediment from a Higher Himalayan source >60 kilometers away.
Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.
Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.
Dealing with predicted increases in extreme weather conditions due to climate change requires robust knowledge about controls on rainfall-triggered landslides. We explore relationships between rainfall and landslide size throughout the Japanese archipelago. We test whether the total volume of landslides can be predicted directly from rainfall totals, intensity, and duration using a nationwide inventory of 4744 rainfall-triggered landslides recorded from A.D. 2001 to 2011. We find that larger landslides were more abundant at the expense of smaller ones when total, maximum, and mean rainfall intensity exceeded similar to 250 mm, similar to 35 mm/h, and similar to 4 mm/h, respectively. Frequency distributions of these rainfall parameters are peaked and heavily skewed. Yet neither the most frequent nor the most extreme values of these rainfall metrics coincide consistently with the maximum landslide volumes. A striking decrease of landslide volumes at both mean and maximum rainfall intensity, as well as duration, points to an exhaustion in hillslope geomorphic response regardless of sample size, landslide type, mobilized volume, dominant lithology, or reporting bias. Our results underscore substantial offsets between the peaks of rainfall metrics and maximum associated landslide volumes, thus complicating straightforward estimates of geomorphic work from metrics of rainstorm magnitude or frequency. Only the rainfall total appears to be a suitable monotonic predictor of landslide volumes mobilized during typhoons and frontal storms.
Limits to lichenometry
(2015)
Lichenometry is a straightforward and inexpensive method for dating Holocene rock surfaces. The rationale is that the diameter of the largest lichen scales with the age of the originally fresh rock surface that it colonised. The success of the method depends on finding the largest lichen diameters, a suitable lichen-growth model, and a robust calibration curve. Recent critique of the method motivates us to revisit the accuracy and uncertainties of lichenometry. Specifically, we test how well lichenometry is capable of resolving the ages of different lobes of large active rock glaciers in the Kyrgyz Tien Shan. We use a bootstrapped quantile regression to calibrate local growth curves of Xanthoria elegans, Aspicilia tianshanica, and Rhizocarpon geographicum, and report a nonlinear decrease in dating accuracy with increasing lichen diameter. A Bayesian type of an analysis of variance demonstrates that our calibration allows discriminating credibly between rock-glacier lobes of different ages despite the uncertainties tied to sample size and correctly identifying the largest lichen thalli. Our results also show that calibration error grows with lichen size, so that the separability of rock-glacier lobes of different ages decreases, while the tendency to assign coeval ages increases. The abundant young (<200 yr) specimen of fast-growing X elegans are in contrast with the fewer, slow-growing, but older (200-1500 yr) R. geographicum and A. tianshanica, and record either a regional reactivation of lobes in the past 200 years, or simply a censoring effect of lichen mortality during early phases of colonisation. The high variance of lichen sizes captures the activity of rock-glacier lobes, which is difficult to explain by regional climatic cooling or earthquake triggers alone. Therefore, we caution against inferring palaeoclimatic conditions from the topographic position of rock-glacier lobes. We conclude that lichenometry works better as a tool for establishing a relative, rather than an absolute, chronology of rock-glacier lobes in the northern Tien Shan. (C) 2015 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.
The northern edge of the western central Tien Shan range is bounded by the Issyk-Ata fault situated south of Bishkek, the capital of Kyrgyzstan. Contraction in this thick-skinned orogen occurs with low-strain accumulation and long earthquake recurrence intervals. In the nineteenth to twentieth centuries, a sequence of large earthquakes with magnitudes between 6.9 and 8 affected the northern Tien Shan but left nearly the entire extent of the Issyk-Ata fault unruptured. Here, the only known historic earthquake ruptured in A.D. 1885 (M6.9) along the western end of the Issyk-Ata fault. Because earthquakes in low-strain regions often tend to cluster in time and may promote failure along nearby structures, the earthquake history of the northern Tien Shan represents an exceptional structural setting for studying fault behavior affected by an intraplate earthquake sequence. We present a paleoseismological study from one site (Belek) along the Issyk-Ata fault located east of the A.D. 1885 epicentral area. Our analysis combines a range of tools, including photogrammetry, differential Global Positioning System, 3D visualization, and age modeling with different dating methods (infrared stimulated luminescence, radiocarbon, U-series) to improve the reliability of an event chronology for the trench stratigraphy and fault geometry. We were able to distinguish three different surfacerupturing paleoearthquakes; these affected the area before 10.5 +/- 1.1 cal ka B.P., at similar to 5.6 +/- 1.0 cal ka B.P., and at similar to 630 +/- 100 cal B.P., respectively. Associated paleomagnitudes for the last two earthquakes range between M6.7 and 7.4, with a cumulative slip rate of 0.7 +/- 0.32 mm/yr. We did not find evidence for the A.D. 1885 event at Belek. Our study yielded two main overall results: first, it extends the regional historic and paleoseismic record; second, the documented rupture events along the Issyk-Ata fault suggest that this fault was not affected in its entirety; instead, these events indicate segmented rupture behavior.
