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In active mountain belts with steep terrain, bedrock landsliding is a major erosional agent. In the Himalayas, landsliding is driven by annual hydro-meteorological forcing due to the summer monsoon and by rarer, exceptional events, such as earthquakes. Independent methods yield erosion rate estimates that appear to increase with sampling time, suggesting that rare, high-magnitude erosion events dominate the erosional budget. Nevertheless, until now, neither the contribution of monsoon and earthquakes to landslide erosion nor the proportion of erosion due to rare, giant landslides have been quantified in the Himalayas. We address these challenges by combining and analysing earthquake- and monsoon-induced landslide inventories across different timescales. With time series of 5 m satellite images over four main valleys in central Nepal, we comprehensively mapped landslides caused by the monsoon from 2010 to 2018. We found no clear correlation between monsoon properties and landsliding and a similar mean landsliding rate for all valleys, except in 2015, where the valleys affected by the earthquake featured similar to 5-8 times more landsliding than the pre-earthquake mean rate. The longterm size-frequency distribution of monsoon-induced landsliding (MIL) was derived from these inventories and from an inventory of landslides larger than similar to 0.1 km(2) that occurred between 1972 and 2014. Using a published landslide inventory for the Gorkha 2015 earthquake, we derive the size-frequency distribution for earthquakeinduced landsliding (EQIL). These two distributions are dominated by infrequent, large and giant landslides but under-predict an estimated Holocene frequency of giant landslides (> 1 km(3)) which we derived from a literature compilation. This discrepancy can be resolved when modelling the effect of a full distribution of earthquakes of variable magnitude and when considering that a shallower earthquake may cause larger landslides. In this case, EQIL and MIL contribute about equally to a total long-term erosion of similar to 2 +/- 0.75 mm yr(-1) in agreement with most thermo-chronological data. Independently of the specific total and relative erosion rates, the heavy-tailed size-frequency distribution from MIL and EQIL and the very large maximal landslide size in the Himalayas indicate that mean landslide erosion rates increase with sampling time, as has been observed for independent erosion estimates. Further, we find that the sampling timescale required to adequately capture the frequency of the largest landslides, which is necessary for deriving long-term mean erosion rates, is often much longer than the averaging time of cosmogenic Be-10 methods. This observation presents a strong caveat when interpreting spatial or temporal variability in erosion rates from this method. Thus, in areas where a very large, rare landslide contributes heavily to long-term erosion (as the Himalayas), we recommend Be-10 sample in catchments with source areas > 10 000 km(2) to reduce the method mean bias to below similar to 20 % of the long-term erosion.
Shear-waves are the most energetic body-waves radiated from an earthquake, and are responsible for the destruction of engineered structures. In both short-term emergency response and long-term risk forecasting of disaster-resilient built environment, it is critical to predict spatially accurate distribution of shear-wave amplitudes. Although decades’ old theory proposes a deterministic, highly anisotropic, four-lobed shear-wave radiation pattern, from lack of convincing evidence, most empirical ground-shaking prediction models settled for an oversimplified stochastic radiation pattern that is isotropic on average. Today, using the large datasets of uniformly processed seismograms from several strike, normal, reverse, and oblique-slip earthquakes across the globe, compiled specifically for engineering applications, we could reveal, quantify, and calibrate the frequency-, distance-, and style-of-faulting dependent transition of shear-wave radiation between a stochastic-isotropic and a deterministic-anisotropic phenomenon. Consequent recalibration of empirical ground-shaking models dramatically improved their predictions: with isodistant anisotropic variations of ±40%, and 8% reduction in uncertainty. The outcomes presented here can potentially trigger a reappraisal of several practical issues in engineering seismology, particularly in seismic ground-shaking studies and seismic hazard and risk assessment.
A comprehensive description of electromagnetic processes related to equatorial plasma depletions (EPDs) is essential for understanding their evolution and day-to-day variability. Recently, field-aligned currents (FACs) flowing at both western and eastern edges of EPDs were observed to be interhemispheric rather than anti-parallel about the dip equator, as suggested by previous theoretical studies. In this paper, we investigate the spatial and temporal variability of the FACs orientation using simultaneous measurements of electron density and magnetic field gathered by ESA’s Swarm constellation mission. By using empirical models, we assess the role of the Pedersen conductance in the preference of the FACs to close either in the northern or southern magnetic hemisphere. Here we show that the closure of the FACs agrees with an electrostatic regime determined by a hemispherical asymmetry of the Pedersen conductance. That is, the EPD-related FACs close at lower altitudes in the hemisphere with the highest conductivity. The evidence of this conclusion stands on the general agreement between the longitudinal and seasonal variability of both the conductivity and the FACs orientation.
Changes in the steepness of river profiles or abrupt vertical steps (i.e. waterfalls) are thought to be indicative of changes in erosion rates, lithology or other factors that affect landscape evolution. These changes are referred to as knickpoints or knickzones and are pervasive in bedrock river systems. Such features are thought to reveal information about landscape evolution and patterns of erosion, and therefore their locations are often reported in the geomorphic literature. It is imperative that studies reporting knickpoints and knickzones use a reproducible method of quantifying their locations, as their number and spatial distribution play an important role in interpreting tectonically active landscapes. In this contribution we introduce a reproducible knickpoint and knickzone extraction algorithm that uses river profiles transformed by integrating drainage area along channel length (the so-called integral or chi method). The profile is then statistically segmented and the differing slopes and step changes in the elevations of these segments are used to identify knickpoints, knickzones and their relative magnitudes. The output locations of identified knickpoints and knickzones compare favourably with human mapping: we test the method on Santa Cruz Island, CA, using previously reported knickzones and also test the method against a new dataset from the Quadrilatero Ferrifero in Brazil. The algorithm allows for the extraction of varying knickpoint morphologies, including stepped, positive slope-break (concave upward) and negative slope-break knickpoints. We identify parameters that most affect the resulting knickpoint and knickzone locations and provide guidance for both usage and outputs of the method to produce reproducible knickpoint datasets.
Climate and weather conditions in the mid-latitudes are strongly driven by the large-scale atmosphere circulation. Observational data indicate that important components of the large-scale circulation have changed in recent decades, including the strength and the width of the Hadley cell, jets, storm tracks and planetary waves. Here, we use a new statistical-dynamical atmosphere model (SDAM) to test the individual sensitivities of the large-scale atmospheric circulation to changes in the zonal temperature gradient, meridional temperature gradient and global-mean temperature. We analyze the Northern Hemisphere Hadley circulation, jet streams, storm tracks and planetary waves by systematically altering the zonal temperature asymmetry, the meridional temperature gradient and the global-mean temperature. Our results show that the strength of the Hadley cell, storm tracks and jet streams depend, in terms of relative changes, almost linearly on both the global-mean temperature and the meridional temperature gradient, whereas the zonal temperature asymmetry has little or no influence. The magnitude of planetary waves is affected by all three temperature components, as expected from theoretical dynamical considerations. The width of the Hadley cell behaves nonlinearly with respect to all three temperature components in the SDAM. Moreover, some of these observed large-scale atmospheric changes are expected from dynamical equations and are therefore an important part of model validation.
