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The effect of lithology on the relationship between denudation rate and chemical weathering pathways
(2022)
The denudation of rocks in mountain belts exposes a range of fresh minerals to the surface of the Earth that are chemically weathered by acidic and oxygenated fluids. The impact of the resulting coupling between denudation and weathering rates fundamentally depends on the types of minerals that are weathering. Whereas silicate weathering sequesters CO2, the combination of sulfide oxidation and carbonate dissolution emits CO2 to the atmosphere. Here, we combine the concentrations of dissolved major elements in stream waters with Be-10 basin-wide denudation rates from 35 small catchments in eastern Tibet to elucidate the importance of lithology in modulating the relationships between denudation rate, chemical weathering pathways, and CO2 consumption or release. Our catchments span 3 orders of magnitude in denudation rate in low-grade flysch, high-grade metapelites, and granitoid rocks. For each stream, we estimate the concentrations of solutes sourced from silicate weathering, carbonate dissolution, and sulfide oxidation using a mixing model. We find that for all lithologies, cation concentrations from silicate weathering are largely independent of denudation rate, but solute concentrations from carbonates and, where present, sulfides increase with increasing denudation rate. With increasing denudation rates, weathering may therefore shift from consuming to releasing CO2 in both (meta)sedimentary and granitoid lithologies. For a given denudation rate, we report dissolved solid concentrations and inferred weathering fluxes in catchments underlain by (meta)sedimentary rock that are 2-10 times higher compared to catchments containing granitoid lithologies, even though climatic and topographic parameters do not vary systematically between these catchments. Thus, varying proportions of exposed (meta)sedimentary and igneous rocks during orogenesis could lead to changes in the sequestration and release of CO2 that are independent of denudation rate.
In the past decade, sediment connectivity has become a widely recognized characteristic of a geomorphic system. However, the quantification of functional connectivity (i.e. connectivity which arises due to the actual occurrence of sediment transport processes) and its variation over space and time is still a challenge. In this context, this study assesses the effects of expected future phenomena in the context of climate change (i.e. glacier retreat, permafrost degradation or meteorological extreme events) on sediment transport dynamics in a glacierised Alpine basin. The study area is the Sulden river basin (drainage area 130 km(2)) in the Italian Alps, which is composed of two geomorphologically diverse sub-basins. Based on graph theory, we evaluated the spatio-temporal variations in functional connectivity in these two sub-basins. The graph-object, obtained by manually mapping sediment transport processes between landforms, was adapted to 6 different hydro-meteorological scenarios, which derive from combining base, heatwave and rainstorm conditions with snowmelt and glacier-melt periods. For each scenario and each sub-basin, the sediment transport network and related catchment characteristics were analysed. To compare the effects of the scenarios on functional connectivity, we introduced a connectivity degree, calculated based on the area of the landforms involved in sediment cascades. Results indicate that the area of the basin connected to its outlet in terms of sediment transport might feature a six-fold increase in case of rainstorm conditions compared to "average " meteorological conditions assumed for the base scenario. Furthermore, markedly different effects of climate change on sediment connectivity are expected between the two sub-catchments due to their contrasting morphological and lithological characteristics, in terms of relative importance of rainfall triggered colluvial processes vs temperature-driven proglacial fluvial dynamics.
Reducing greenhouse gas emissions in food systems is becoming more challenging as food is increasingly consumed away from producer regions, highlighting the need to consider emissions embodied in trade in agricultural emissions accounting.
To address this, our study explores recent trends in trade-adjusted agricultural emissions of food items at the global, regional, and national levels.
We find that emissions are largely dependent on a country’s consumption patterns and their agricultural emission intensities relative to their trading partners’.
The absolute differences between the production-based and trade-adjusted emissions accounting approaches are especially apparent for major agricultural exporters and importers and where large shares of emission-intensive items such as ruminant meat, milk products and rice are involved.
In relative terms, some low-income and emerging and developing economies with consumption of high emission intensity food products show large differences between approaches.
Similar trends are also found under various specifications that account for trade and re-exports differently.
These findings could serve as an important element towards constructing national emissions reduction targets that consider trading partners, leading to more effective emissions reductions overall.
The concepts of CO2 emission, global warming, climate change, and their environmental impacts are of utmost importance for the understanding and protection of the ecosystems.
Among the natural sources of gases into the atmosphere, the contribution of geogenic sources plays a crucial role. However, while subaerial emissions are widely studied, submarine outgassing is not yet well understood.
In this study, we review and catalog 122 literature and unpublished data of submarine emissions distributed in ten coastal areas of the Aegean Sea. This catalog includes descriptions of the degassing vents through in situ observations, their chemical and isotopic compositions, and flux estimations.
Temperatures and pH data of surface seawaters in four areas affected by submarine degassing are also presented.
This overview provides useful information to researchers studying the impact of enhanced seawater CO2 concentrations related either to increasing CO2 levels in the atmosphere or leaking carbon capture and storage systems.
In-depth understanding of the reorganization of the hydrological cycle in response to global climate change is crucial in highly sensitive regions like the eastern Mediterranean, where water availability is a major factor for socioeconomic and political development.
The sediments of Lake Lisan provide a unique record of hydroclimatic change during the last glacial to Holocene transition (ca. 24-11 ka) with its tremendous water level drop of similar to 240 m that finally led to its transition into the present hypersaline water body-the Dead Sea.
Here we utilize high-resolution sedimentological analyses from the marginal terraces and deep lake to reconstruct an unprecedented seasonal record of the last millennia of Lake Lisan. Aragonite varve formation in intercalated intervals of our record demonstrates that a stepwise long-term lake level decline was interrupted by almost one millennium of rising or stable water level.
Even periods of pronounced water level drops indicated by gypsum deposition were interrupted by decades of positive water budgets.
Our results thus highlight that even during major climate change at the end of the last glacial, decadal to millennial periods of relatively stable or positive moisture supply occurred which could have been an important premise for human sedentism.
The region of the Andean back-arc of northwestern Argentina has been struck by several magnitude >= 6 crustal earthquakes since the first historically recorded event in 1692. One of these events corresponds to the Anta earthquake on 25 August 1948, with epicenter in the Santa Barbara System causing three deaths and severe damage in Salta and Jujuy provinces with maximum Modified Mercalli seismic intensities (MMI) of IX. We collected and digitized analog seismograms of this earthquake from worldwide seismic observatories in order to perform first-motion analysis and modeling of long-period teleseismic P-waveforms. Our results indicate a simple seismic source of M0 = 2.85 x 1019 N m consistent with a moment magnitude Mw = 6.9. We have also tested for the focal depth determining a shallow source at 8 km with a reverse focal mechanism solution with a minor dextral strike-slip component (strike 20 degrees, dip 30 degrees, rake 120 degrees) from the best fit of waveforms. Using magnitude size empirical relationships, the comparison of the obtained Mw 6.9 magnitude value and the ca. 10,000 km2 area of MMI >= IX from our seismic intensity map, which was obtained from newspaper and many historical reports, indicates a rupture length of 42 +/- 8 km for the Anta earthquake. We show our results in a 3D geological model around the epicentral area, which integrates modern seismicity, geological data, and information of a previously studied east-west cross section located a few kilometers south of the 1948 epicenter. The integration of all available information provides evidence of the re-activation of the Pie de la Sierra del Gallo fault during the 1948 Mw 6.9 shallow earthquake; this thrust fault bounds the Santa Barbara System along its western foothill.
A novel idea for an optimal time delay state space reconstruction from uni- and multivariate time series is presented. The entire embedding process is considered as a game, in which each move corresponds to an embedding cycle and is subject to an evaluation through an objective function. This way the embedding procedure can be modeled as a tree, in which each leaf holds a specific value of the objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path, which ends at the leaf with the lowest achieved value of the objective function. The method aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way, enabling practitioners to choose a statistic for possible delays in each embedding cycle as well as a suitable objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. As a proof of concept, we demonstrate the superiority of the proposed method over the classical time delay embedding methods using a variety of application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. Finally, we utilize state space reconstruction for the detection of causality and its strength between observables of a gas turbine type thermoacoustic combustor.
A large landslide (frozen debris avalanche) occurred at Assapaat on the south coast of the Nuussuaq Peninsula in Central West Greenland on June 13, 2021, at 04:04 local time. We present a compilation of available data from field observations, photos, remote sensing, and seismic monitoring to describe the event. Analysis of these data in combination with an analysis of pre- and post-failure digital elevation models results in the first description of this type of landslide. The frozen debris avalanche initiated as a 6.9 * 10(6) m(3) failure of permafrozen talus slope and underlying colluvium and till at 600-880 m elevation. It entrained a large volume of permafrozen colluvium along its 2.4 km path in two subsequent entrainment phases accumulating a total volume between 18.3 * 10(6) and 25.9 * 10(6) m(3). About 3.9 * 10(6) m(3) is estimated to have entered the Vaigat strait; however, no tsunami was reported, or is evident in the field. This is probably because the second stage of entrainment along with a flattening of slope angle reduced the mobility of the frozen debris avalanche. We hypothesise that the initial talus slope failure is dynamically conditioned by warming of the ice matrix that binds the permafrozen talus slope. When the slope ice temperature rises to a critical level, its shear resistance is reduced, resulting in an unstable talus slope prone to failure. Likewise, we attribute the large-scale entrainment to increasing slope temperature and take the frozen debris avalanche as a strong sign that the permafrost in this region is increasingly at a critical state. Global warming is enhanced in the Arctic and frequent landslide events in the past decade in Western Greenland let us hypothesise that continued warming will lead to an increase in the frequency and magnitude of these types of landslides. Essential data for critical arctic slopes such as precipitation, snowmelt, and ground and surface temperature are still missing to further test this hypothesis. It is thus strongly required that research funds are made available to better predict the change of landslide threat in the Arctic.