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.
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.
Much of contemporary landslide research is concerned with predicting and mapping susceptibility to slope failure. Many studies rely on generalised linear models with environmental predictors that are trained with data collected from within and outside of the margins of mapped landslides. Whether and how the performance of these models depends on sample size, location, or time remains largely untested. We address this question by exploring the sensitivity of a multivariate logistic regression-one of the most widely used susceptibility models-to data sampled from different portions of landslides in two independent inventories (i.e. a historic and a multi-temporal) covering parts of the eastern rim of the Fergana Basin, Kyrgyzstan. We find that considering only areas on lower parts of landslides, and hence most likely their deposits, can improve the model performance by >10% over the reference case that uses the entire landslide areas, especially for landslides of intermediate size. Hence, using landslide toe areas may suffice for this particular model and come in useful where landslide scars are vague or hidden in this part of Central Asia. The model performance marginally varied after progressively updating and adding more landslides data through time. We conclude that landslide susceptibility estimates for the study area remain largely insensitive to changes in data over about a decade. Spatial or temporal stratified sampling contributes only minor variations to model performance. Our findings call for more extensive testing of the concept of dynamic susceptibility and its interpretation in data-driven models, especially within the broader framework of landslide risk assessment under environmental and land-use change.
Much of contemporary landslide research is concerned with predicting and mapping susceptibility to slope failure. Many studies rely on generalised linear models with environmental predictors that are trained with data collected from within and outside of the margins of mapped landslides. Whether and how the performance of these models depends on sample size, location, or time remains largely untested. We address this question by exploring the sensitivity of a multivariate logistic regression-one of the most widely used susceptibility models-to data sampled from different portions of landslides in two independent inventories (i.e. a historic and a multi-temporal) covering parts of the eastern rim of the Fergana Basin, Kyrgyzstan. We find that considering only areas on lower parts of landslides, and hence most likely their deposits, can improve the model performance by >10% over the reference case that uses the entire landslide areas, especially for landslides of intermediate size. Hence, using landslide toe areas may suffice for this particular model and come in useful where landslide scars are vague or hidden in this part of Central Asia. The model performance marginally varied after progressively updating and adding more landslides data through time. We conclude that landslide susceptibility estimates for the study area remain largely insensitive to changes in data over about a decade. Spatial or temporal stratified sampling contributes only minor variations to model performance. Our findings call for more extensive testing of the concept of dynamic susceptibility and its interpretation in data-driven models, especially within the broader framework of landslide risk assessment under environmental and land-use change.
The Indus River, one of Asia's premier rivers, drains the western Tibetan Plateau and the Nanga Parbat syntaxis. These two areas juxtapose some of the lowest and highest topographic relief and commensurate denudation rates in the Himalaya-Tibet orogen, respectively, yet the spatial pattern of denudation rates upstream of the syntaxis remains largely unclear, as does the way in which major rivers drive headward incision into the Tibetan Plateau. We report a new inventory of Be-10-based basinwide denudation rates from 33 tributaries flanking the Indus River along a 320 km reach across the western Tibetan Plateau margin. We find that denudation rates of up to 110 mm k.y.(-1) in the Ladakh and Zanskar Ranges systematically decrease eastward to 10 mm k.y.(-1) toward the Tibetan Plateau. Independent results from bulk petrographic and heavy mineral analyses support this denudation gradient. Assuming that incision along the Indus exerts the base-level control on tributary denudation rates, our data show a systematic eastward decrease of landscape downwearing, reaching its minimum on the Tibetan Plateau. In contrast, denudation rates increase rapidly 150-200 km downstream of a distinct knick-point that marks the Tibetan Plateau margin in the Indus River longitudinal profile. We infer that any vigorous headward incision and any accompanying erosional waves into the interior of the plateau mostly concerned reaches well below this plateau margin. Moreover, reported long-term (>10(6) yr) exhumation rates from low-temperature chronometry of 0.1-0.75 mm yr(-1) consistently exceed our Be-10-derived denudation rates. With averaging time scales of 10(3)-10(4) yr for our denudation data, we report postglacial rates of downwearing in a tectonically idle landscape. To counterbalance this apparent mismatch, denudation rates must have been higher in the Quaternary during glacial-interglacial intervals.
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.