Geomorphic strain markers accumulating the effects of many earthquake cycles help to constrain the mechanical behaviour of continental rift systems as well as the related seismic hazards. In the Corinth Rift (Greece), the unique record of onshore and offshore markers of Pleistocene similar to 100-ka climate cycles provides an outstanding possibility to constrain rift mechanics over a range of timescales. Here we use high-resolution topography to analyse the 3D geometry of a sequence of Pleistocene emerged marine terraces associated with flexural rift-flank uplift. We integrate this onshore dataset with offshore seismic data to provide a synoptic view of the flexural deformation across the rift. This allows us to derive an average slip rate of 4.5-9.0 mm.yr(-1) on the master fault over the past similar to 610 ka and an uplift/ subsidence ratio of 1:1.1-2.4. We reproduce the observed flexure patterns, using 3 and 5-layered lithospheric scale finite element models. Modelling results imply that the observed elastic flexure is produced by coseismic slip along 40-60 degrees planar normal faults in the elastic upper crust, followed by postseismic viscous relaxation occurring within the basal lower crust or upper mantle. We suggest that such a mechanism may typify rapid localised extension of continental lithosphere.
Proxy records from climate archives provide evidence about past climate changes, but the recorded signal is affected by non-climate-related effects as well as time uncertainty. As proxy-based climate reconstructions are frequently used to test climate models and to quantitatively infer past climate, we need to improve our understanding of the proxy record signal content as well as the uncertainties involved. In this study, we empirically estimate signal-to-noise ratios (SNRs) of temperature proxy records used in global compilations of the middle to late Holocene (last 6000 years). This is achieved through a comparison of the correlation of proxy time series from nearby sites of three compilations and model time series extracted at the proxy sites from two transient climate model simulations: a Holocene simulation of the ECHAM5/MPI-OM model and the Holocene part of the TraCE-21ka simulation. In all comparisons, we found the mean correlations of the proxy time series on centennial to millennial timescales to be low (R < 0.2), even for nearby sites, which resulted in low SNR estimates. The estimated SNRs depend on the assumed time uncertainty of the proxy records, the timescale analysed, and the model simulation used. Using the spatial correlation structure of the ECHAM5/MPI-OM simulation, the estimated SNRs on centennial timescales ranged from 0.05 - assuming no time uncertainty - to 0.5 for a time uncertainty of 400 years. On millennial timescales, the estimated SNRs were generally higher. Use of the TraCE-21ka correlation structure generally resulted in lower SNR estimates than for ECHAM5/MPI-OM. As the number of available high-resolution proxy records continues to grow, a more detailed analysis of the signal content of specific proxy types should become feasible in the near future. The estimated low signal content of Holocene temperature compilations should caution against over-interpretation of these multi-proxy and multisite syntheses until further studies are able to facilitate a better characterisation of the signal content in paleoclimate records.
Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively.
Rapid local adaptation frequently occurs during the spread of invading species. It remains unclear, however, how consistent, and therefore potentially predictable, such patterns of local adaptation are. One approach to this question is to measure patterns of local differentiation in functional traits and plasticity levels in invasive species in multiple regions. Finding consistent patterns of local differentiation in replicate regions suggests that these patterns are adaptive. Further, this outcome indicates that the invading species likely responds predictably to selection along environmental gradients, even though standing genetic variation is likely to have been reduced during introduction. We studied local differentiation in the invasive annual plant Erodium cicutarium in two invaded regions, California and Chile. We collected seeds from across strong gradients in precipitation and temperature in Mediterranean-climate parts of the two regions (10 populations per region). We grew seeds from maternal families from these populations through two generations and exposed the second generation to contrasting levels of water and nutrient availability. We measured growth, flowering time and leaf functional traits across these treatments to obtain trait means and plasticity measures. We found strong differentiation among populations in all traits. Plants from drier environments flowered earlier, were less plastic in flowering time and reached greater size in all treatments. Correlations among traits within regions suggested a coordinated evolutionary response along environmental gradients associated with growing season length. There was little divergence in traits and trait intercorrelations between regions, but strongly parallel divergence in traits within regions. Similar, statistically consistent patterns of local trait differentiation across two regions suggest that local adaptation to environmental gradients has aided the spread of this invasive species, and that the formation of ecotypes in newly invaded environments has been relatively consistent and predictable.
The propagation of a seismic rupture on a fault introduces spatial variations in the seismic wave field surrounding the fault. This directivity effect results in larger shaking amplitudes in the rupture propagation direction. Its seismic radiation pattern also causes amplitude variations between the strike-normal and strike-parallel components of horizontal ground motion. We investigated the landslide response to these effects during the 2016 Kumamoto earthquake (M-w 7.1) in central Kyushu (Japan). Although the distribution of some 1500 earthquake-triggered landslides as a function of rupture distance is consistent with the observed Arias intensity, the landslides were more concentrated to the northeast of the southwest-northeast striking rupture. We examined several landslide susceptibility factors: hillslope inclination, the median amplification factor (MAF) of ground shaking, lithology, land cover, and topographic wetness. None of these factors sufficiently explains the landslide distribution or orientation (aspect), although the landslide head scarps have an elevated hillslope inclination and MAF. We propose a new physics-based ground-motion model (GMM) that accounts for the seismic rupture effects, and we demonstrate that the low-frequency seismic radiation pattern is consistent with the overall landslide distribution. Its spatial pattern is influenced by the rupture directivity effect, whereas landslide aspect is influenced by amplitude variations between the fault-normal and fault-parallel motion at frequencies < 2 Hz. This azimuth dependence implies that comparable landslide concentrations can occur at different distances from the rupture. This quantitative link between the prevalent landslide aspect and the low-frequency seismic radiation pattern can improve coseismic landslide hazard assessment.
We show that near-real-time seismic monitoring of fluid injection allowed control of induced earthquakes during the stimulation of a 6.1-km-deep geothermal well near Helsinki, Finland. A total of 18,160 m(3) of fresh water was pumped into crystalline rocks over 49 days in June to July 2018. Seismic monitoring was performed with a 24-station borehole seismometer network. Using near-real-time information on induced-earthquake rates, locations, magnitudes, and evolution of seismic and hydraulic energy, pumping was either stopped or varied-in the latter case, between well-head pressures of 60 and 90 MPa and flow rates of 400 and 800 liters/min. This procedure avoided the nucleation of a project-stopping magnitude M-W 2.0 induced earthquake, a limit set by local authorities. Our results suggest a possible physics-based approach to controlling stimulation-induced seismicity in geothermal projects.