Measuring the variability of incoming neutrons locally would be usefull for the cosmic-ray neutron sensing (CRNS) method. As the measurement of high energy neutrons is not so easy, alternative particles can be considered for such purpose. Among them, muons are particles created from the same cascade of primary cosmic-ray fluxes that generate neutrons at the ground. In addition, they can be easily detected by small and relatively inexpensive detectors. For these reasons they could provide a suitable local alternative to incoming corrections based on remote neutron monitor data. The reported measurements demonstrated that muon detection system can detect incoming cosmic-ray variations locally. Furthermore the precision of this measurement technique is considered adequate for many CRNS applications.
In this study, 3-D models of P-wave velocity (Vp) and P-wave and S-wave ratio (Vp/Vs) of the crust and upper mantle in the Eastern and eastern Southern Alps (northern Italy and southern Austria) were calculated using local earthquake tomography (LET). The data set includes high-quality arrival times from well-constrained hypocenters observed by the dense, temporary seismic networks of the AlpArray AASN and SWATH-D. The resolution of the LET was checked by synthetic tests and analysis of the model resolution matrix. The small inter-station spacing (average of similar to 15 km within the SWATH-D network) allowed us to image crustal structure at unprecedented resolution across a key part of the Alps. The derived P velocity model revealed a highly heterogeneous crustal structure in the target area. One of the main findings is that the lower crust is thickened, forming a bulge at 30-50 km depth just south of and beneath the Periadriatic Fault and the Tauern Window. This indicates that the lower crust decoupled both from its mantle substratum as well as from its upper crust. The Moho, taken to be the iso-velocity contour of Vp = 7.25 km/s, agrees with the Moho depth from previous studies in the European and Adriatic forelands. It is shallower on the Adriatic side than on the European side. This is interpreted to indicate that the European Plate is subducted beneath the Adriatic Plate in the Eastern and eastern Southern Alps.
Climate Benefits of Cleaner Energy Transitions in East and South Asia Through Black Carbon Reduction
(2022)
The state of air pollution has historically been tightly linked to how we produce and use energy. Air pollutant emissions over Asia are now changing rapidly due to cleaner energy transitions; however, magnitudes of benefits for climate and air quality remain poorly quantified. The associated risks involve adverse health impacts, reduced agricultural yields, reduced freshwater availability, contributions to climate change, and economic costs. We focus particularly on climate benefits of energy transitions by making first-time use of two decades of high quality observations of atmospheric loading of light-absorbing black carbon (BC) over Kanpur (South Asia) and Beijing (East Asia) and relating these observations to changing energy, emissions, and economic trends in India and China. Our analysis reveals that absorption aerosol optical depth (AAOD) due to BC has decreased substantially, by 40% over Kanpur and 60% over Beijing between 2001 and 2017, and thus became decoupled from regional economic growth. Furthermore, the resultant decrease in BC emissions and BC AAOD over Asia is regionally coherent and occurs primarily due to transitions into cleaner energies (both renewables and fossil fuels) and not due to the decrease in primary energy supply or decrease in use of fossil use and biofuels and waste. Model simulations show that BC aerosols alone contribute about half of the surface temperature change (warming) of the total forcing due to greenhouse gases, natural and internal variability, and aerosols, thus clearly revealing the climate benefits due to a reduction in BC emissions, which would significantly reduce global warming. However, this modeling study excludes responses from natural variability, circulation, and sea ice responses, which cause relatively strong temperature fluctuations that may mask signals from BC aerosols. Our findings show additional benefits for climate (beyond benefits of CO2 reduction) and for several other issues of sustainability over South and East Asia, provide motivation for ongoing cleaner energy production, and consumption transitions, especially when they are associated with reduced emissions of air pollutants. Such an analysis connecting the trends in energy transitions and aerosol absorption loading, unavailable so far, is crucial for simulating the aerosol climate impacts over Asia which is quite uncertain.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
In some catchments, the distribution of annual maximum streamflow shows heavy tail behavior, meaning the occurrence probability of extreme events is higher than if the upper tail decayed exponentially. Neglecting heavy tail behavior can lead to an underestimation of the likelihood of extreme floods and the associated risk. Partly contradictory results regarding the controls of heavy tail behavior exist in the literature and the knowledge is still very dispersed and limited. To better understand the drivers, we analyze the upper tail behavior and its controls for 480 catchments in Germany and Austria over a period of more than 50 years. The catchments span from quickly reacting mountain catchments to large lowland catchments, allowing for general conclusions. We compile a wide range of event and catchment characteristics and investigate their association with an indicator of the tail heaviness of flood distributions, namely the shape parameter of the GEV distribution. Following univariate analyses of these characteristics, along with an evaluation of different aggregations of event characteristics, multiple linear regression models, as well as random forests, are constructed. A novel slope indicator, which represents the relation between the return period of flood peaks and event characteristics, captures the controls of heavy tails best. Variables describing the catchment response are found to dominate the heavy tail behavior, followed by event precipitation, flood seasonality, and catchment size. The pre-event moisture state in a catchment has no relevant impact on the tail heaviness even though it does influence flood magnitudes.
In this study we present a novel method for the automatic detection of minerals and elements using hyperspectral transmittance imaging microscopy measurements of complete thin sections (HyperTIM).
This is accomplished by using a hyperspectral camera system that operates in the visible and near-infrared (VNIR) range with a specifically designed sample holder, scanning setup, and a microscope lens.
We utilize this method on a monazite ore thin section from Steenkampskraal (South Africa), which we analyzed for the rare earth element (REE)-bearing mineral monazite ((Ce,Nd,La)PO4), with high concentrations of Nd. The transmittance analyses with the hyperspectral VNIR camera can be used to identify REE minerals and Nd in thin sections.
We propose a three-point band depth index, the Nd feature depth index (NdFD), and its related product the Nd band depth index (NdBDI), which enables automatic mineral detection and classification for the Nd-bearing monazites in thin sections. In combination with the average concentration of the relative Nd content, it permits a destruction-free, total concentration calculation for Nd across the entire thin section.
A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (Rain for Peru and Ecuador), at 0.1 degrees spatial resolution for the period 1981-2015 covering Peru and Ecuador. It is based on the application of 1) the random forest method to merge multisource precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and 2) observed and modeled streamflow data to first detect biases and second further adjust gridded precipitation by inversely applying the simulated results of the ecohydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Pacific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low, high, and peak flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods. Significance StatementWe developed a novel precipitation dataset RAIN4PE for Peru and Ecuador by merging multisource precipitation data (satellite, reanalysis, and ground-based precipitation) with terrain elevation using the random forest method. Furthermore, RAIN4PE was hydrologically corrected using streamflow data in watersheds with precipitation underestimation through reverse hydrology. The results of a comprehensive hydrological evaluation showed that RAIN4PE outperformed state-of-the-art precipitation datasets such as CHIRP, ERA5, CHIRPS, MSWEP, and PISCO in terms of daily and monthly streamflow simulations, including extremely low and high flows in almost all Peruvian and Ecuadorian catchments. This underlines the suitability of RAIN4PE for hydrometeorological applications in this region. Furthermore, our approach for the generation of RAIN4PE can be used in other data-scarce regions.
Assessment of climate change impact on discharge of the lakhmass catchment (Northwest Tunisia)
(2022)
The Mediterranean region is increasingly recognized as a climate change hotspot but is highly underrepresented in hydrological climate change studies. This study aims to investigate the climate change effects on the hydrology of Lakhmass catchment in Tunisia. Lakhmass catchment is a part of the Medium Valley of Medjerda in northwestern Tunisia that drains an area of 126 km(2). First, the Hydrologiska Byrans Vattenbalansavdelning light (HBV-light) model was calibrated and validated successfully at a daily time step to simulate discharge during the 1981-1986 period. The Nash Sutcliffe Efficiency and Percent bias (NSE, PBIAS) were (0.80, +2.0%) and (0.53, -9.5%) for calibration (September 1982-August 1984) and validation (September 1984-August 1986) periods, respectively. Second, HBV-light model was considered as a predictive tool to simulate discharge in a baseline period (1981-2009) and future projections using data (precipitation and temperature) from thirteen combinations of General Circulation Models (GCMs) and Regional Climatic Models (RCMs). We used two trajectories of Representative Concentration Pathways, RCP4.5 and RCP8.5, suggested by the Intergovernmental Panel on Climate Change (IPCC). Each RCP is divided into three projection periods: near-term (2010-2039), mid-term (2040-2069) and long-term (2070-2099). For both scenarios, a decrease in precipitation and discharge will be expected with an increase in air temperature and a reduction in precipitation with almost 5% for every +1 degrees C of global warming. By long-term (2070-2099) projection period, results suggested an increase in temperature with about 2.7 degrees C and 4 degrees C, and a decrease in precipitation of approximately 7.5% and 15% under RCP4.5 and RCP8.5, respectively. This will likely result in a reduction of discharge of 12.5% and 36.6% under RCP4.5 and RCP8.5, respectively. This situation calls for early climate change adaptation measures under a participatory approach, including multiple stakeholders and water users.
Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of-and the interaction between-climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry C-14-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 C-14 dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity-whether driven by reduced resource abundance or increased competition-can lead to violence in subsistence societies when the outcome is lower per capita resource availability.
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment.
