Refine
Has Fulltext
- no (35)
Year of publication
Document Type
- Article (35) (remove)
Language
- English (35) (remove)
Is part of the Bibliography
- yes (35)
Keywords
- Nepal (3)
- hydropower (3)
- Graph theory (2)
- Himalaya (2)
- Himalayas (2)
- glacial hazards (2)
- glacial lake outburst floods (2)
- water resources (2)
- 3D CAVE (1)
- ALS (1)
- Badlands (1)
- Bayesian statistics (1)
- Betula pubescens Ehrh. ssp czerepanovii (1)
- Bray-Curtis (1)
- Catastrophic valley infill (1)
- Channel steepness index (1)
- Chao (1)
- Chile (1)
- Climate change (1)
- Complexity (1)
- Debris flows (1)
- Delft-FLOW (1)
- Digital elevation model (1)
- Digital elevation models (1)
- Digital terrain analysis (1)
- Drainage networks (1)
- Drylands (1)
- Ecohydrology (1)
- Effective number of species (1)
- Fluvial geomorphology (1)
- Full-waveform (1)
- Fuzzy (1)
- Geomorphic coupling (1)
- Geomorphology (1)
- Geosciences (1)
- Great Himalayan earthquakes (1)
- HEC-RAS (1)
- Incomplete inventories (1)
- Inundation (1)
- Issyk Kul (1)
- Jaccard (1)
- Kyrgyzstan (1)
- Last Glacial Maximum (1)
- LiDAR (1)
- Macrolepidoptera (1)
- Maritime Alps (1)
- Model landscape (1)
- Morisita (1)
- Morisita-Horn (1)
- NESS (1)
- Networks (1)
- Norfolk Island (1)
- Norway (1)
- Paleoseismology (1)
- Point cloud (1)
- Process domains (1)
- Provenance analysis (1)
- Radiocarbon age dating (1)
- Rainfall simulation (1)
- Resilience (1)
- Rivers (1)
- Rocky deserts (1)
- Sediment cascades (1)
- Sediment connectivity (1)
- Sierra nevada (1)
- Slope-area plot (1)
- Spatially explicit models (1)
- Structural models (1)
- Susceptibility (1)
- Tectonics (1)
- Uncertainty (1)
- Water (1)
- Weights-of-Evidence (1)
- WorldView-2 (1)
- aboveground biomass (1)
- belowground biomass (1)
- canyon (1)
- cosmogenic nuclides (1)
- decision tree (1)
- digital elevation model (1)
- digital terrain analysis (1)
- drainage networks (1)
- dynamics (1)
- earthquake (1)
- earthquakes (1)
- flood (1)
- flood risk (1)
- floodplain (1)
- fluvial response (1)
- headward erosion (1)
- higher education (1)
- hydrological conditioning (1)
- immersive 3D geovisualization (1)
- inundation (1)
- knickpoint (1)
- lake-level changes (1)
- landscape evolution (1)
- landslide dam breach (1)
- landslides (1)
- learning success (1)
- localized flooding (1)
- low-relief (1)
- mountain birch (1)
- natural hazards (1)
- object-based image analysis (1)
- outburst flood (1)
- patterns (1)
- river (1)
- river longitudinal profile (1)
- root depth distribution (1)
- scale (1)
- seascape (1)
- sediment yield (1)
- sediment-routing system connectivity (1)
- shoreline (1)
- signal propagation (1)
- steep mountain stream (1)
- student survey (1)
- submarine (1)
- tectonics (1)
- turbidity current (1)
- turbidity currents (1)
- wetlands (1)
Institute
The efficiency of sediment routing from land to the ocean depends on the position of submarine canyon heads with regard to terrestrial sediment sources. We aim to identify the main controls on whether a submarine canyon head remains connected to terrestrial sediment input during Holocene sea-level rise. Globally, we identified 798 canyon heads that are currently located at the 120m-depth contour (the Last Glacial Maximum shoreline) and 183 canyon heads that are connected to the shore (within a distance of 6 km) during the present-day highstand. Regional hotspots of shore-connected canyons are the Mediterranean active margin and the Pacific coast of Central and South America. We used 34 terrestrial and marine predictor variables to predict shore-connected canyon occurrence using Bayesian regression. Our analysis shows that steep and narrow shelves facilitate canyon-head connectivity to the shore. Moreover, shore-connected canyons occur preferentially along active margins characterized by resistant bedrock and high river-water discharge.