The novel space-borne Global Navigation Satellite System Reflectometry (GNSS-R) technique has recently shown promise in monitoring the ocean state and surface wind speed with high spatial coverage and unprecedented sampling rate. The L-band signals of GNSS are structurally able to provide a higher quality of observations from areas covered by dense clouds and under intense precipitation, compared to those signals at higher frequencies from conventional ocean scatterometers. As a result, studying the inner core of cyclones and improvement of severe weather forecasting and cyclone tracking have turned into the main objectives of GNSS-R satellite missions such as Cyclone Global Navigation Satellite System (CYGNSS). Nevertheless, the rain attenuation impact on GNSS-R wind speed products is not yet well documented. Evaluating the rain attenuation effects on this technique is significant since a small change in the GNSS-R can potentially cause a considerable bias in the resultant wind products at intense wind speeds. Based on both empirical evidence and theory, wind speed is inversely proportional to derived bistatic radar cross section with a natural logarithmic relation, which introduces high condition numbers (similar to ill-posed conditions) at the inversions to high wind speeds. This paper presents an evaluation of the rain signal attenuation impact on the bistatic radar cross section and the derived wind speed. This study is conducted simulating GNSS-R delay-Doppler maps at different rain rates and reflection geometries, considering that an empirical data analysis at extreme wind intensities and rain rates is impossible due to the insufficient number of observations from these severe conditions. Finally, the study demonstrates that at a wind speed of 30 m/s and incidence angle of 30 degrees, rain at rates of 10, 15, and 20 mm/h might cause overestimation as large as approximate to 0.65 m/s (2%), 1.00 m/s (3%), and 1.3 m/s (4%), respectively, which are still smaller than the CYGNSS required uncertainty threshold. The simulations are conducted in a pessimistic condition (severe continuous rainfall below the freezing height and over the entire glistening zone) and the bias is expected to be smaller in size in real environments.
During eruptive activity of andesitic stratovolcanoes, the extrusion of lava domes, their collapse and intermittent explosions are common volcanic hazards. Many lava domes grow in a preferred direction, in turn affecting the direction of lava flows and pyroclastic density currents. Access to active lava domes is difficult and hazardous, so detailed data characterizing lava dome growth are typically limited, keeping the processes controlling the directionality of extrusions unclear. Here we combine TerraSAR-X satellite radar observations with high-resolution airborne photogrammetry to assess morphological changes, and perform finite element modeling to investigate the impact of loading stress on shallow magma ascent directions associated with lava dome extrusion and crater formation at Volcan de Colima, Mexico. The TerraSAR-X data, acquired in similar to 1-m resolution spotlight mode, enable us to derive a chronology of the eruptive processes from intensity-based time-lapse observations of the general crater and dome evolution. The satellite images are complemented by close-range airborne photos, processed by the Structure-from-Motion workflow. This allows the derivation of high-resolution digital elevation models, providing insight into detailed loading and unloading features. During the observation period from Jan-2013 to Feb-2016, we identify a dominantly W-directed dome growth and lava flow production until Jan-2015. In Feb-2015, following the removal of the active summit dome, the surface crater widened and elongated along a NE-SW axis. Later in May-2015, a new dome grew toward the SW of the crater while a separate vent developed in the NE of the crater, reflecting a change in the direction of magma ascent and possible conduit bifurcation. Finite element models show a significant stress change in agreement with the observed magma ascent direction changes in response to the changing surface loads, both for loading (dome growth) and unloading (crater forming excavation) cases. These results allow insight into shallow dome growth dynamics and the migration of magma ascent in response to changing volcano summit morphology. They further highlight the importance of detailed volcano summit morphology surveillance, as changes in direction or location of dome extrusion may have major implications regarding the directions of potential volcanic hazards, such as pyroclastic density currents generated by dome collapse.
Sediment Transit Time and Floodplain Storage Dynamics in Alluvial Rivers Revealed by Meteoric 10Be
(2020)
Quantifying the time scales of sediment transport and storage through river systems is fundamental for understanding weathering processes, biogeochemical cycling, and improving watershed management, but measuring sediment transit time is challenging. Here we provide the first systematic test of measuring cosmogenic meteoric Beryllium-10 (10Bem) in the sediment load of a large alluvial river to quantify sediment transit times. We take advantage of a natural experiment in the Rio Bermejo, a lowland alluvial river traversing the east Andean foreland basin in northern Argentina. This river has no tributaries along its trunk channel for nearly 1,300 km downstream from the mountain front. We sampled suspended sediment depth profiles along the channel and measured the concentrations of 10Bem in the chemically extracted grain coatings. We calculated depth-integrated 10Bem concentrations using sediment flux data and found that 10Bem concentrations increase 230% from upstream to downstream, indicating a mean total sediment transit time of 8.4 ± 2.2 kyr. Bulk sediment budget-based estimates of channel belt and fan storage times suggest that the 10Bem tracer records mixing of old and young sediment reservoirs. On a reach scale, 10Bem transit times are shorter where the channel is braided and superelevated above the floodplain, and longer where the channel is incised and meandering, suggesting that transit time is controlled by channel morphodynamics. This is the first systematic application of 10Bem as a sediment transit time tracer and highlights the method's potential for inferring sediment routing and storage dynamics in large river systems.
Sustainable development goals (SDGs) have set the 2030 agenda to transform our world by tackling multiple challenges humankind is facing to ensure well-being, economic prosperity, and environmental protection. In contrast to conventional development agendas focusing on a restricted set of dimensions, the SDGs provide a holistic and multidimensional view on development. Hence, interactions among the SDGs may cause diverging results. To analyze the SDG interactions we systematize the identification of synergies and trade-offs using official SDG indicator data for 227 countries. A significant positive correlation between a pair of SDG indicators is classified as a synergy while a significant negative correlation is classified as a trade-off. We rank synergies and trade-offs between SDGs pairs on global and country scales in order to identify the most frequent SDG interactions. For a given SDG, positive correlations between indicator pairs were found to outweigh the negative ones in most countries. Among SDGs the positive and negative correlations between indicator pairs allowed for the identification of particular global patterns. SDG 1 (No poverty) has synergetic relationship with most of the other goals, whereas SDG 12 (Responsible consumption and production) is the goal most commonly associated with trade-offs. The attainment of the SDG agenda will greatly depend on whether the identified synergies among the goals can be leveraged. In addition, the highlighted trade-offs, which constitute obstacles in achieving the SDGs, need to be negotiated and made structurally nonobstructive by deeper changes in the current strategies.