The release of greenhouse gases from the large organic carbon stock in permafrost deposits in the circumarctic regions may accelerate global warming upon thaw. The extent of this positive climate feedback is thought to be largely controlled by the microbial degradability of the organic matter preserved in these sediments. In addition, weathering and oxidation processes may release inorganic carbon preserved in permafrost sediments as CO2, which is generally not accounted for. We used C-13 and C-14 analysis and isotopic mass balances to differentiate and quantify organic and inorganic carbon released as CO2 in the field from an active retrogressive thaw slump of Pleistocene-age Yedoma and during a 1.5-years incubation experiment. The results reveal that the dominant source of the CO2 released from freshly thawed Yedoma exposed as thaw mound is Pleistocene-age organic matter (48-80%) and to a lesser extent modern organic substrate (3-34%). A significant portion of the CO2 originated from inorganic carbon in the Yedoma (17-26%). The mixing of young, active layer material with Yedoma at a site on the slump floor led to the preferential mineralization of this young organic carbon source. Admixtures of younger organic substrates in the Yedoma thaw mound were small and thus rapidly consumed as shown by lower contributions to the CO2 produced during few weeks of aerobic incubation at 4 degrees C corresponding to approximately one thaw season. Future CO2 fluxes from the freshly thawed Yedoma will contain higher proportions of ancient inorganic (22%) and organic carbon (61-78%) as suggested by the results at the end, after 1.5 years of incubation. The increasing contribution of inorganic carbon during the incubation is favored by the accumulation of organic acids from microbial organic matter degradation resulting in lower pH values and, in consequence, in inorganic carbon dissolution. Because part of the inorganic carbon pool is assumed to be of pedogenic origin, these emissions would ultimately not alter carbon budgets. The results of this study highlight the preferential degradation of younger organic substrates in freshly thawed Yedoma, if available, and a substantial release of CO2 from inorganic sources.
The Arctic is changing rapidly and permafrost is thawing. Especially ice-rich permafrost, such as the late Pleistocene Yedoma, is vulnerable to rapid and deep thaw processes such as surface subsidence after the melting of ground ice. Due to permafrost thaw, the permafrost carbon pool is becoming increasingly accessible to microbes, leading to increased greenhouse gas emissions, which enhances the climate warming.
The assessment of the molecular structure and biodegradability of permafrost organic matter (OM) is highly needed. My research revolves around the question “how does permafrost thaw affect its OM storage?” More specifically, I assessed (1) how molecular biomarkers can be applied to characterize permafrost OM, (2) greenhouse gas production rates from thawing permafrost, and (3) the quality of OM of frozen and (previously) thawed sediments.
I studied deep (max. 55 m) Yedoma and thawed Yedoma permafrost sediments from Yakutia (Sakha Republic). I analyzed sediment cores taken below thermokarst lakes on the Bykovsky Peninsula (southeast of the Lena Delta) and in the Yukechi Alas (Central Yakutia), and headwall samples from the permafrost cliff Sobo-Sise (Lena Delta) and the retrogressive thaw slump Batagay (Yana Uplands). I measured biomarker concentrations of all sediment samples. Furthermore, I carried out incubation experiments to quantify greenhouse gas production in thawing permafrost.
I showed that the biomarker proxies are useful to assess the source of the OM and to distinguish between OM derived from terrestrial higher plants, aquatic plants and microbial activity. In addition, I showed that some proxies help to assess the degree of degradation of permafrost OM, especially when combined with sedimentological data in a multi-proxy approach. The OM of Yedoma is generally better preserved than that of thawed Yedoma sediments. The greenhouse gas production was highest in the permafrost sediments that thawed for the first time, meaning that the frozen Yedoma sediments contained most labile OM. Furthermore, I showed that the methanogenic communities had established in the recently thawed sediments, but not yet in the still-frozen sediments.
My research provided the first molecular biomarker distributions and organic carbon turnover data as well as insights in the state and processes in deep frozen and thawed Yedoma sediments. These findings show the relevance of studying OM in deep permafrost sediments.
Groundwater is critical in supporting current and future reliable water supply throughout Africa. Although continental maps of groundwater storage and recharge have been developed, we currently lack a clear understanding on how the controls on groundwater recharge vary across the entire continent. Reviewing the existing literature, we synthesize information on reported groundwater recharge controls in Africa. We find that 15 out of 22 of these controls can be characterised using global datasets. We develop 11 descriptors of climatic, topographic, vegetation, soil and geologic properties using global datasets, to characterise groundwater recharge controls in Africa. These descriptors cluster Africa into 15 Recharge Landscape Units for which we expect recharge controls to be similar. Over 80% of the continents land area is organized by just nine of these units. We also find that aggregating the Units by similarity into four broader Recharge Landscapes (Desert, Dryland, Wet tropical and Wet tropical forest) provides a suitable level of landscape organisation to explain differences in ground-based long-term mean annual recharge and recharge ratio (annual recharge / annual precipitation) estimates. Furthermore, wetter Recharge Landscapes are more efficient in converting rainfall to recharge than drier Recharge Landscapes as well as having higher annual recharge rates. In Dryland Recharge Landscapes, we found that annual recharge rates largely varied according to mean annual precipitation, whereas recharge ratio estimates increase with increasing monthly variability in P-PET. However, we were unable to explain why ground based estimates of recharge signatures vary across other Recharge Landscapes, in which there are fewer ground based recharge estimates, using global datasets alone. Even in dryland regions, there is still considerable unexplained variability in the estimates of annual recharge and recharge ratio, stressing the limitations of global datasets for investigating ground-based information.
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Despite its high-seismogenic potential, the details of the seismogenic processes of Zagros Simply Folded Belt (SFB) remains debated. Three large earthquakes (M-w 7.3, 5.9 and 6.3) struck in the Lurestan arc of the Zagros SFB in 2017 and 2018. The sequence was recorded by seismic stations at regional, and teleseismic distances. Coseismic surface displacements, measured by Sentinel-1A/B satellites, provide additional data and a unique opportunity to study these earthquakes in detail. Here, we complement previous studies of the coseismic slip distribution of the 12 November 2017 M-w 7.3 Ezgeleh earthquake by a detailed analysis of its aftershocks, and we analysed the rupture process of the two interrelated earthquakes (25 August 2018 M-w 5.9 Tazehabad and the 25 November 2018 M-w 6.3 Sarpol-e Zahab earthquakes). We model the surface displacements obtained from Interferometric Synthetic Aperture Radar (InSAR) measurements and seismic records. We conduct non-linear probabilistic optimizations based on joint InSAR and seismic data to obtain finite-fault rupture of these earthquakes. The Lurestan arc earthquakes were followed by a sustained aftershock activity, with 133 aftershocks exceeding M-n 4.0 until 30 December 2019. We rely on the permanent seismic networks of Iran and Iraq to relocate similar to 700 M-n 3 + events and estimate moment tensor solutions for 85 aftershocks down to M-w 4.0. The 2017 Ezgeleh earthquake has been considered to activate a low-angle (similar to 17 degrees) dextral-thrust fault at the depth of 10-20 km. However, most of its aftershocks have shallow centroid depths (8-12 km). The joint interpretation of finite source models, moment tensor and hypocentral location indicate that the 2018 Tazehabad and Sarpol-e Zahab earthquakes ruptured different strike-slip structures, providing evidence for the activation of the sinistral and dextral strike-slip faults, respectively. The deformation in the Lurestan arc is seismically accommodated by a complex fault system involving both thrust and strike-slip faults. Knowledge about the deformation characteristics is important for the understanding of crustal shortening, faulting and hazard and risk assessment in this region.
The Altiplano-Puna plateau, in Central Andes, is the second-largest continental plateau on Earth, extending between 22 degrees and 27 degrees S at an average altitude of 4400 m. The Puna plateau has been formed in consequence of the subduction of the oceanic Nazca Plate beneath the continental South American plate, which has an average crustal thickness of 50 km at this location. A large seismicity cluster, the Jujuy cluster, is observed at depth of 150-250 km beneath the central region of the Puna plateau. The cluster is seismically very active, with hundreds of earthquakes reported and a peak magnitude MW 6.6 on 25th August 2006. The cluster is situated in one of three band of intermediate-depth focus seismicity, which extend parallel to the trench roughly North to South. It has been hypothesized that the Jujuy cluster could be a seismic nest, a compact seismogenic region characterized by a high stationary activity relative to its surroundings. In this study, we collected more than 40 years of data from different catalogs and proof that the cluster meets the three conditions of a seismic nest. Compared to other known intermediate depth nests at Hindu Kush (Afganisthan) or Bucaramanga (Colombia), the Jujuy nest presents an outstanding seismicity rate, with more than 100 M4+ earthquakes per year. We additionally performed a detailed analysis of the rupture process of some of the largest earthquakes in the nest, by means of moment tensor inversion and directivity analysis. We focused on the time period 2017-2018, where the seismic monitoring was the most extended. Our results show that earthquakes in the nest take place within the eastward subducting oceanic plate, but rupture along sub-horizontal planes dipping westward. We suggest that seismicity at Jujuy nest is controlled by dehydration processes, which are also responsible for the generation of fluids ascending to the crust beneath the Puna volcanic region. We use the rupture plane and nest geometry to provide a constraint to maximal expected magnitude, which we estimate as MW -6.7.
Ground-motion models (GMMs) are often used to predict the random distribution of Spectral accelerations (SAs) at a site due to a nearby earthquake. In probabilistic seismic hazard and risk assessment, large earthquakes occurring close to a site are considered as critical scenarios. GMMs are expected to predict realistic SAs with low within-model uncertainty (sigma(mu)) for such rare scenarios. However, the datasets used to regress GMMs are usually deficient of data from critical scenarios. The (Kotha et al., A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe Bulletin of Earthquake Engineering 18:4091-4125, 2020) GMM developed from the Engineering strong motion (ESM) dataset was found to predict decreasing short-period SAs with increasing M-W >= M-h = 6.2, and with large sigma(mu) at near-source distances <= 30km. In this study, we updated the parametrisation of the GMM based on analyses of ESM and the Near source strong motion (NESS) datasets. With M-h = 5.7, we could rectify the M-W scaling issue, while also reducing sigma(mu). at M-W >= M-h. We then evaluated the GMM against NESS data, and found that the SAs from a few large, thrust-faulting events in California, New Zealand, Japan, and Mexico are significantly higher than GMM median predictions. However, recordings from these events were mostly made on soft-soil geology, and contain anisotropic pulse-like effects. A more thorough non-ergodic treatment of NESS was not possible because most sites sampled unique events in very diverse tectonic environments. We provide an updated set of GMM coefficients,sigma(mu), and heteroscedastic variance models; while also cautioning against its application for M-W <= 4 in low-moderate seismicity regions without evaluating the homogeneity of M-W estimates between pan-European ESM and regional datasets.