Beta diversity is a conceptual link between diversity at local and regional scales. Various additional methodologies of quantifying this and related phenomena have been applied. Among them, measures of pairwise (dis)similarity of sites are particularly popular. Undersampling, i.e. not recording all taxa present at a site, is a common situation in ecological data. Bias in many metrics related to beta diversity must be expected, but only few studies have explicitly investigated the properties of various measures under undersampling conditions. On the basis of an empirical data set, representing near-complete local inventories of the Lepidoptera from an isolated Pacific island, as well as simulated communities with varying properties, we mimicked different levels of undersampling. We used 14 different approaches to quantify beta diversity, among them dataset-wide multiplicative partitioning (i.e. true beta diversity') and pairwise site x site dissimilarities. We compared their values from incomplete samples to true results from the full data. We used these comparisons to quantify undersampling bias and we calculated correlations of the dissimilarity measures of undersampled data with complete data of sites. Almost all tested metrics showed bias and low correlations under moderate to severe undersampling conditions (as well as deteriorating precision, i.e. large chance effects on results). Measures that used only species incidence were very sensitive to undersampling, while abundance-based metrics with high dependency on the distribution of the most common taxa were particularly robust. Simulated data showed sensitivity of results to the abundance distribution, confirming that data sets of high evenness and/or the application of metrics that are strongly affected by rare species are particularly sensitive to undersampling. The class of beta measure to be used should depend on the research question being asked as different metrics can lead to quite different conclusions even without undersampling effects. For each class of metric, there is a trade-off between robustness to undersampling and sensitivity to rare species. In consequence, using incidence-based metrics carries a particular risk of false conclusions when undersampled data are involved. Developing bias corrections for such metrics would be desirable.
Himalayan water resources attract a rapidly growing number of hydroelectric power projects (HPP) to satisfy Asia's soaring energy demands. Yet HPP operating or planned in steep, glacier-fed mountain rivers face hazards of glacial lake outburst floods (GLOFs) that can damage hydropower infrastructure, alter water and sediment yields, and compromise livelihoods downstream. Detailed appraisals of such GLOF hazards are limited to case studies, however, and a more comprehensive, systematic analysis remains elusive. To this end we estimate the regional exposure of 257 Himalayan HPP to GLOFs, using a flood-wave propagation model fed by Monte Carlo-derived outburst volumes of >2300 glacial lakes. We interpret the spread of thus modeled peak discharges as a predictive uncertainty that arises mainly from outburst volumes and dam-breach rates that are difficult to assess before dams fail. With 66% of sampled HPP are on potential GLOF tracks, up to one third of these HPP could experience GLOF discharges well above local design floods, as hydropower development continues to seek higher sites closer to glacial lakes. We compute that this systematic push of HPP into headwaters effectively doubles the uncertainty about GLOF peak discharge in these locations. Peak discharges farther downstream, in contrast, are easier to predict because GLOF waves attenuate rapidly. Considering this systematic pattern of regional GLOF exposure might aid the site selection of future Himalayan HPP. Our method can augment, and help to regularly update, current hazard assessments, given that global warming is likely changing the number and size of Himalayan meltwater lakes.