Disentangling shallow‐water bulk carbonate carbon isotope archives into primary and diagenetic components is a notoriously difficult task and even diagenetically screened records often provide chemostratigraphic patterns that significantly differ from global signals. This is mainly caused by the polygenetic nature of shallow‐water carbonate substrates, local carbon cycle processes causing considerable neritic–pelagic isotope gradients and the presence of hiatal surfaces resulting in extremely low carbonate preservation rates. Provided here is an in‐depth petrographic and geochemical evaluation of different carbonate phases of a mid‐Cretaceous (Barremian–Aptian) shallow‐water limestone succession (Jabal Madar section) deposited on the tropical Arabian carbonate platform in Oman. The superposition of stable isotope signatures of identified carbonate phases causes a complex and often noisy bulk carbon isotope pattern. Blocky sparite cements filling intergranular pores and bioclastic voids evidence intermediate to (arguably) deep burial diagenetic conditions during their formation, owing to different timing or differential faulting promoting the circulation of fluids from variable sources. In contrast, sparite cements filling sub‐vertical veins reveal a rock‐buffered diagenetic fluid composition with an intriguing moderate enrichment in 13C, probably due to fractionation during pressure release in the context of the Miocene exhumation of the carbonate platform under study. The presence of abundant, replacive dedolomite in mud‐supported limestone samples forced negative carbon and oxygen isotope changes that are either associated with the thermal breakdown of organic matter in the deep burial realm or the expulsion of buried meteoric water in the intermediate burial realm. Notwithstanding the documented stratigraphically variable and often facies‐related impact of different diagenetic fluids on the bulk‐rock stable isotope signature, the identification of diagenetic end‐members defined δ13C and δ18O threshold values that allowed the most reliable ‘primary’ bulk carbon isotope signatures to be extracted. Most importantly, this approach exemplifies how to place regional shallow‐water stable isotope patterns with evidence for a complex multi‐stage diagenetic history into a supraregional or even global context.
Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
We present a new algorithm for solving the common problem of flow trapped in closed depressions within digital elevation models, as encountered in many applications relying on flow routing. Unlike other approaches (e.g., the Priority-Flood depression filling algorithm), this solution is based on the explicit computation of the flow paths both within and across the depressions through the construction of a graph connecting together all adjacent drainage basins. Although this represents many operations, a linear time complexity can be reached for the whole computation, making it very efficient. Compared to the most optimized solutions proposed so far, we show that this algorithm of flow path enforcement yields the best performance when used in landscape evolution models. In addition to its efficiency, our proposed method also has the advantage of letting the user choose among different strategies of flow path enforcement within the depressions (i.e., filling vs. carving). Furthermore, the computed graph of basins is a generic structure that has the potential to be reused for solving other problems as well, such as the simulation of erosion. This sequential algorithm may be helpful for those who need to, e.g., process digital elevation models of moderate size on single computers or run batches of simulations as part of an inference study.
James Ross Island (JRI) offers the exceptional opportunity to study microbial-driven pedogenesis without the influence of vascular plants or faunal activities (e.g., penguin rookeries). In this study, two soil profiles from JRI (one at Santa Martha Cove - SMC, and another at Brandy Bay BB) were investigated, in order to gain information about the initial state of soil formation and its interplay with prokaryotic activity, by combining pedological, geochemical and microbiological methods. The soil profiles are similar with respect to topographic position and parent material but are spatially separated by an orographic barrier and therefore represent windward and leeward locations towards the mainly southwesterly winds. These different positions result in differences in electric conductivity of the soils caused by additional input of bases by sea spray at the windward site and opposing trends in the depth functions of soil pH and electric conductivity. Both soils are classified as Cryosols, dominated by bacterial taxa such as Actinobacteria, Proteobacteria, Acidobacteria, Gemmatimonadetes and Chloroflexi. A shift in the dominant taxa was observed below 20 cm in both soils as well as an increased abundance of multiple operational taxonomic units (OTUs) related to potential chemolithoautotrophic Acidiferrobacteraceae. This shift is coupled by a change in microstructure. While single/pellicular grain microstructure (SMC) and platy microstructure (BB) are dominant above 20 cm, lenticular microstructure is dominant below 20 cm in both soils. The change in microstructure is caused by frequent freeze-thaw cycles and a relative high water content, and it goes along with a development of the pore spacing and is accompanied by a change in nutrient content. Multivariate statistics revealed the influence of soil parameters such as chloride, sulfate, calcium and organic carbon contents, grain size distribution and pedogenic oxide ratios on the overall microbial community structure and explained 49.9% of its variation. The correlation of the pedogenic oxide ratios with the compositional distribution of microorganisms as well as the relative abundance certain microorganisms such as potentially chemolithotrophic Acidiferrobacteraceae-related OTUs could hint at an interplay between soil-forming processes and microorganisms.
With the advent of the two Sentinel-1 (S1) satellites, Synthetic Aperture Radar (SAR) data with high temporal and spatial resolution are freely available. This provides a promising framework to facilitate detailed investigations of surface instabilities and movements on large scales with high temporal resolution, but also poses substantial processing challenges because of storage and computation requirements. Methods are needed to efficiently detect short term changes in dynamic environments. Approaches considering pair-wise processing of a series of consecutive scenes to retain maximum temporal resolution in conjunction with time series analyses are required. Here we present OSARIS, the “Open Source SAR Investigation System,” as a framework to process large stacks of S1 data on high-performance computing clusters. Based on Generic Mapping Tools SAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexible processing schemes, convenient configuration, and generation of geocoded stacks of analysis-ready base data, including amplitude, phase, coherence, and unwrapped interferograms. Time series analyses can be conducted by applying automated modules to the data stacks. The capabilities of OSARIS are demonstrated in a case study from the northwestern Tien Shan, Central Asia. After merging of slices, a total of 80 scene pairs were processed from 174 total input scenes. The coherence time series exhibits pronounced seasonal variability, with relatively high coherence values prevailing during the summer months in the nival zone. As an example of a time series analysis module, we present OSARIS' “Unstable Coherence Metric” which identifies pixels affected by significant drops from high to low coherence values. Measurements of motion provided by LOSD measurements require careful evaluation because interferometric phase unwrapping is prone to errors. Here, OSARIS provides a series of modules to detect and mask unwrapping errors, correct for atmospheric disturbances, and remove large-scale trends. Wall clock processing time for the case study (area ~9,000 km2) was ~12 h 4 min on a machine with 400 cores and 2 TB RAM. In total, ~12 d 10 h 44 min (~96%) were saved through parallelization. A comparison of selected OSARIS datasets to results from two state-of-the-art SAR processing suites, ISCE and SNAP, shows that OSARIS provides products of competitive quality despite its high level of automatization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years.
The question of whether urbanization contributes to increasing carbon dioxide emissions has been mainly investigated via scaling relationships with population or population density. However, these approaches overlook the correlations between population and area, and ignore possible interactions between these quantities. Here, we propose a generalized framework that simultaneously considers the effects of population and area along with possible interactions between these urban metrics. Our results significantly improve the description of emissions and reveal the coupled role between population and density on emissions. These models show that variations in emissions associated with proportionate changes in population or density may not only depend on the magnitude of these changes but also on the initial values of these quantities. For US areas, the larger the city, the higher is the impact of changing its population or density on its emissions; but population changes always have a greater effect on emissions than population density.
With the growing size and use of night light time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night light data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g., airports and prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15-20% of the mean. Greenhouses and flares, however, are not stable sources. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.