Ground-penetrating radar (GPR) is a method that can provide detailed information about the near subsurface in sedimentary and carbonate environments.
The classical interpretation of GPR data (e.g., based on manual feature selection) often is labor-intensive and limited by the experience of the intercally used for seismic interpretation, can provide faster, more repeatable, and less biased interpretations. We have recorded a 3D GPD data set collected across a paleokarst breccia pipe in the Billefjorden area on Spitsbergen, Svalbard. After performing advanced processing, we compare the results of a classical GPR interpretation to the results of an attribute-based classification.
Our attribute classification incorporates a selection of dip and textural attributes as the input for a k-means clustering approach. Similar to the results of the classical interpretation, the resulting classes differentiate between undisturbed strata and breccias or fault zones.
The classes also reveal details inside the breccia pipe that are not discerned in the classical fer that the intrapipe GPR facies result from subtle differences, such as breccia lithology, clast size, or pore-space filling.
Megathrust earthquakes impose changes of differential stress and pore pressure in the lithosphere-asthenosphere system that are transiently relaxed during the postseismic period primarily due to afterslip, viscoelastic and poroelastic processes.
Especially during the early postseismic phase, however, the relative contribution of these processes to the observed surface deformation is unclear.
To investigate this, we use geodetic data collected in the first 48 days following the 2010 Maule earthquake and a poro-viscoelastic forward model combined with an afterslip inversion.
This model approach fits the geodetic data 14% better than a pure elastic model. Particularly near the region of maximum coseismic slip, the predicted surface poroelastic uplift pattern explains well the observations.
If poroelasticity is neglected, the spatial afterslip distribution is locally altered by up to +/- 40%.
Moreover, we find that shallow crustal aftershocks mostly occur in regions of increased postseismic pore-pressure changes, indicating that both processes might be mechanically coupled.
Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries.
This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions.
The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations.
The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction.
This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method.
The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19% to-22% of our monthly evaluation.
The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.
Drainage-divide migration, controlled by rock-uplift and rainfall patterns, may play a major role in the geomorphic evolution of mountain ranges.
However, divide-migration rates over geologic timescales have only been estimated by theoretical studies and remain empirically poorly constrained.
Geomorphological evidence suggests that the Sierra de Aconquija, on the eastern side of the southern Central Andes, northwest Argentina, is undergoing active westward drainage-divide migration. The mountain range has been subjected to steep rock trajectories and pronounced orographic rainfall for the last several million years, presenting an ideal setting for using low-temperature thermochronometric data to explore its topographic evolution.
We perform three-dimensional thermal-kinematic modeling of previously published thermochronometric data spanning the windward and leeward sides of the range to explore the most likely structural and topographic evolution of the range.
We find that the data can be explained by scenarios involving drainage-divide migration alone, or by scenarios that also involve changes in the structures that have accommodated deformation through time.
By combining new Be-10-derived catchment-average denudation rates with geomorphic constraints on probable fault activity, we conclude that the evolution of the range was likely dominated by west-vergent faulting on a high-angle reverse fault underlying the range, together with westward drainage-divide migration at a rate of several km per million years.
Our findings place new constraints on the magnitudes and rates of drainage-divide migration in real landscapes, quantify the effects of orographic rainfall and erosion on the topographic evolution of a mountain range, and highlight the importance of considering drainage-divide migration when interpreting thermochronometer age patterns.
Improving nitrogen (N) status in European water bodies is a pressing issue. N levels depend not only on current but also past N inputs to the landscape, that have accumulated through time in legacy stores (e.g., soil, groundwater).
Catchment-scale N models, that are commonly used to investigate in-stream N levels, rarely examine the magnitude and dynamics of legacy components.
This study aims to gain a better understanding of the long-term fate of the N inputs and its uncertainties, using a legacy-driven N model (ELEMeNT) in Germany's largest national river basin (Weser; 38,450 km(2)) over the period 1960-2015.
We estimate the nine model parameters based on a progressive constraining strategy, to assess the value of different observational data sets.
We demonstrate that beyond in-stream N loading, soil N content and in-stream N concentration allow to reduce the equifinality in model parameterizations.
We find that more than 50% of the N surplus denitrifies (1480-2210 kg ha(-1)) and the stream export amounts to around 18% (410-640 kg ha(-1)), leaving behind as much as around 230-780 kg ha(-1) of N in the (soil) source zone and 10-105 kg ha(-1) in the subsurface.
A sensitivity analysis reveals the importance of different factors affecting the residual uncertainties in simulated N legacies, namely hydrologic travel time, denitrification rates, a coefficient characterizing the protection of organic N in source zone and N surplus input.
Our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce the equifinality in water quality modeling.
Agricultural production worldwide has been increasing in the last decades at a very fast pace and with it the waste generation. Livestock activities are one of the largest producers of residues in the agricultural sector and contribute greatly to climate change. The present chapter gives an introduction and an in-depth analysis of the waste management of livestock for the conversion in a circular agriculture and economy based on research and experience in the sector conducted in the last decades. The conversion of animal waste into energy generation is an opportunity for farmers to obtain additional economic benefits, while contributing to the environment by preventing the release of GHGs into the atmosphere. The use of animal waste for energy generation through anaerobic digestion is a progressive technique and is being widely accepted in Europe, where Germany is the leading country in the use of biogas plants for energy production among others in the European Union. Economically speaking, the livestock industry faces the challenge of converting its production into a clean and more profitable production. The goal of this chapter is to analyze the economic benefit as well as the environmental contribution and future challenges of the use of livestock waste in the biorefineries sector from different perspectives, based on an intensive literature review. This review is accompanied by a geospatial analysis component, mapping biogas reactor hotspots and clusters in Germany, by means of methods of spatial statistics as analysis methods as kernel density estimations (KDE) and K-means clustering, based on volunteer geographic data. The applied methods easily can be transferred to other regions and allow a quick macroscopic overview over existing biogas reactors; furthermore, an identification of cluster and hotspots with a high biogas potential, that in a subsequent step can be analyzed in depth in larger scales.
Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from.
However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions.
To shed light on
1) the age-depth relationship and its full uncertainty,
2) the magnitude of mixing processes affecting the downcore proxy variations, and
3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle.
Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( similar to 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 x 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth.
Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met.
Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples.
We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records.
Nocardioides alcanivorans sp. nov., a novel hexadecane-degrading species isolated from plastic waste
(2022)
Strain NGK65(T), a novel hexadecane degrading, non-motile, Gram-positive, rod-to-coccus shaped, aerobic bacterium, was isolated from plastic polluted soil sampled at a landfill.
Strain NGK65(T) hydrolysed casein, gelatin, urea and was catalase-positive. It optimally grew at 28 degrees C. in 0-1% NaCl and at pH 7.5-8.0. Glycerol, D-glucose, arbutin, aesculin, salicin, potassium 5-ketogluconate. sucrose, acetate, pyruvate and hexadecane were used as sole carbon sources.
The predominant membrane fatty acids were iso-C-16:0 followed by iso-C(17:)0 and C-18:1 omega 9c. The major polar lipids were phosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol and hydroxyphosphatidylinositol.
The cell-wall peptidoglycan type was A3 gamma, with LL-diaminopimelic acid and glycine as the diagnostic amino acids. MK 8 (H-4) was the predominant menaquinone. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain NGK65(T) belongs to the genus Nocardioides (phylum Actinobacteria). appearing most closely related to Nocardioides daejeonensis MJ31(T) (98.6%) and Nocardioides dubius KSL-104(T) (98.3%).
The genomic DNA G+C content of strain NGK65(T) was 68.2%.
Strain NGK65(T) and the type strains of species involved in the analysis had average nucleotide identity values of 78.3-71.9% as well as digital DNA-DNA hybridization values between 22.5 and 19.7%, which clearly indicated that the isolate represents a novel species within the genus Nocardioides.
Based on phenotypic and molecular characterization, strain NGK65(T) can clearly be differentiated from its phylogenetic neighbours to establish a novel species, for which the name Nocardioides alcanivorans sp. nov. is proposed.
The type strain is NGK65(T) (=DSM 113112(T)=NCCB 100846(T)).
Soil bacteria play a fundamental role in pedogenesis. However, knowledge about both the impact of climate and slope aspects on microbial communities and the consequences of these items in pedogenesis is lacking. Therefore, soil-bacterial communities from four sites and two different aspects along the climate gradient of the Chilean Coastal Cordillera were investigated. Using a combination of microbiological and physicochemical methods, soils that developed in arid, semi-arid, mediterranean, and humid climates were analyzed. Proteobacteria, Acidobacteria, Chloroflexi, Verrucomicrobia, and Planctomycetes were found to increase in abundance from arid to humid climates, while Actinobacteria and Gemmatimonadetes decreased along the transect. Bacterial-community structure varied with climate and aspect and was influenced by pH, bulk density, plant-available phosphorus, clay, and total organic-matter content. Higher bacterial specialization was found in arid and humid climates and on the south-facing slope and was likely promoted by stable microclimatic conditions. The presence of specialists was associated with ecosystem-functional traits, which shifted from pioneers that accumulated organic matter in arid climates to organic decomposers in humid climates. These findings provide new perspectives on how climate and slope aspects influence the composition and functional capabilities of bacteria, with most of these capabilities being involved in pedogenetic processes.