Moderate to large earthquakes can increase the amount of water feeding stream flows, mobilizing excess water from deep groundwater, shallow groundwater, or the vadose zone. Here we examine the regional pattern of streamflow response to the Maule M8.8 earthquake across Chile's diverse topographic and hydro-climatic gradients. We combine streamflow analyses with groundwater flow modeling and a random forest classifier, and find that, after the earthquake, at least 85 streams had a change in flow. Discharge mostly increased () shortly after the earthquake, liberating an excess water volume of >1.1 km3, which is the largest ever reported following an earthquake. Several catchments had increased discharge of >50 mm, locally exceeding seasonal streamflow discharge under undisturbed conditions. Our modeling results favor enhanced vertical permeability induced by dynamic strain as the most probable process explaining the observed changes at the regional scale. Supporting this interpretation, our random forest classification identifies peak ground velocity and elevation extremes as most important for predicting streamflow response. Given the mean recurrence interval of ∼25 yr for >M8.0 earthquakes along the Peru–Chile Trench, our observations highlight the role of earthquakes in the regional water cycle, especially in arid environments.
Fjords and old-growth forests store large amounts of organic carbon. Yet the role of episodic disturbances, particularly volcanic eruptions, in mobilizing organic carbon in fjord landscapes covered by temperate rainforests remains poorly quantified. To this end, we estimated how much wood and soils were flushed to nearby fjords following the 2008 eruption of Chaiten volcano in south-central Chile, where pyroclastic sediments covered >12km(2) of pristine temperate rainforest. Field-based surveys of forest biomass, soil organic content, and dead wood transport reveal that the reworking of pyroclastic sediments delivered similar to 66,500+14,600/-14,500tC of large wood to two rivers entering the nearby Patagonian fjords in less than a decade. A similar volume of wood remains in dead tree stands and buried beneath pyroclastic deposits (similar to 79,900+21,100/-16,900tC) or stored in active river channels (5,900-10,600tC). We estimate that bank erosion mobilized similar to 132,300(+21,700)/(-30,600)tC of floodplain forest soil. Eroded and reworked forest soils have been accreting on coastal river deltas at >5mmyr(-1) since the eruption. While much of the large wood is transported out of the fjord by long-shore drift, the finer fraction from eroded forest soils is likely to be buried in the fjords. We conclude that the organic carbon fluxes boosted by rivers adjusting to high pyroclastic sediment loads may remain elevated for up to a decade and that Patagonian temperate rainforests disturbed by excessive loads of pyroclastic debris can be episodic short-lived carbon sources. Plain Language Summary Fjords and old-growth forests are important sinks of organic carbon. However, the role of volcanic eruptions in flushing organic carbon in fjord landscapes remains unexplored. Here we estimated how much forest vegetation and soils were lost to fjords following the 2008 eruption ofunknownChaiten volcano in south-central Chile. Pyroclastic sediments obliterated near-pristine temperateunknownrainforest, and the subsequent reworking of these sediments delivered in less than a decade similar to 66,000 tC of large wood to the mountain rivers, draining into the nearby Patagonian fjords. A similar volume of wood remains in dead tree stands and buried beneath pyroclastic deposits or stored in active riverunknownchannels. We estimate that similar to 130,000 tC of organic carbon-rich soil was lost to erosion, thus adding to the carbon loads. While much of the wood enters the long-shore drift in the fjord heads, the finerunknownfraction from eroded forest soils is likely to be buried in the fjords at rates that exceed regional estimates by an order of magnitude. We anticipate that these eruption-driven fluxes will remain elevated forunknownthe coming years and that Patagonian temperate rainforests episodically switch from carbon sinks to hitherto undocumented carbon sources if disturbed by explosive volcanic eruptions.
The Norwegian traffic network is impacted by about 2000 landslides, avalanches, and debris flows each year that incur high economic losses. Despite the urgent need to mitigate future losses, efforts to locate potential debris flow source areas have been rare at the regional scale. We tackle this research gap by exploring a minimal set of possible topographic predictors of debris flow initiation that we input to a Weights-of-Evidence (WofE) model for mapping the regional susceptibility to debris flows in western Norway. We use an inventory of 429 debris flows that were recorded between 1979 and 2008, and use the terrain variables of slope, total curvature, and contributing area (flow accumulation) to compute the posterior probabilities of local debris flow occurrence. The novelty of our approach is that we quantify the uncertainties in the WofE approach arising from different predictor classification schemes and data input, while estimating model accuracy and predictive performance from independent test data. Our results show that a percentile-based classification scheme excels over a manual classification of the predictor variables because differing abundances in manually defined bins reduce the reliability of the conditional independence tests, a key, and often neglected, prerequisite for the WofE method. The conditional dependence between total curvature and flow accumulation precludes their joint use in the model. Slope gradient has the highest true positive rate (88%), although the fraction of area classified as susceptible is very large (37%). The predictive performance, i.e. the reduction of false positives, is improved when combined with either total curvature or flow accumulation. Bootstrapping shows that the combination of slope and flow accumulation provides more reliable predictions than the combination of slope and total curvature, and helps refining the use of slope-area plots for identifying morphometric fingerprints of debris flow source areas, an approach used outside the field of landslide susceptibility assessments.
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.