Proglacial environments are ideal for studying the development of soils through the changes of rocks exposed by glacier retreat to weathering and microbial processes. Carbon (C) and nitrogen (N) contents as well as soil pH and soil elemental compositions are thought to be dominant factors structuring the bacterial, archaeal and fungal communities in the early stages of soil ecosystem formation. However, the functional linkages between C and N contents, soil composition and microbial community structures remain poorly understood. Here, we describe a multivariate analysis of geochemical properties and associated microbial community structures between a moraine and a glaciofluvial outwash in the proglacial area of a High Arctic glacier (Longyearbreen, Svalbard). Our results reveal distinct differences in developmental stages and heterogeneity between the moraine and the glaciofluvial outwash. We observed significant relationships between C and N contents, delta C-13(org) and delta N-15 isotopic ratios, weathering and microbial abundance and community structures. We suggest that the observed differences in microbial and geochemical parameters between the moraine and the glaciofluvial outwash are primarily a result of geomorphological variations of the proglacial terrain.
The 2-D distinct element method (DEM) code (PFC2D_V5) is used here to simulate the evolution of subsidence-related karst landforms, such as single and clustered sinkholes, and associated larger-scale depressions. Subsurface material in the DEM model is removed progressively to produce an array of cavities; this simulates a network of subsurface groundwater conduits growing by chemical/mechanical erosion. The growth of the cavity array is coupled mechanically to the gravitationally loaded surroundings, such that cavities can grow also in part by material failure at their margins, which in the limit can produce individual collapse sinkholes. Two end-member growth scenarios of the cavity array and their impact on surface subsidence were examined in the models: (1) cavity growth at the same depth level and growth rate; (2) cavity growth at progressively deepening levels with varying growth rates. These growth scenarios are characterised by differing stress patterns across the cavity array and its overburden, which are in turn an important factor for the formation of sinkholes and uvalalike depressions. For growth scenario (1), a stable compression arch is established around the entire cavity array, hindering sinkhole collapse into individual cavities and favouring block-wise, relatively even subsidence across the whole cavity array. In contrast, for growth scenario (2), the stress system is more heterogeneous, such that local stress concentrations exist around individual cavities, leading to stress interactions and local wall/overburden fractures. Consequently, sinkhole collapses occur in individual cavities, which results in uneven, differential subsidence within a larger-scale depression. Depending on material properties of the cavity-hosting material and the overburden, the larger-scale depression forms either by sinkhole coalescence or by widespread subsidence linked geometrically to the entire cavity array. The results from models with growth scenario (2) are in close agreement with surface morphological and subsurface geophysical observations from an evaporite karst area on the eastern shore of the Dead Sea.
OpenForecast
(2019)
The development and deployment of new operational runoff forecasting systems are a strong focus of the scientific community due to the crucial importance of reliable and timely runoff predictions for early warnings of floods and flashfloods for local businesses and communities. OpenForecast, the first operational runoff forecasting system in Russia, open for public use, is presented in this study. We developed OpenForecast based only on open-source software and data-GR4J hydrological model, ERA-Interim meteorological reanalysis, and ICON deterministic short-range meteorological forecasts. Daily forecasts were generated for two basins in the European part of Russia. Simulation results showed a limited efficiency in reproducing the spring flood of 2019. Although the simulations managed to capture the timing of flood peaks, they failed in estimating flood volume. However, further implementation of the parsimonious data assimilation technique significantly alleviates simulation errors. The revealed limitations of the proposed operational runoff forecasting system provided a foundation to outline its further development and improvement.
The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of climate and land use change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. To facilitate in-depth evaluations of the effects of climate and land use changes and to separate the effects of natural and anthropogenic drivers in the region, six sites were chosen for comprehensive monitoring. In addition, at selected sites, geoarchives were used to substantially extend the instrumental records back in time. It is this combination of diverse disciplines working across different time scales that makes the observatory TERENO-NE a unique observation platform. We provide information about the general characteristics of the observatory and its six monitoring sites and present examples of interdisciplinary research activities at some of these sites. We also illustrate how monitoring improves process understanding, how remote sensing techniques are fine-tuned by the most comprehensive ground-truthing site DEMMIN, how soil erosion dynamics have evolved, how greenhouse gas monitoring of rewetted peatlands can reveal unexpected mechanisms, and how proxy data provides a long-term perspective of current ongoing changes.
In response to collision and convergence between India and Asia during the Cenozoic, convergence took place between the Pamir and South Tian Shan. Here we present new detrital zircon U-Pb ages coupled with conglomerate clast counting and sedimentary data from the late Cenozoic Wuheshalu section in the convergence zone, to shed light on the convergence process of the Pamir and South Tian Shan. Large Triassic zircon U-Pb age populations in all seven samples suggest that Triassic igneous rocks from the North Pamir were the major source area for the late Cenozoic Wuheshalu section. In the Miocene, large populations of the North Pamir component supports rapid exhumation in the North Pamir and suggest that topography already existed there since the early Miocene. Exhumation of the South Tian Shan was relatively less important in the Miocene and its detritus could only reach a limited area in the foreland area. Gradually increasing sediment loading and convergence of the Pamir and South Tian Shan caused rapid subsidence in the convergence area. Since ca. 6-5.3 Ma, the combination of a major North Pamir component and a minor South Tian Shan component at the Wuheshalu section is consistent with active deformation of the South Tian Shan and the North Pamir. During deposition of the upper Atushi Formation, a larger proportion of North Pamir-derived sediments was deposited in the Wuheshalu section, maybe because faulting and northward propagation of the North Pamir caused northward displacement of the depocenter to north of the Wuheshalu section.
The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies-especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.
Past climate and continentality inferred from ice wedges at Batagay Highlands, interior Yakutia
(2019)
Ice wedges in the Yana Highlands of interior Yakutia - the most continental region of the Northern Hemisphere - were investigated to elucidate changes in winter climate and continentality that have taken place since the Middle Pleistocene. The Batagay megaslump exposes ice wedges and composite wedges that were sampled from three cryostratigraphic units: the lower ice complex of likely pre-Marine Isotope Stage (MIS) 6 age, the upper ice complex (Yedoma) and the upper sand unit (both MIS 3 to 2). A terrace of the nearby Adycha River provides a Late Holocene (MIS 1) ice wedge that serves as a modern reference for interpretation. The stable-isotope composition of ice wedges in the MIS 3 upper ice complex at Batagay is more depleted (mean delta O-18 about -35 parts per thousand) than those from 17 other ice-wedge study sites across coastal and central Yakutia. This observation points to lower winter temperatures and therefore higher continentality in the Yana Highlands during MIS 3. Likewise, more depleted isotope values are found in Holocene wedge ice (mean delta O-18 about -29 parts per thousand) compared to other sites in Yakutia. Ice-wedge isotopic signatures of the lower ice complex mean delta O-18 about -33 parts per thousand) and of the MIS 3-2 upper sand unit (mean delta O-18 from about -33 parts per thousand to -30 parts per thousand) are less distinctive regionally. The latter unit preserves traces of fast formation in rapidly accumulating sand sheets and of post-depositional isotopic fractionation.