Shallow earthquakes frequently disturb the hydrological and mechanical state of the subsurface, with consequences for hazard and water management. Transient post-seismic hydrological behavior has been widely reported, suggesting that the recovery of material properties (relaxation) following ground shaking may impact groundwater fluctuations. However, the monitoring of seismic velocity variations associated with earthquake damage and hydrological variations are often done assuming that both effects are independent. In a field site prone to highly variable hydrological conditions, we disentangle the different forcing of the relative seismic velocity variations delta v retrieved from a small dense seismic array in Nepal in the aftermath of the 2015 M-w 7.8 Gorkha earthquake. We successfully model transient damage effects by introducing a universal relaxation function that contains a unique maximum relaxation timescale for the main shock and the aftershocks, independent of the ground shaking levels. Next, we remove the modeled velocity from the raw data and test whether the corresponding residuals agree with a background hydrological behavior we inferred from a previously calibrated groundwater model. The fitting of the delta v data with this model is improved when we introduce transient hydrological properties in the phase immediately following the main shock. This transient behavior, interpreted as an enhanced permeability in the shallow subsurface, lasts for similar to 6 months and is shorter than the damage relaxation (similar to 1 yr). Thus, we demonstrate the capability of seismic interferometry to deconvolve transient hydrological properties after earthquakes from non-linear mechanical recovery.
Rainfall-intense summer monsoon seasons on the Indian subcontinent that are exceeding long-term averages cause widespread floods and landslides.
Here we show that the latest generation of coupled climate models robustly project an intensification of very rainfall-intense seasons (June-September).
Under the shared socioeconomic pathway SSP5-8.5, very wet monsoon seasons as observed in only 5 years in the period 1965-2015 are projected to occur 8 times more often in 2050-2100 in the multi-model average.
Under SSP2-4.5, these seasons become only a factor of 6 times more frequent, showing that even modest efforts to mitigate climate change can have a strong impact on the frequency of very strong rainfall seasons.
Besides, we find that the increasing risk of extreme seasonal rainfall is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase.
Phase transitions in molecular crystals are often determined by intermolecular interactions. The cage complex of [Co(C12H30N8)](3+) . 3 NO3- is reported to undergo a disorder-order phase transition at T-c1 approximate to 133 K upon cooling. Temperature-dependent neutron and synchrotron diffraction experiments revealed satellite reflections in addition to main reflections in the diffraction patterns below T-c1. The modulation wave vector varies as function of temperature and locks in at T-c3 approximate to 98 K. Here, we demonstrate that the crystal symmetry lowers from hexagonal to monoclinic in the incommensurately modulated phases in T-c1<T<T-c3. Distinctive levels of competitions: trade-off between longer N-H...O and shorter C-H...O hydrogen bonds; steric constraints to dense C-H...O bonds give rise to pronounced modulation of the basic structure. Severely frustrated crystal packing in the incommensurate phase is precursor to optimal balance of intermolecular interactions in the lock-in phase.
A detailed analysis of horizontal and vertical particulate matter (PM) fluxes during wind erosion has been done, based on measurements of PM smaller than 10, 2.5, and 1.0 mu mm, at windward and leeward positions on a measuring field. The three fractions of PM measurement are differently influenced by the increasing wind and shear velocities of the wind. The measured concentrations of the coarser fractions of the fine dust, PM10, and PM2.5, increase with wind and shear velocity, whereas the PM1.0 concentrations show no clear correlation to the shear velocity. The share of PM2.5 on PM10 depends on the measurement height and wind speed and varies between 4 and 12 m/s at the 1 m height ranging from 25% to 7% (average 10%), and at the 4 m height from 39% to 23% (average 30%). Although general relationships between wind speed, PM concentration, and horizontal and vertical fluxes could be found, the contribution of the measuring field was very low, as balances of incoming and outgoing fluxes show. Consequently, the measured PM concentrations are determined from a variety of sources, such as traffic on unpaved roads, cattle drives, tillage operations, and wind erosion, and thus, represent all components of land use and landscape structure in the near and far surroundings of the measuring field. The current results may reflect factors from the landscape scale rather than the influence of field-related variables. The measuring devices used to monitor PM concentrations showed differences of up to 20%, which led to considerable deviations when determining total balances. Differences up to 67% between the calculated fluxes prove the necessity of a previous calibration of the devices used. (c) 2022 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion Research.
Among the multitude of geomorphological processes, aeolian shaping processes are of special character, Pedogenic dust is one of the most important sources of atmospheric aerosols and therefore regarded as a key player for atmospheric processes. Soil dust emissions, being complex in composition and properties, influence atmospheric processes and air quality and has impacts on other ecosystems. In this because even though their immediate impact can be considered low (exceptions exist), their constant and large-scale force makes them a powerful player in the earth system. dissertation, we unravel a novel scientific understanding of this complex system based on a holistic dataset acquired during a series of field experiments on arable land in La Pampa, Argentina. The field experiments as well as the generated data provide information about topography, various soil parameters, the atmospheric dynamics in the very lower atmosphere (4m height) as well as measurements regarding aeolian particle movement across a wide range of particle size classes between 0.2μm up to the coarse sand.
The investigations focus on three topics: (a) the effects of low-scale landscape structures on aeolian transport processes of the coarse particle fraction, (b) the horizontal and vertical fluxes of the very fine particles and (c) the impact of wind gusts on particle emissions.
Among other considerations presented in this thesis, it could in particular be shown, that even though the small-scale topology does have a clear impact on erosion and deposition patterns, also physical soil parameters need to be taken into account for a robust statistical modelling of the latter. Furthermore, specifically the vertical fluxes of particulate matter have different characteristics for the particle size classes. Finally, a novel statistical measure was introduced to quantify the impact of wind gusts on the particle uptake and its application on the provided data set. The aforementioned measure shows significantly increased particle concentrations during points in time defined as gust event.
With its holistic approach, this thesis further contributes to the fundamental understanding of how atmosphere and pedosphere are intertwined and affect each other.
Southeastern Tibetan Plateau growth revealed by inverse analysis of landscape evolution model
(2022)
The Cenozoic history of the Tibetan Plateau topography is critical for understanding the evolution of the Indian-Eurasian collision, climate, and biodiversity. However, the long-term growth and landscape evolution of the Tibetan Plateau remain ambiguous, it remains unclear if plateau uplift occurred soon after the India-Asia collision in the Paleogene (similar to 50-25 Ma) or later in the Neogene (similar to 20-5 Ma). Here, we reproduce the uplift history of the southeastern Tibetan Plateau using a 2D landscape evolution model, which simultaneously solves fluvial erosion and sediment transport processes in the drainage basins of the Three Rivers region (Yangtze, Mekong, and Salween Rivers). Our model was optimized through a formal inverse analysis with 20,000 forward simulations, which aims to reconcile the transient states of the present-day river profiles. The results, compared to existing paleoelevation and thermochronologic data, suggest initially low elevations (similar to 300-500 m) during the Paleogene, followed by a gradual southeastward propagation of topographic uplift of the plateau margin.
Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms.
Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms.
The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.
On their way from inland to the ocean, flowing water bodies, their constituents and their biotic communities are ex-posed to complex transport and transformation processes. However, detailed process knowledge as revealed by La-grangian measurements adjusted to travel time is rare in large rivers, in particular at hydrological extremes. To fill this gap, we investigated autotrophic processes, heterotrophic carbon utilization, and micropollutant concentrations applying a Lagrangian sampling design in a 600 km section of the River Elbe (Germany) at historically low discharge. Under base flow conditions, we expect the maximum intensity of instream processes and of point source impacts. Phy-toplankton biomass and photosynthesis increased from upstream to downstream sites but maximum chlorophyll con-centration was lower than at mean discharge. Concentrations of dissolved macronutrients decreased to almost complete phosphate depletion and low nitrate values. The longitudinal increase of bacterial abundance and production was less pronounced than in wetter years and bacterial community composition changed downstream. Molecular analyses revealed a longitudinal increase of many DOM components due to microbial production, whereas saturated lipid-like DOM, unsaturated aromatics and polyphenols, and some CHOS surfactants declined. In decomposition exper-iments, DOM components with high O/C ratios and high masses decreased whereas those with low O/C ratios, low masses, and high nitrogen content increased at all sites. Radiocarbon age analyses showed that DOC was relatively old (890-1870 years B.P.), whereas the mineralized fraction was much younger suggesting predominant oxidation of algal lysis products and exudates particularly at downstream sites. Micropollutants determining toxicity for algae (terbuthylazine, terbutryn, isoproturon and lenacil), hexachlorocyclohexanes and DDTs showed higher concentrations from the middle towards the downstream part but calculated toxicity was not negatively correlated to phytoplankton. Overall, autotrophic and heterotrophic process rates and micropollutant concentrations increased from up-to down-stream reaches, but their magnitudes were not distinctly different to conditions at medium discharges.
Sulfate reduction is the quantitatively most important process to degrade organic matter in anoxic marine sediment and has been studied intensively in a variety of settings. Guaymas Basin, a young marginal ocean basin, offers the unique opportunity to study sulfate reduction in an environment characterized by organic-rich sediment, high sedimentation rates, and high geothermal gradients (100-958 degrees C km(-1)). We measured sulfate reduction rates (SRR) in samples taken during the International Ocean Discovery Program (IODP) Expedition 385 using incubation experiments with radiolabeled (SO42-)-S-35 carried out at in situ pressure and temperature. The highest SRR (387 nmol cm(-3) d(-1)) was recorded in near-surface sediments from Site U1548C, which had the steepest geothermal gradient (958 degrees C km(-1)). At this site, SRR were generally over an order of magnitude higher than at similar depths at other sites (e.g., 387-157 nmol cm(-3) d(-1) at 1.9 mbsf from Site U1548C vs. 46-1.0 nmol cm(-3) d(-1) at 2.1 mbsf from Site U1552B). Site U1546D is characterized by a sill intrusion, but it had already reached thermal equilibrium and SRR were in the same range as nearby Site U1545C, which is minimally affected by sills. The wide temperature range observed at each drill site suggests major shifts in microbial community composition with very different temperature optima but awaits confirmation by molecular biological analyses. At the transition between the mesophilic and thermophilic range around 40 degrees C-60 degrees C, sulfate-reducing activity appears to be decreased, particularly in more oligotrophic settings, but shows a slight recovery at higher temperatures.