Himalayan water resources attract a rapidly growing number of hydroelectric power projects (HPP) to satisfy Asia's soaring energy demands. Yet HPP operating or planned in steep, glacier-fed mountain rivers face hazards of glacial lake outburst floods (GLOFs) that can damage hydropower infrastructure, alter water and sediment yields, and compromise livelihoods downstream. Detailed appraisals of such GLOF hazards are limited to case studies, however, and a more comprehensive, systematic analysis remains elusive. To this end we estimate the regional exposure of 257 Himalayan HPP to GLOFs, using a flood-wave propagation model fed by Monte Carlo-derived outburst volumes of >2300 glacial lakes. We interpret the spread of thus modeled peak discharges as a predictive uncertainty that arises mainly from outburst volumes and dam-breach rates that are difficult to assess before dams fail. With 66% of sampled HPP are on potential GLOF tracks, up to one third of these HPP could experience GLOF discharges well above local design floods, as hydropower development continues to seek higher sites closer to glacial lakes. We compute that this systematic push of HPP into headwaters effectively doubles the uncertainty about GLOF peak discharge in these locations. Peak discharges farther downstream, in contrast, are easier to predict because GLOF waves attenuate rapidly. Considering this systematic pattern of regional GLOF exposure might aid the site selection of future Himalayan HPP. Our method can augment, and help to regularly update, current hazard assessments, given that global warming is likely changing the number and size of Himalayan meltwater lakes.
Plain Language Summary The 2015 Gorkha earthquake in Nepal caused severe losses in the hydropower sector. The country temporarily lost similar to 20% of its hydropower capacity, and >30 hydropower projects were damaged. The projects hit hardest were those that were affected by earthquake-triggered landslides. We show that these projects are located along very steep rivers with towering sidewalls that are prone to become unstable during strong seismic ground shaking. A statistical classification based on a topographic metric that expresses river steepness and earthquake ground acceleration is able to approximately predict hydropower damage during future earthquakes, based on successful testing of past cases. Thus, our model enables us to estimate earthquake damages to hydropower projects in other parts of the Himalayas. We find that >10% of the Himalayan drainage network may be unsuitable for hydropower infrastructure given high probabilities of high earthquake damages.
Badlands have long been considered as model landscapes due to their perceived close relationship between form and process. The often intense features of erosion have also attracted many geomorphologists because the associated high rates of erosion appeared to offer the opportunity for studying surface processes and the resulting forms. Recently, the perceived simplicity of badlands has been questioned because the expected relationships between driving forces for erosion and the resulting sediment yield could not be observed. Further, a high variability in erosion and sediment yield has been observed across scales. Finally, denudation based on currently observed erosion rates would have lead to the destruction of most badlands a long time ago. While the perceived simplicity of badlands has sparked a disproportional (compared to the land surface they cover) amount of research, our increasing amount of information has not necessarily increased our understanding of badlands in equal terms. Overall, badlands appear to be more complex than initially assumed. In this paper, we review 40 years of research in the Zin Valley Badlands in Israel to reconcile some of the conflicting results observed there and develop a perspective on the function of badlands as model landscapes. While the data collected in the Zin Valley clearly confirm that spatial and temporal patterns of geomorphic processes and their interaction with topography and surface properties have to be understood, we still conclude that the process of realizing complexity in the "simple" badlands has a model function both for our understanding as well as perspective on all landscape systems.
Climate science is highly interdisciplinary by nature, so understanding interactions between Earth processes inherently warrants the use of analytical software that can operate across the disciplines of Earth science. Toward this end, we present the Climate Data Toolbox for MATLAB, which contains more than 100 functions that span the major climate-related disciplines of Earth science. The toolbox enables streamlined, entirely scriptable workflows that are intuitive to write and easy to share. Included are functions to evaluate uncertainty, perform matrix operations, calculate climate indices, and generate common data displays. Documentation is presented pedagogically, with thorough explanations of how each function works and tutorials showing how the toolbox can be used to replicate results of published studies. As a well-tested, well-documented platform for interdisciplinary collaborations, the Climate Data Toolbox for MATLAB aims to reduce time spent writing low-level code, let researchers focus on physics rather than coding and encourage more efficacious code sharing. Plain Language Summary This article describes a collection of computer code that has recently been released to help scientists analyze many types of Earth science data. The code in this toolbox makes it easy to investigate things like global warming, El Nino, or other major climate-related processes such as how winds affect ocean circulation. Although the toolbox was designed to be used by expert climate scientists, its instruction manual is well written, and beginners may be able to learn a great deal about coding and Earth science, simply by following along with the provided examples. The toolbox is intended to help scientists save time, help them ensure their analysis is accurate, and make it easy for other scientists to repeat the results of previous studies.