Pollen-based quantitative land-cover reconstruction for northern Asia covering the last 40 ka cal BP
(2019)
We collected the available relative pollen productivity estimates (PPEs) for 27 major pollen taxa from Eurasia and applied them to estimate plant abundances during the last 40 ka cal BP (calibrated thousand years before present) using pollen counts from 203 fossil pollen records in northern Asia (north of 40 degrees N). These pollen records were organized into 42 site groups and regional mean plant abundances calculated using the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. Time-series clustering, constrained hierarchical clustering, and detrended canonical correspondence analysis were performed to investigate the regional pattern, time, and strength of vegetation changes, respectively. Reconstructed regional plant functional type (PFT) components for each site group are generally consistent with modern vegetation in that vegetation changes within the regions are characterized by minor changes in the abundance of PFTs rather than by an increase in new PFTs, particularly during the Holocene. We argue that pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, particularly when a high pollen producer invades areas dominated by low pollen producers. Comparisons with vegetation-independent climate records show that climate change is the primary factor driving land-cover changes at broad spatial and temporal scales. Vegetation changes in certain regions or periods, however, could not be explained by direct climate change, e.g. inland Siberia, where a sharp increase in evergreen conifer tree abundance occurred at ca. 7-8 ka cal BP despite an unchanging climate, potentially reflecting their response to complex climate-permafrost-fire-vegetation interactions and thus a possible long-term lagged climate response.
Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade‐offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual‐based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open‐source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals.
High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.
The Argentine-German Geodetic Observatory (AGGO) is one of the very few sites in the Southern Hemisphere equipped with comprehensive cutting-edge geodetic instrumentation. The employed observation techniques are used for a wide range of geophysical applications. The data set provides gravity time series and selected gravity models together with the hydrometeorological monitoring data of the observatory. These parameters are of great interest to the scientific community, e.g. for achieving accurate realization of terrestrial and celestial reference frames. Moreover, the availability of the hydrometeorological products is beneficial to inhabitants of the region as they allow for monitoring of environmental changes and natural hazards including extreme events. The hydrological data set is composed of time series of groundwater level, modelled and observed soil moisture content, soil temperature, and physical soil properties and aquifer properties. The meteorological time series include air temperature, humidity, pressure, wind speed, solar radiation, precipitation, and derived reference evapotranspiration. These data products are extended by gravity models of hydrological, oceanic, La Plata estuary, and atmospheric effects. The quality of the provided meteorological time series is tested via comparison to the two closest WMO (World Meteorological Organization) sites where data are available only in an inferior temporal resolution. The hydrological series are validated by comparing the respective forward-modelled gravity effects to independent gravity observations reduced up to a signal corresponding to local water storage variation. Most of the time series cover the time span between April 2016 and November 2018 with either no or only few missing data points. The data set is available at https://doi.org/10.588/GFZ.5.4.2018.001 (Mikolaj et al., 2018).
The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.
Hungry cities: how local food self-sufficiency relates to climate change, diets, and urbanisation
(2019)
Using a newly developed model approach and combining it with remote sensing, population, and climate data, first insights are provided into how local diets, urbanisation, and climate change relates to local urban food self-sufficiency. In plain terms, by utilizing the global peri-urban (PU) food production potential approximately lbn urban residents (30% of global urban population) can be locally nourished, whereby further urbanisation is by far the largest pressure factor on PU agriculture, followed by a change of diets, and climate change. A simple global food transport model which optimizes transport and neglects differences in local emission intensities indicates that CO2 emissions related to food transport can be reduced by a factor of 10.
Underground coal gasification (UCG) enables utilization of coal reserves, currently not economically exploitable due to complex geological boundary conditions. Hereby, UCG produces a high-calorific synthesis gas that can be used for generation of electricity, fuels, and chemical feedstock. The present study aims to identify economically-competitive, site-specific end-use options for onshore- and offshore-produced UCG synthesis gas, taking into account the capture and storage (CCS) and/or utilization (CCU) of produced CO2. Modeling results show that boundary conditions favoring electricity, methanol, and ammonia production expose low costs for air separation, low compression power requirements, and appropriate shares of H-2/N-2. Hereby, a gasification agent ratio of more than 30% oxygen by volume is not favorable from the economic and CO2 mitigation viewpoints. Compared to the costs of an offshore platform with its technical equipment, offshore drilling costs are marginal. Thus, uncertainties related to parameters influenced by drilling costs are negligible. In summary, techno-economic process modeling results reveal that air-blown gasification scenarios are the most cost-effective ones, while offshore UCG-CCS/CCU scenarios are up to 1.7 times more expensive than the related onshore processes. Hereby, all investigated onshore scenarios except from ammonia production under the assumed worst-case conditions are competitive on the European market.
The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999), and Wenchuan, China (2008), each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross-check against rainfall-induced landslide inventories seems to confirm that crest clustering is specific to seismic triggering as observed in previous studies. In our three study areas, the seismic ground motion parameters and lithologic and topographic features used do not seem to exert a primary control on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest and toe clustering occur in areas with specific geological features. Toe clustering of seismically induced landslides tends to occur along regional major faults. Crest clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used as a definite indicator of the topographic amplification of ground shaking.
Compound flooding, such as the co-occurrence of fluvial floods and extreme coastal water levels (CWL), may lead to significant impacts in densely-populated Low Elevation Coastal Zones. They may overstrain disaster management owing to the co-occurrence of inundation from rivers and the sea. Recent studies are limited by analyzing joint dependence between river discharge and either CWL or storm surges, and little is known about return levels of compound flooding, accounting for the covariance between drivers. Here, we assess the compound flood severity and identify hotspots for northwestern Europe during 1970–2014, using a newly developed Compound Hazard Ratio (CHR) that compares the severity of compound flooding associated with extreme CWL with the unconditional T-year fluvial peak discharge. We show that extreme CWL and stronger storms greatly amplify fluvial flood hazards. Our results, based on frequency analyses of observational records during 2013/2014’s winter storm Xaver, reveal that the river discharge of the 50-year compound flood is up to 70% larger, conditioned on the occurrence of extreme CWL, than that of the at-site peak discharge. For this event, nearly half of the stream gauges show increased flood hazards, demonstrating the importance of including the compounding effect of extreme CWL in river flood risk management.
The morphology of marine and lacustrine terraces has been largely used to measure past sea- and lake-level positions and estimate vertical deformation in a wealth of studies focused on climate and tectonic processes. To obtain accurate morphometric assessments of terrace morphology we present TerraceM-2, an improved version of our MatlabR (R) graphic-user interface that provides new methodologies for morphometric analyses as well as landscape evolution and fault-dislocation modeling. The new version includes novel routines to map the elevation and spatial distribution of terraces, to model their formation and evolution, and to estimate fault-slip rates from terrace deformation patterns. TerraceM-2 has significantly improves its processing speed and mapping capabilities, and includes separate functions for developing customized workflows beyond the graphic-user interface. We illustrate these new mapping and modeling capabilities with three examples: mapping lacustrine shorelines in the Dead Sea to estimate deformation across the Dead Sea Fault, landscape evolution modeling to estimate a history of uplift rates in southern Peru, and dislocation modeling of deformed marine terraces in California. These examples also illustrate the need to use topographic data of different resolutions. The new modeling and mapping routines of TerraceM-2 highlight the advantages of an integrated joint mapping and modeling approach to improve the efficiency and precision of coastal terrace metrics in both marine and lacustrine environments.