The James Ross archipelago houses numerous lakes and ponds. In this region, a vast diatom and cyanobacterial variety has been reported; however, the prokaryotic diversity in microbial mats from these lakes remains poorly explored.
Here, a high-throughput sequencing of 16S rRNA gene in microbial mats from Lake Bart-Roja in James Ross Island and lakes Pan Negro and North Pan Negro located in Vega Island was performed. Combined with mineralogical and environmental characteristics, we analyzed the diversity and structure of the microbial communities. Sequences assigned to Archaea were extremely low, while Bacteria domain prevailed with the abundance of Proteobacteria (mostly Betaproteobacteriales) followed by Bacteroidetes, Verrucomicrobia, Firmicutes, and Cyanobacteria.
Local environmental conditions, such as conductivity and Eh, provided differential microbial assemblages that might have implications in the oligotrophic status of the lakes. Consequently, a clear segregation at the family level was observed.
In this sense, the assigned diversity was related to taxa recognized as denitrifiers and sulfur oxidizers. Particularly, in Lake Pan Negro sulfur-reducing and methanogenic representatives were also found and positively correlate with alkalinity and water depth.
Moreover, Deinococcus-Thermus was observed in Lake Bart-Roja, while Melainabacteria (Cyanobacteria)-poorly reported in Antarctic mats-was detected in Lake Pan Negro. Epsilonbacteraeota was exclusively found in this lake, suggesting new potential phylotypes. This study contributes to the understanding of the diversity, composition, and structure of Antarctic benthic microbial ecosystems and provides highly valuable information, which can be used as a proxy to evaluate environmental changes affecting Antarctic microbiota.
Hydrodynamic interactions, i.e. the floodplain storage effects caused by inundations upstream on flood wave propagation, inundation areas, and flood damage downstream, are important but often ignored in large-scale flood risk assessments. Although new methods considering these effects sometimes emerge, they are often limited to a small or meso scale. In this study, we investigate the role of hydrodynamic interactions and floodplain storage on flood hazard and risk in the German part of the Rhine basin. To do so, we compare a new continuous 1D routing scheme within a flood risk model chain to the piece-wise routing scheme, which largely neglects floodplain storage. The results show that floodplain storage is significant, lowers water levels and discharges, and reduces risks by over 50%. Therefore, for accurate risk assessments, a system approach must be adopted, and floodplain storage and hydrodynamic interactions must carefully be considered.
Gas hydrates are ice-like crystalline compounds made of water cavities that retain various types of guest molecules. Natural gas hydrates are CH4-rich but also contain higher hydrocarbons as well as CO2, H2S, etc. They are highly dependent of local pressure and temperature conditions. Considering the high energy content, natural gas hydrates are artificially dissociated for the production of methane gas. Besides, they may also dissociate in response to global warming. It is therefore crucial to investigate the hydrate nucleation and growth process at a molecular level. The understanding of how guest molecules in the hydrate cavities respond to warming climate or gas injection is also of great importance.
This thesis is concerned with a systematic investigation of simple and mixed gas hydrates at conditions relevant to the natural hydrate reservoir in Qilian Mountain permafrost, China. A high-pressure cell that integrated into the confocal Raman spectroscopy ensured a precise and continuous characterization of the hydrate phase during formation/dissociation/transformation processes with a high special and spectral resolution. By applying laboratory experiments, the formation of mixed gas hydrates containing other hydrocarbons besides methane was simulated in consideration of the effects from gas supply conditions and sediments. The results revealed a preferential enclathration of different guest molecules in hydrate cavities and further refute the common hypothesis of the coexistence of hydrate phases due to a changing feed gas phase. However, the presence of specific minerals and organic compounds in sediments may have significant impacts on the coexisting solid phases. With regard to the dissociation, the formation damage caused by fines mobilization and migration during hydrate decomposition was reported for the first time, illustrating the complex interactions between fine grains and hydrate particles. Gas hydrates, starting from simple CH4 hydrates to binary CH4—C3H8 hydrates and multi-component mixed hydrates were decomposed by thermal stimulation mimicking global warming. The mechanisms of guest substitution in hydrate structures were studied through the experimental data obtained from CH4—CO2, CH4—mixed gas hydrates and mixed gas hydrates—CO2 systems. For the first time, a second transformation behavior was documented during the transformation process from CH4 hydrates to CO2-rich mixed hydrates. Most of the crystals grew or maintained when exposed to CO2 gas while some others decreased in sizes and even disappeared over time. The highlight of the two last experimental simulations was to visualize and characterize the hydrate crystals which were at different structural transition stages. These experimental simulations enhanced our knowledge about the mixed gas hydrates in natural reservoirs and improved our capability to assess the response to global warming.
Large-Scale interseismic strain mapping of the NE Tibetan Plateau from Sentinel-1 Interferometry
(2022)
The launches of the Sentinel-1 synthetic aperture radar satellites in 2014 and 2016 started a new era of high-resolution velocity and strain rate mapping for the continents. However, multiple challenges exist in tying independently processed velocity data sets to a common reference frame and producing high-resolution strain rate fields. We analyze Sentinel-1 data acquired between 2014 and 2019 over the northeast Tibetan Plateau, and develop new methods to derive east and vertical velocities with similar to 100 m resolution and similar to 1 mm/yr accuracy across an area of 440,000 km(2). By implementing a new method of combining horizontal gradients of filtered east and interpolated north velocities, we derive the first similar to 1 km resolution strain rate field for this tectonically active region. The strain rate fields show concentrated shear strain along the Haiyuan and East Kunlun Faults, and local contractional strain on fault junctions, within the Qilianshan thrusts, and around the Longyangxia Reservoir. The Laohushan-Jingtai creeping section of the Haiyuan Fault is highlighted in our data set by extremely rapid strain rates. Strain across unknown portions of the Haiyuan Fault system, including shear on the eastern extension of the Dabanshan Fault and contraction at the western flank of the Quwushan, highlight unmapped tectonic structures. In addition to the uplift across most of the lowlands, the vertical velocities also contain climatic, hydrological or anthropogenic-related deformation signals. We demonstrate the enhanced view of large-scale active tectonic processes provided by high-resolution velocities and strain rates derived from Sentinel-1 data and highlight associated wide-ranging research applications.
In seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaiso (Chile) subjected to seismic ground-shaking from one subduction earthquake. We have found that building class reconnaissance, either from prior assumptions by desktop studies with aggregated data (top-down approach), or from building-by-building data collection (bottom-up approach), plays a fundamental role in the statistical modelling of exposure. To model the vulnerability of such a heterogeneous building stock, we require that their associated set of structural fragility functions handle multiple spectral periods. Thereby, we also discuss the relevance and specific uncertainty upon generating either uncorrelated or spatially cross-correlated ground motion fields within this framework. We successively show how various epistemic uncertainties embedded within these probabilistic exposure models are differently propagated throughout the computed direct financial losses. This work calls for further efforts to redesign desktop exposure studies, while also highlighting the importance of exposure data collection with standardized and iterative approaches.
Understanding catchment controls on catchment solute export is a prerequisite for water quality management. StorAge Selection (SAS) functions encapsulate essential information about catchment functioning in terms of discharge selection preference and solute export dynamics. However, they lack information on the spatial origin of solutes when applied at the catchment scale, thereby limiting our understanding of the internal (subcatchment) functioning. Here, we parameterized SAS functions in a spatially explicit way to understand the internal catchment responses and transport dynamics of reactive dissolved nitrate (N-NO3). The model was applied in a nested mesoscale catchment (457 km(2)), consisting of a mountainous partly forested, partly agricultural subcatchment, a middle-reach forested subcatchment, and a lowland agricultural subcatchment. The model captured flow and nitrate concentration dynamics not only at the catchment outlet but also at internal gauging stations. Results reveal disparate subsurface mixing dynamics and nitrate export among headwater and lowland subcatchments. The headwater subcatchment has high seasonal variation in subsurface mixing schemes and younger water in discharge, while the lowland subcatchment has less pronounced seasonality in subsurface mixing and much older water in discharge. Consequently, nitrate concentration in discharge from the headwater subcatchment shows strong seasonality, whereas that from the lowland subcatchment is stable in time. The temporally varying responses of headwater and lowland subcatchments alternate the dominant contribution to nitrate export in high and low-flow periods between subcatchments. Overall, our results demonstrate that the spatially explicit SAS modeling provides useful information about internal catchment functioning, helping to develop or evaluate spatial management practices.
The most profound shift in the African hydroclimate of the last 1 million years occurred around 300 thousand years (ka) ago.
This change in African hydroclimate is manifest as an east-west change in moisture balance that cannot be fully explained through linkages to high latitude climate systems.
The east-west shift is, instead, probably driven by a shift in the tropical Walker Circulation related to sea surface temperature change driven by orbital forcing. Comparing records of past vegetation change, and hominin evolution and development, with this breakpoint in the climate system is challenging owing to the paucity of study sites available and uncertainties regarding the dating of records. Notwithstanding these uncertainties we find that, broadly speaking, both vegetation and hominins change around 300 ka.
The vegetative backdrop suggests that relative abundance of vegetative resources shifted from western to eastern Africa, although resources would have persisted across the continent.
The climatic and vegetation changes probably provided challenges for hominins and are broadly coincident with the appearance of Homo sapiens (ca 315 ka) and the emergence of Middle Stone Age technology.
The concomitant changes in climate, vegetation and hominin evolution suggest that these factors are closely intertwined.
This article is part of the theme issue 'Tropical forests in the deep human past'.