TopoToolbox is a MATLAB program for the analysis of digital elevation models (DEMs). With the release of version 2, the software adopts an object-oriented programming (OOP) approach to work with gridded DEMs and derived data such as flow directions and stream networks. The introduction of a novel technique to store flow directions as topologically ordered vectors of indices enables calculation of flow-related attributes such as flow accumulation similar to 20 times faster than conventional algorithms while at the same time reducing memory overhead to 33% of that required by the previous version. Graphical user interfaces (GUIs) enable visual exploration and interaction with DEMs and derivatives and provide access to tools targeted at fluvial and tectonic geomorphologists. With its new release, TopoToolbox has become a more memory-efficient and faster tool for basic and advanced digital terrain analysis that can be used as a framework for building hydrological and geomorphological models in MATLAB.
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.
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.
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.
The 2015 magnitude 7.8 Gorkha earthquake and its aftershocks weakened mountain slopes in Nepal. Co- and postseismic landsliding and the formation of landslide-dammed lakes along steeply dissected valleys were widespread, among them a landslide that dammed the Kali Gandaki River. Overtopping of the landslide dam resulted in a flash flood downstream, though casualties were prevented because of timely evacuation of low-lying areas. We hindcast the flood using the BREACH physically based dam-break model for upstream hydrograph generation, and compared the resulting maximum flow rate with those resulting from various empirical formulas and a simplified hydrograph based on published observations. Subsequent modeling of downstream flood propagation was compromised by a coarse-resolution digital elevation model with several artifacts. Thus, we used a digital-elevation-model preprocessing technique that combined carving and smoothing to derive topographic data. We then applied the 1-dimensional HEC-RAS model for downstream flood routing, and compared it to the 2-dimensional Delft-FLOW model. Simulations were validated using rectified frames of a video recorded by a resident during the flood in the village of Beni, allowing estimation of maximum flow depth and speed. Results show that hydrological smoothing is necessary when using coarse topographic data (such as SRTM or ASTER), as using raw topography underestimates flow depth and speed and overestimates flood wave arrival lag time. Results also show that the 2-dimensional model produces more accurate results than the 1-dimensional model but the 1-dimensional model generates a more conservative result and can be run in a much shorter time. Therefore, a 2-dimensional model is recommended for hazard assessment and planning, whereas a 1-dimensional model would facilitate real-time warning declaration.
Natural catchments are likely to show the existence of knickpoints in their river networks. The origin and genesis of the knickpoints can be manifold, considering that the present morphology is the result of the interactions of different factors such as tectonic movements, quaternary glaciations, river captures, variable lithology, and base-level changes. We analyzed the longitudinal profiles of the river channels in the Stura di Demonte Valley (Maritime Alps) to identify the knickpoints of such an alpine setting and to characterize their origins. The distribution and the geometry of stream profiles were used to identify the possible causes of the changes in stream gradients and to define zones with genetically linked knickpoints. Knickpoints are key geomorphological features for reconstructing the evolution of fluvial dissected basins, when the different perturbing factors affecting the ideally graded fluvial system have been detected. This study shows that even in a regionally small area, perturbations of river profiles are caused by multiple factors. Thus, attributing (automatically)-extracted knickpoints solely to one factor, can potentially lead to incomplete interpretations of catchment evolution.