Rapidly changing climate in the Northern Hemisphere and associated socio-economic impacts require reliable understanding of lake systems as important freshwater resources and sensitive sentinels of environmental change. To better understand time-series data in lake sediment cores, it is necessary to gain information on within-lake spatial variabilities of environmental indicator data. Therefore, we retrieved a set of 38 samples from the sediment surface along spatial habitat gradients in the boreal, deep, and yet pristine Lake Bolshoe Toko in southern Yakutia, Russia. Our methods comprise laboratory analyses of the sediments for multiple proxy parameters, including diatom and chironomid taxonomy, oxygen isotopes from diatom silica, grain-size distributions, elemental compositions (XRF), organic carbon content, and mineralogy (XRD). We analysed the lake water for cations, anions, and isotopes. Our results show that the diatom assemblages are strongly influenced by water depth and dominated by planktonic species, i.e. Pliocaenicus bolshetokoensis. Species richness and diversity are higher in the northern part of the lake basin, associated with the availability of benthic, i.e. periphytic, niches in shallower waters. delta O-18(diatom) values are higher in the deeper south-western part of the lake, probably related to water temperature differences. The highest amount of the chironomid taxa underrepresented in the training set used for palaeoclimate inference was found close to the Utuk River and at southern littoral and profundal sites. Abiotic sediment components are not symmetrically distributed in the lake basin, but vary along restricted areas of differential environmental forcing. Grain size and organic matter are mainly controlled by both river input and water depth. Mineral (XRD) data distributions are influenced by the methamorphic lithology of the Stanovoy mountain range, while elements (XRF) are intermingled due to catchment and diagenetic differences. We conclude that the lake represents a valuable archive for multiproxy environmental reconstruction based on diatoms (including oxygen isotopes), chironomids, and sediment-geochemical parameters. Our analyses suggest multiple coring locations preferably at intermediate depth in the northern basin and the deep part in the central basin, to account for representative bioindicator distributions and higher temporal resolution, respectively.
Microbial community composition and abundance after millennia of submarine permafrost warming
(2019)
Warming of the Arctic led to an increase in permafrost temperatures by about 0.3 degrees C during the last decade. Permafrost warming is associated with increasing sediment water content, permeability, and diffusivity and could in the long term alter microbial community composition and abundance even before permafrost thaws. We studied the long-term effect (up to 2500 years) of submarine permafrost warming on microbial communities along an onshore-offshore transect on the Siberian Arctic Shelf displaying a natural temperature gradient of more than 10 degrees C. We analysed the in situ development of bacterial abundance and community composition through total cell counts (TCCs), quantitative PCR of bacterial gene abundance, and amplicon sequencing and correlated the microbial community data with temperature, pore water chemistry, and sediment physicochemical parameters. On timescales of centuries, permafrost warming coincided with an overall decreasing microbial abundance, whereas millennia after warming microbial abundance was similar to cold onshore permafrost. In addition, the dissolved organic carbon content of all cores was lowest in submarine permafrost after millennial-scale warming. Based on correlation analysis, TCC, unlike bacterial gene abundance, showed a significant rank-based negative correlation with increasing temperature, while bacterial gene copy numbers showed a strong negative correlation with salinity. Bacterial community composition correlated only weakly with temperature but strongly with the pore water stable isotopes delta O-18 and delta D, as well as with depth. The bacterial community showed substantial spatial variation and an overall dominance of Actinobacteria, Chloroflexi, Firmicutes, Gemmatimonadetes, and Proteobacteria, which are amongst the microbial taxa that were also found to be active in other frozen permafrost environments. We suggest that, millennia after permafrost warming by over 10 degrees C, microbial community composition and abundance show some indications for proliferation but mainly reflect the sedimentation history and paleoenvironment and not a direct effect through warming.
Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances
Uplift in the broken Andean foreland of the Argentine Santa Bárbara System (SBS) is associated with the contractional reactivation of basement anisotropies, similar to those reported from the thick-skinned Cretaceous-Eocene Laramide province of North America. Fault scarps, deformed Quaternary deposits and landforms, disrupted drainage patterns, and medium-sized earthquakes within the SBS suggest that movement along these structures may be a recurring phenomenon, with yet to be defined repeat intervals and rupture lengths. In contrast to the Subandes thrust belt farther north, where eastward-migrating deformation has generated a well-defined thrust front, the SBS records spatiotemporally disparate deformation along structures that are only known to the first order. We present herein the results of geomorphic desktop analyses, structural field observations, and 2D electrical resistivity tomography and seismic-refraction tomography surveys and an interpretation of seismic reflection profiles across suspected fault scarps in the sedimentary basins adjacent to the Candelaria Range (CR) basement uplift, in the south-central part of the SBS. Our analysis in the CR piedmont areas reveals consistency between the results of near-surface electrical resistivity and seismic-refraction tomography surveys, the locations of prominent fault scarps, and structural geometries at greater depth imaged by seismic reflection data. We suggest that this deformation is driven by deep-seated blind thrusting beneath the CR and associated regional warping, while shortening involving Mesozoic and Cenozoic sedimentary strata in the adjacent basins was accommodated by layer-parallel folding and flexural-slip faults that cut through Quaternary landforms and deposits at the surface.
Empirical evidence of the relationship between social support and post-disaster mental health provides support for a general beneficial effect of social support (main-effect model; Wheaton, 1985). From a theoretical perspective, a buffering effect of social support on the negative relationship between disaster-related stress and mental health also seems plausible (stress-buffering model; Wheaton, 1985). Previous studies, however, (a) have paid less attention to the buffering effect of social support and (b) have mainly relied on interpersonal support (but not collective-level support such as community resilience) when investigating this issue. This previous work might have underestimated the effect of support on post-disaster mental health. Building on a sample of residents in Germany recently affected by flooding (N = 118), we show that community resilience to flooding (but not general interpersonal social support) buffered against the negative effects of flooding on post-disaster mental health. The results support the stress-buffering model and call for a more detailed look at the relationship between support and resilience and post-disaster adjustment, including collective-level variables.
Colombia's agriculture, forestry and other land use sector accounts for nearly half of its total greenhouse gas (GHG) emissions. The importance of smallholder deforestation is comparatively high in relation to its regional counterparts, and livestock agriculture represents the largest driver of primary forest depletion. Silvopastoral systems (SPSs) are presented as agroecological solutions that synergistically enhance livestock productivity, improve local farmers' livelihoods and hold the potential to reduce pressure on forest conversion. The department of Caquetá represents Colombia's most important deforestation hotspot. Targeting smallholder livestock farms through survey data, in this work we investigate the GHG mitigation potential of implementing SPSs for smallholder farms in this region. Specifically, we assess whether the carbon sequestration taking place in the soil and biomass of SPSs is sufficient to offset the per-hectare increase in livestock GHG emissions resulting from higher stocking rates. To address these questions we use data on livestock population characteristics and historic land cover changes reported from a survey covering 158 farms and model the carbon sequestration occurring in three different scenarios of progressively-increased SPS complexity using the CO2 fix model. We find that, even with moderate tree planting densities, the implementation of SPSs can reduce GHG emissions by 2.6 Mg CO2e ha−1 yr−1 in relation to current practices, while increasing agriculture productivity and contributing to the restoration of severely degraded landscapes.