The region of West Bohemia and Upper Palatinate belongs to the West Bohemian Massif. The study area is situated at the junction of three different Variscan tectonic units and hosts the ENE-WSW trending Ohre Rift as well as many different fault systems. The entire region is characterized by ongoing magmatic processes in the intra-continental lithospheric mantle expressed by a series of phenomena, including e.g. the occurrence of repeated earthquake swarms and massive degassing of mantle derived CO2 in form of mineral springs and mofettes. Ongoing active tectonics is mainly manifested by Cenozoic volcanism represented by different Quaternary volcanic structures. All these phenomena make the Ohre Rift a unique target area for European intra-continental geo-scientific research. With magnetotelluric (MT) measurements we image the subsurface distribution of the electrical resistivity and map possible fluid pathways. Two-dimensional (2D) inversion results by Munoz et al. (2018) reveal a conductive channel in the vicinity of the earthquake swarm region that extends from the lower crust to the surface forming a pathway for fluids into the region of the mofettes. A second conductive channel is present in the south of their model; however, their 2D inversions allow ambiguous interpretations of this feature. Therefore, we conducted a large 3D MT field experiment extending the study area towards the south. The 3D inversion result matches well with the known geology imaging different fluid/magma reservoirs at crust-mantle depth and mapping possible fluid pathways from the reservoirs to the surface feeding known mofettes and spas. A comparison of 3D and 2D inversion results suggests that the 2D inversion results are considerably characterized by 3D and off-profile structures. In this context, the new results advocate for the swarm earthquakes being located in the resistive host rock surrounding the conductive channels; a finding in line with observations e.g. at the San Andreas Fault, California.
We construct and examine the prototype of a deep learning-based ground-motion model (GMM) that is both fully data driven and nonergodic. We formulate ground-motion modeling as an image processing task, in which a specific type of neural network, the U-Net, relates continuous, horizontal maps of earthquake predictive parameters to sparse observations of a ground-motion intensity measure (IM). The processing of map-shaped data allows the natural incorporation of absolute earthquake source and observation site coordinates, and is, therefore, well suited to include site-, source-, and path-specific amplification effects in a nonergodic GMM. Data-driven interpolation of the IM between observation points is an inherent feature of the U-Net and requires no a priori assumptions. We evaluate our model using both a synthetic dataset and a subset of observations from the KiK-net strong motion network in the Kanto basin in Japan. We find that the U-Net model is capable of learning the magnitude???distance scaling, as well as site-, source-, and path-specific amplification effects from a strong motion dataset. The interpolation scheme is evaluated using a fivefold cross validation and is found to provide on average unbiased predictions. The magnitude???distance scaling as well as the site amplification of response spectral acceleration at a period of 1 s obtained for the Kanto basin are comparable to previous regional studies.
The main Marmara fault (MMF) extends for 150 km through the Sea of Marmara and forms the only portion of the North Anatolian fault zone that has not ruptured in a large event (Mw >7) for the last 250 yr. Accordingly, this portion is potentially a major source contributing to the seismic hazard of the Istanbul region. On 26 September 2019, a sequence of moderate-sized events started along the MMF only 20 km south of Istanbul and were widely felt by the population. The largest three events, 26 September Mw 5.8 (10:59 UTC), 26 September 2019 Mw 4.1 (11:26 UTC), and 20 January 2020 Mw 4.7 were recorded by numerous strong-motion seismic stations and the resulting ground motions were compared to the predicted means resulting from a set of the most recent ground-motion prediction equations (GMPEs). The estimated residuals were used to investigate the spatial variation of ground motion across the Marmara region. Our results show a strong azimuthal trend in ground-motion residuals, which might indicate systematically repeating directivity effects toward the eastern Marmara region.
The new in situ geodynamic laboratory established in the framework of the ICDP Eger project aims to develop the most modern, comprehensive, multiparameter laboratory at depth for studying earthquake swarms, crustal fluid flow, mantle-derived CO2 and helium degassing, and processes of the deep biosphere. In order to reach a new level of high-frequency, near-source and multiparameter observation of earthquake swarms and related phenomena, such a laboratory comprises a set of shallow boreholes with high-frequency 3-D seismic arrays as well as modern continuous real-time fluid monitoring at depth and the study of the deep biosphere.
This laboratory is located in the western part of the Eger Rift at the border of the Czech Republic and Germany (in the West Bohemia–Vogtland geodynamic region) and comprises a set of five boreholes around the seismoactive zone. To date, all monitoring boreholes have been drilled. This includes the seismic monitoring boreholes S1, S2 and S3 in the crystalline units north and east of the major Nový Kostel seismogenic zone, borehole F3 in the Hartoušov mofette field and borehole S4 in the newly discovered Bažina maar near Libá. Supplementary borehole P1 is being prepared in the Neualbenreuth maar for paleoclimate and biological research. At each of these sites, a borehole broadband seismometer will be installed, and sites S1, S2 and S3 will also host a 3-D seismic array composed of a vertical geophone chain and surface seismic array. Seismic instrumenting has been completed in the S1 borehole and is in preparation in the remaining four monitoring boreholes. The continuous fluid monitoring site of Hartoušov includes three boreholes, F1, F2 and F3, and a pilot monitoring phase is underway. The laboratory also enables one to analyze microbial activity at CO2 mofettes and maar structures in the context of changes in habitats. The drillings into the maar volcanoes contribute to a better understanding of the Quaternary paleoclimate and volcanic activity.
Lithium and boron are trace components of magmas, released during exsolution of a gas phase during volcanic activity.
In this study, we determine the diffusivity and isotopic fractionation of Li and B in hydrous silicate melts.
Two glasses were synthesized with the same rhyolitic composition (4.2 wt% water), having different Li and B contents; these were studied in diffusion-couple experiments that were performed using an internally heated pressure vessel, operated at 300 MPa in the temperature range 700-1250 degrees C for durations from 0 s to 24 h. From this we determined activation energies for Li and B diffusion of 57 +/- 4 kJ/mol and 152 +/- 15 kJ/mol with pre-exponential factors of 1.53 x 10(-7) m(2)/s and 3.80 x 10(-8) m(2)/s, respectively.
Lithium isotopic fractionation during diffusion gave beta values between 0.15 and 0.20, whereas B showed no clear isotopic fractionation.
Our Li diffusivities and isotopic fractionation results differ somewhat from earlier published values, but overall confirm that Li diffusivity increases with water content. Our results on B diffusion show that similarly to Li, B mobility increases in the presence of water.
By applying the Eyring relation, we confirm that B diffusivity is limited by viscous flow in silicate melts.
Our results on Li and B diffusion present a new tool for understanding degassing-related processes, offering a potential geospeedometer to measure volcanic ascent rates.
Data recorded by distributed acoustic sensing (DAS) along an optical fibre sample the spatial and temporal properties of seismic wavefields at high spatial density. Often leading to massive amount of data when collected for seismic monitoring along many kilometre long cables. The spatially coherent signals from weak seismic arrivals within the data are often obscured by incoherent noise. We present a flexible and computationally efficient filtering technique, which makes use of the dense spatial and temporal sampling of the data and that can handle the large amount of data. The presented adaptive frequency-wavenumber filter suppresses the incoherent seismic noise while amplifying the coherent wavefield. We analyse the response of the filter in time and spectral domain, and we demonstrate its performance on a noisy data set that was recorded in a vertical borehole observatory showing active and passive seismic phase arrivals. Lastly, we present a performant open-source software implementation enabling real-time filtering of large DAS data sets.
A review of source models to further the understanding of the seismicity of the Groningen field
(2022)
The occurrence of felt earthquakes due to gas production in Groningen has initiated numerous studies and model attempts to understand and quantify induced seismicity in this region. The whole bandwidth of available models spans the range from fully deterministic models to purely empirical and stochastic models. In this article, we summarise the most important model approaches, describing their main achievements and limitations. In addition, we discuss remaining open questions and potential future directions of development.
The new in situ geodynamic laboratory established in the framework of the ICDP Eger project aims to develop the most modern, comprehensive, multiparameter laboratory at depth for studying earthquake swarms, crustal fluid flow, mantle-derived CO2 and helium degassing, and processes of the deep biosphere. In order to reach a new level of high-frequency, near-source and multiparameter observation of earthquake swarms and related phenomena, such a laboratory comprises a set of shallow boreholes with high-frequency 3-D seismic arrays as well as modern continuous real-time fluid monitoring at depth and the study of the deep biosphere.
This laboratory is located in the western part of the Eger Rift at the border of the Czech Republic and Germany (in the West Bohemia-Vogtland geodynamic region) and comprises a set of five boreholes around the seismoactive zone. To date, all monitoring boreholes have been drilled. This includes the seismic monitoring boreholes S1, S2 and S3 in the crystalline units north and east of the major Novy Kostel seismogenic zone, borehole F3 in the Hartousov mofette field and borehole S4 in the newly discovered Bazina maar near Liba. Supplementary borehole P1 is being prepared in the Neualbenreuth maar for paleoclimate and biological research. At each of these sites, a borehole broadband seismometer will be installed, and sites S1, S2 and S3 will also host a 3-D seismic array composed of a vertical geophone chain and surface seismic array. Seismic instrumenting has been completed in the S1 borehole and is in preparation in the remaining four monitoring boreholes. The continuous fluid monitoring site of Hartousov includes three boreholes, F1, F2 and F3, and a pilot monitoring phase is underway. The laboratory also enables one to analyze microbial activity at CO2 mofettes and maar structures in the context of changes in habitats. The drillings into the maar volcanoes contribute to a better understanding of the Quaternary paleoclimate and volcanic activity.