Modelling the transfer of supraglacial meltwater to the bed of Leverett Glacier, Southwest Greenland
(2015)
Meltwater delivered to the bed of the Greenland Ice Sheet is a driver of variable ice-motion through changes in effective pressure and enhanced basal lubrication. Ice surface velocities have been shown to respond rapidly both to meltwater production at the surface and to drainage of supraglacial lakes, suggesting efficient transfer of meltwater from the supraglacial to subglacial hydrological systems. Although considerable effort is currently being directed towards improved modelling of the controlling surface and basal processes, modelling the temporal and spatial evolution of the transfer of melt to the bed has received less attention. Here we present the results of spatially distributed modelling for prediction of moulins and lake drainages on the Leverett Glacier in Southwest Greenland. The model is run for the 2009 and 2010 ablation seasons, and for future increased melt scenarios. The temporal pattern of modelled lake drainages are qualitatively comparable with those documented from analyses of repeat satellite imagery. The modelled timings and locations of delivery of meltwater to the bed also match well with observed temporal and spatial patterns of ice surface speed-ups. This is particularly true for the lower catchment (< 1000 m a.s.l.) where both the model and observations indicate that the development of moulins is the main mechanism for the transfer of surface meltwater to the bed. At higher elevations (e.g. 1250-1500 m a.s.l.) the development and drainage of supraglacial lakes becomes increasingly important. At these higher elevations, the delay between modelled melt generation and subsequent delivery of melt to the bed matches the observed delay between the peak air temperatures and subsequent velocity speed-ups, while the instantaneous transfer of melt to the bed in a control simulation does not. Although both moulins and lake drainages are predicted to increase in number for future warmer climate scenarios, the lake drainages play an increasingly important role in both expanding the area over which melt accesses the bed and in enabling a greater proportion of surface melt to reach the bed.
Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques are often hampered on floodplains by the presence of herbaceous vegetation. To address this problem, this study presents the application of full waveform airborne laser scanning (ALS) data for detection of floodwater extent. In general, water surfaces are characterised by low values of backscattered energy due to water absorption of the infrared laser shots, but the exact strength of the recorded laser pulse depends on the area covered by the targets located within a laser pulse footprint area. To account for this we analysed the physical quantity of radio metrically calibrated ALS data, the backscattering coefficient, in relation to water and vegetation coverage within a single laser footprint. The results showed that the backscatter was negatively correlated to water coverage, and that of the three distinguished classes of water coverage (low, medium, and high) only the class with the largest extent of water cover (>70%) had relatively distinct characteristics that can be used for classification of water surfaces. Following the laser footprint analysis, three classifiers, namely AdaBoost with Decision Tree, Naive Bayes and Random Forest, were utilised to classify laser points into flooded and non-flooded classes and to derive the map of flooding extent. The performance of the classifiers is highly dependent on the set of laser points features used. Best performance was achieved by combining radiometric and geometric laser point features. The accuracy of flooding maps based solely on radiometric features resulted in overall accuracies of up to 70% and was limited due to the overlap of the backscattering coefficient values between water and other land cover classes. Our point-based classification methods assure a high mapping accuracy (similar to 89%) and demonstrate the potential of using full-waveform ALS data to detect water surfaces on floodplain areas with limited water surface exposition through the vegetation canopy. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
Mass wasting is an important process for denuding hillslopes and lowering ridge crests in active mountain belts such as the Himalaya-Karakoram ranges (HKR). Such a high-relief landscape is likely to be at its mechanical threshold, maintained by competing rapid rock uplift, river incision, and pervasive slope failure. We introduce excess topography, Z(E), for quantifying potentially unstable rock-mass volumes inclined at angles greater than a specified threshold angle. We find that Z(E) peaks along major fluvial and glacial inner gorges, which is also where the majority of 492 large (>0.1 km(2)) rock-slope failures occur in the Himalaya's largest cluster of documented Pleistocene to Holocene bedrock landslides. Our data reveal that bedrock landslides in the HKR chiefly detached from near or below the median elevation, whereas glaciers and rock glaciers occupy higher-elevation bands almost exclusively. Less than 10% of the area of the HKR is upslope of glaciers, such that possible censoring of evidence of large bedrock landslides above the permanent snow line barely affects this finding. Bedrock landslides appear to preferentially undermine topographic relief in response to fluvial and glacial incision along inner gorges, unless more frequent and smaller undetected failures, or rigorous (peri-)glacial erosion, compensate for this role at higher elevation. Either way, the distinct patterns of excess topography and large bedrock landsliding in the HKR juxtapose two stacked domains of landslide and (peri-)glacial erosion that may respond to different time scales of perturbation. Our findings call for more detailed analysis of vertical erosional domains and their geomorphic coupling in active mountain belts.