The Alpine orogen formed as a result of the collision between the Adriatic and European plates. Significant crustal heterogeneity exists within the region due to the long history of interplay between these plates, other continental and oceanic blocks in the region, and inherited crustal features from earlier orogenies. Deformation relating to the collision continues to the present day. Here, a seismically constrained, 3-D structural and density model of the lithosphere of the Alps and their respective forelands, derived from integrating numerous geoscientific datasets, was adjusted to match the observed gravity field. It is shown that the distribution of seismicity and deformation within the region correlates well to thickness and density changes within the crust, and that the present-day Adriatic crust is both thinner and denser (22.5 km, 2800 kg m(-3) ) than the European crust (27.5 km, 2750 kg m(-3)). Alpine crust derived from each respective plate is found to show the same trend, with zones of Adriatic provenance (Austro-Alpine unit and Southern Alps) found to be denser and those of European provenance (Helvetic zone and Tauern Window) to be less dense. This suggests that the respective plates and related terranes had similar crustal properties to the present-day ones prior to orogenesis. The model generated here is available for open-access use to further discussions about the crust in the region.
Climate change is affecting the rate of carbon cycling, particularly in the Arctic. Permafrost degradation through deeper thaw and physical disturbances results in the release of carbon dioxide and methane to the atmosphere and to an increase in lateral dissolved organic matter (DOM) fluxes. Whereas riverine DOM fluxes of the large Arctic rivers are well assessed, knowledge is limited with regard to small catchments that cover more than 40% of the Arctic drainage basin. Here, we use absorption measurements to characterize changes in DOM quantity and quality in a low Arctic (Herschel Island, Yukon, Canada) and a high Arctic (Cape Bounty, Melville Island, Nunavut, Canada) setting with regard to geographical differences, impacts of permafrost degradation, and rainfall events. We find that DOM quantity and quality is controlled by differences in vegetation cover and soil organic carbon content (SOCC). The low Arctic site has higher SOCC and greater abundance of plant material resulting in higher chromophoric dissolved organic matter (cDOM) and dissolved organic carbon (DOC) than in the high Arctic. DOC concentration and cDOM in surface waters at both sites show strong linear relationships similar to the one for the great Arctic rivers. We used the optical characteristics of DOM such as cDOM absorption, specific ultraviolet absorbance (SUVA), ultraviolet (UV) spectral slopes (S275-295), and slope ratio (SR) for assessing quality changes downstream, at base flow and storm flow conditions, and in relation to permafrost disturbance. DOM in streams at both sites demonstrated optical signatures indicative of photodegradation downstream processes, even over short distances of 2000 m. Flow pathways and the connected hydrological residence time control DOM quality. Deeper flow pathways allow the export of permafrost-derived DOM (i.e. from deeper in the active layer), whereas shallow pathways with shorter residence times lead to the export of fresh surface- and near-surface-derived DOM. Compared to the large Arctic rivers, DOM quality exported from the small catchments studied here is much fresher and therefore prone to degradation. Assessing optical properties of DOM and linking them to catchment properties will be a useful tool for understanding changing DOM fluxes and quality at a pan-Arctic scale.
Deformation associated with plate convergence at subduction zones is accommodated by a complex system involving fault slip and viscoelastic flow. These processes have proven difficult to disentangle. The 2010 M-w 8.8 Maule earthquake occurred close to the Chilean coast within a dense network of continuously recording Global Positioning System stations, which provide a comprehensive history of surface strain. We use these data to assemble a detailed picture of a structurally controlled megathrust fault frictional patchwork and the three-dimensional rheological and time-dependent viscosity structure of the lower crust and upper mantle, all of which control the relative importance of afterslip and viscoelastic relaxation during postseismic deformation. These results enhance our understanding of subduction dynamics including the interplay of localized and distributed deformation during the subduction zone earthquake cycle.
Nature-based solutions (NBS) have recently received attention due to their potential ability to sustainably reduce hydro-meteorological risks, providing co-benefits for both ecosystems and affected people. Therefore, pioneering research has dedicated efforts to optimize the design of NBS, to evaluate their wider co-benefits and to understand promoting and/or hampering governance conditions for the uptake of NBS. In this article, we aim to complement this research by conducting a comprehensive literature review of factors shaping people’s perceptions of NBS as a means to reduce hydro-meteorological risks. Based on 102 studies, we identified six topics shaping the current discussion in this field of research: (1) valuation of the co-benefits (including those related to ecosystems and society); (2) evaluation of risk reduction efficacy; (3) stakeholder participation; (4) socio-economic and location-specific conditions; (5) environmental attitude, and (6) uncertainty. Our analysis reveals that concerned empirical insights are diverse and even contradictory, they vary in the depth of the insights generated and are often not comparable for a lack of a sound theoretical-methodological grounding. We, therefore, propose a conceptual model outlining avenues for future research by indicating potential inter-linkages between constructs underlying perceptions of NBS to hydro-meteorological risks.
Germany and the United Kingdom have domestic shale gas reserves which they may exploit in the future to complement their national energy strategies. However gas production releases volatile organic compounds (VOC) and nitrogen oxides (NOx), which through photochemical reaction form ground-level ozone, an air pollutant that can trigger adverse health effects e.g. on the respiratory system. This study explores the range of impacts of a potential shale gas industry in these two countries on local and regional ambient ozone. To this end, comprehensive emission scenarios are used as the basis for input to an online-coupled regional chemistry transport model (WRF-Chem). Here we simulate shale gas scenarios over summer (June, July, August) 2011, exploring the effects of varying VOC emissions, gas speciation, and concentration of NOx emissions over space and time, on ozone formation. An evaluation of the model setup is performed, which exhibited the model’s ability to predict surface meteorological and chemical variables well compared with observations, and consistent with other studies. When different shale gas scenarios were employed, the results show a peak increase in maximum daily 8-hour average ozone from 3.7 to 28.3 μg m–3. In addition, we find that shale gas emissions can force ozone exceedances at a considerable percentage of regulatory measurement stations locally (up to 21% in Germany and 35% in the United Kingdom) and in distant countries through long-range transport, and increase the cumulative health-related metric SOMO35 (maximum percent increase of ~28%) throughout the region. Findings indicate that VOC emissions are important for ozone enhancement, and to a lesser extent NOx, meaning that VOC regulation for a future European shale gas industry will be of especial importance to mitigate unfavorable health outcomes. Overall our findings demonstrate that shale gas production in Europe can worsen ozone air quality on both the local and regional scales.