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.
Understanding how Earth-surface processes respond to past climatic perturbations is crucial for making informed predictions about future impacts of climate change on sediment "uxes. Sedimentary records provide the archives for inferring these processes, but their interpretation is compromised by our incomplete understanding of how sediment-routing systems respond to millennial-scale climate cycles. We analyzed seven sediment cores recovered from marine turbidite depositional sites along the Chile continental margin. The sites span a pronounced arid-to-humid gradient with variable relief and related sediment connectivity of terrestrial and marine environments. These sites allowed us to study event related depositional processes in different climatic and geomorphic settings from the Last Glacial Maximum to the present day. The three sites reveal a steep decline of turbidite deposition during deglaciation. High rates of sea-level rise postdate the decline in turbidite deposition. Comparison with paleoclimate proxies documents that the spatio-temporal sedimentary pattern rather mirrors the deglacial humidity decrease and concomitant warming with no resolvable lag times. Our results let us infer that declining deglacial humidity decreased "uvial sediment supply. This signal propagated rapidly through the highly connected systems into the marine sink in north-central Chile. In contrast, in south-central Chile, connectivity between the Andean erosional zone and the "uvial transfer zone probably decreased abruptly by sediment trapping in piedmont lakes related to deglaciation, resulting in a sudden decrease of sediment supply to the ocean. Additionally, reduced moisture supply may have contributed to the rapid decline of turbidite deposition. These different causes result in similar depositional patterns in the marine sinks. We conclude that turbiditic strata may constitute reliable recorders of climate change across a wide range of climatic zones and geomorphic conditions. However, the underlying causes for similar signal manifestations in the sinks may differ, ranging from maintained high system connectivity to abrupt connectivity loss. (C) 2017 Elsevier B.V. All rights reserved.
Graph theory has long been used in quantitative geography and landscape ecology and has been applied in Earth and atmospheric sciences for several decades. Recently, however, there have been increased, and more sophisticated, applications of graph theory concepts and methods in geosciences, principally in three areas: spatially explicit modeling, small-world networks, and structural models of Earth surface systems. This paper reviews the contrasting goals and methods inherent in these approaches, but focuses on the common elements, to develop a synthetic view of graph theory in the geosciences. Techniques applied in geosciences are mainly of three types: connectivity measures of entire networks; metrics of various aspects of the importance or influence of particular nodes, links, or regions of the network; and indicators of system dynamics based on graph adjacency matrices. Geoscience applications of graph theory can be grouped in five general categories: (1) Quantification of complex network properties such as connectivity, centrality, and clustering; (2) Tests for evidence of particular types of structures that have implications for system behavior, such as small-world or scale-free networks; (3) Testing dynamical system properties, e.g., complexity, coherence, stability, synchronization, and vulnerability; (4) Identification of dynamics from historical records or time series; and (5) spatial analysis. Recent and future expansion of graph theory in geosciences is related to general growth of network-based approaches. However, several factors make graph theory especially well suited to the geosciences: Inherent complexity, exploration of very large data sets, focus on spatial fluxes and interactions, and increasing attention to state transitions are all amenable to analysis using graph theory approaches. (C) 2015 Elsevier B.V. All rights reserved.