Effect of temperature on the densification of silicate melts to lower earth's mantle conditions
(2022)
Physical properties of silicate melts play a key role for global planetary dynamics, controlling for example volcanic eruption styles, mantle convection and elemental cycling in the deep Earth. They are significantly modified by structural changes at the atomic scale due to external parameters such as pressure and temperature or due to chemistry. Structural rearrangements such as 4- to 6-fold coordination change of Si with increasing depth may profoundly influence melt properties, but have so far mostly been studied at ambient temperature due to experimental difficulties. In order to investigate the structural properties of silicate melts and their densification mechanisms at conditions relevant to the deep Earth's interior, we studied haplo basaltic glasses and melts (albite-diopside composition) at high pressure and temperature conditions in resistively and laser-heated diamond anvil cells using X-ray absorption near edge structure spectroscopy. Samples were doped with 10 wt% of Ge, which is accessible with this experimental technique and which commonly serves as a structural analogue for the network forming cation Si. We acquired spectra on the Ge K edge up to 48 GPa and 5000 K and derived the average Ge-O coordination number NGe-O, and bond distance RGe-O as functions of pressure. Our results demonstrate a continuous transformation from tetrahedral to octahedral coordination between ca. 5 and 30 GPa at ambient temperature. Above 1600 K the data reveal a reduction of the pressure needed to complete conversion to octahedral coordination by ca. 30 %. The results allow us to determine the influence of temperature on the Si coordination number changes in natural melts in the Earth's interior. We propose that the complete transition to octahedral coordination in basaltic melts is reached at about 40 GPa, corresponding to a depth of ca. 1200 km in the uppermost lower mantle. At the core-mantle boundary (2900 km, 130 GPa, 3000 K) the existence of non-buoyant melts has been proposed to explain observed low seismic wave velocity features. Our results highlight that the melt composition can affect the melt density at such extreme conditions and may strongly influence the structural response.
The creation of building exposure models for seismic risk assessment is frequently challenging due to the lack of availability of detailed information on building structures. Different strategies have been developed in recent years to overcome this, including the use of census data, remote sensing imagery and volunteered graphic information (VGI). This paper presents the development of a building-by-building exposure model based exclusively on openly available datasets, including both VGI and census statistics, which are defined at different levels of spatial resolution and for different moments in time. The initial model stemming purely from building-level data is enriched with statistics aggregated at the neighbourhood and city level by means of a Monte Carlo simulation that enables the generation of full realisations of damage estimates when using the exposure model in the context of an earthquake scenario calculation. Though applicable to any other region of interest where analogous datasets are available, the workflow and approach followed are explained by focusing on the case of the German city of Cologne, for which a scenario earthquake is defined and the potential damage is calculated. The resulting exposure model and damage estimates are presented, and it is shown that the latter are broadly consistent with damage data from the 1978 Albstadt earthquake, notwithstanding the differences in the scenario. Through this real-world application we demonstrate the potential of VGI and open data to be used for exposure modelling for natural risk assessment, when combined with suitable knowledge on building fragility and accounting for the inherent uncertainties.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Enhanced geothermal systems (EGS) are considered a cornerstone of future sustainable energy production. In such systems, high-pressure fluid injections break the rock to provide pathways for water to circulate in and heat up. This approach inherently induces small seismic events that, in rare cases, are felt or can even cause damage. Controlling and reducing the seismic impact of EGS is crucial for a broader public acceptance. To evaluate the applicability of hydraulic fracturing (HF) in EGS and to improve the understanding of fracturing processes and the hydromechanical relation to induced seismicity, six in-situ, meter-scale HF experiments with different injection schemes were performed under controlled conditions in crystalline rock in a depth of 410 m at the Äspö Hard Rock Laboratory (Sweden).
I developed a semi-automated, full-waveform-based detection, classification, and location workflow to extract and characterize the acoustic emission (AE) activity from the continuous recordings of 11 piezoelectric AE sensors. Based on the resulting catalog of 20,000 AEs, with rupture sizes of cm to dm, I mapped and characterized the fracture growth in great detail. The injection using a novel cyclic injection scheme (HF3) had a lower seismic impact than the conventional injections. HF3 induced fewer AEs with a reduced maximum magnitude and significantly larger b-values, implying a decreased number of large events relative to the number of small ones. Furthermore, HF3 showed an increased fracture complexity with multiple fractures or a fracture network. In contrast, the conventional injections developed single, planar fracture zones (Publication 1).
An independent, complementary approach based on a comparison of modeled and observed tilt exploits transient long-period signals recorded at the horizontal components of two broad-band seismometers a few tens of meters apart from the injections. It validated the efficient creation of hydraulic fractures and verified the AE-based fracture geometries. The innovative joint analysis of AEs and tilt signals revealed different phases of the fracturing process, including the (re-)opening, growth, and aftergrowth of fractures, and provided evidence for the reactivation of a preexisting fault in one of the experiments (Publication 2). A newly developed network-based waveform-similarity analysis applied to the massive AE activity supports the latter finding.
To validate whether the reduction of the seismic impact as observed for the cyclic injection schemes during the Äspö mine-scale experiments is transferable to other scales, I additionally calculated energy budgets for injection experiments from previously conducted laboratory tests and from a field application. Across all three scales, the cyclic injections reduce the seismic impact, as depicted by smaller maximum magnitudes, larger b-values, and decreased injection efficiencies (Publication 3).
The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 ± 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 ± 0.2 ka recurrence time for Mw~7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.
Seismology, like many scientific fields, e.g., music information retrieval and speech signal pro- cessing, is experiencing exponential growth in the amount of data acquired by modern seismo- logical networks. In this thesis, I take advantage of the opportunities offered by "big data" and by the methods developed in the areas of music information retrieval and machine learning to predict better the ground motion generated by earthquakes and to study the properties of the surface layers of the Earth. In order to better predict seismic ground motions, I propose two approaches based on unsupervised deep learning methods, an autoencoder network and Generative Adversarial Networks. The autoencoder technique explores a massive amount of ground motion data, evaluates the required parameters, and generates synthetic ground motion data in the Fourier amplitude spectra (FAS) domain. This method is tested on two synthetic datasets and one real dataset. The application on the real dataset shows that the substantial information contained within the FAS data can be encoded to a four to the five-dimensional manifold. Consequently, only a few independent parameters are required for efficient ground motion prediction. I also propose a method based on Conditional Generative Adversarial Networks (CGAN) for simulating ground motion records in the time-frequency and time domains. CGAN generates the time-frequency domains based on the parameters: magnitude, distance, and shear wave velocities to 30 m depth (VS30). After generating the amplitude of the time-frequency domains using the CGAN model, instead of classical conventional methods that assume the amplitude spectra with a random phase spectrum, the phase of the time-frequency domains is recovered by minimizing the observed and reconstructed spectrograms. In the second part of this dissertation, I propose two methods for the monitoring and characterization of near-surface materials and site effect analyses. I implement an autocorrelation function and an interferometry method to monitor the velocity changes of near-surface materials resulting from the Kumamoto earthquake sequence (Japan, 2016). The observed seismic velocity changes during the strong shaking are due to the non-linear response of the near-surface materials. The results show that the velocity changes lasted for about two months after the Kumamoto mainshock. Furthermore, I used the velocity changes to evaluate the in-situ strain-stress relationship. I also propose a method for assessing the site proxy "VS30" using non-invasive analysis. In the proposed method, a dispersion curve of surface waves is inverted to estimate the shear wave velocity of the subsurface. This method is based on the Dix-like linear operators, which relate the shear wave velocity to the phase velocity. The proposed method is fast, efficient, and stable. All of the methods presented in this work can be used for processing "big data" in seismology and for the analysis of weak and strong ground motion data, to predict ground shaking, and to analyze site responses by considering potential time dependencies and nonlinearities.
Volcano-seismic signals such as long-period events and tremor are important indicators for volcanic activity and unrest. However, their wavefield is complex and characterization and location using traditional seismological instrumentation is often difficult.
In 2019 we recorded the full seismic wavefield using a newly developed 3C rotational sensor co-located with a 3C traditional seismometer on Etna, Italy. We compare the performance of the rotational sensor, the seismometer and the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) seismic network with respect to the analysis of complex volcano-seismic signals. We create event catalogs for volcano-tectonic (VT) and long-period (LP) events combining a STA/LTA algorithm and cross-correlations.
The event detection based on the rotational sensor is as reliable as the seismometer-based detection. The LP events are dominated by SH-type waves. Derived SH phase velocities range from 500 to 1,000 m/s for LP events and 300-400 m/s for volcanic tremor. SH-waves compose the tremor during weak volcanic activity and SH- and SV-waves during sustained strombolian activity.
We derive back azimuths using (a) horizontal rotational components and (b) vertical rotation rate and transverse acceleration. The estimated back azimuths are consistent with the INGV-OE event location for (a) VT events with an epicentral distance larger than 3 km and some closer events, (b) LP events and tremor in the main crater area. Measuring the full wavefield we can reliably analyze the back azimuths, phase velocities and wavefield composition for VT, LP events and tremor in regions that are difficult to access such as volcanoes.
Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological-meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure.
Purpose:
Soil erosion by water yields sediment to surface reservoirs, reducing their storage capacities, changing their geometry, and degrading water quality. Sediment reuse, i.e., fertilization of agricultural soils with the nutrient-enriched sediment from reservoirs, has been proposed as a recovery strategy. However, the sediment needs to meet certain criteria. In this study, we characterize sediments from the densely dammed semiarid Northeast Brazil by VNIR-SWIR spectroscopy and assess the effect of spectral resolution and spatial scale on the accuracy of N, P, K, C, electrical conductivity, and clay prediction models.
Methods
Sediment was collected in 10 empty reservoirs, and physical and chemical laboratory analyses as well as spectral measurements were performed. The spectra, initially measured at 1 nm spectral resolution, were resampled to 5 and 10 nm, and samples were analysed for both high and low spectral resolution at three spatial scales, namely (1) reservoir, (2) catchment, and (3) regional scale.
Results
Partial least square regressions performed from good to very good in the prediction of clay and electrical conductivity from reservoir (<40 km(2)) to regional (82,500 km(2)) scales. Models for C and N performed satisfactorily at the reservoir scale, but degraded to unsatisfactory at the other scales. Models for P and K were more unstable and performed from unsatisfactorily to satisfactorily at all scales. Coarsening spectral resolution by up to 10 nm only slightly degrades the models' performance, indicating the potential of characterizing sediment from spectral data captured at lower resolutions, such as by hyperspectral satellite sensors.
Conclusion:
By reducing the costly and time-consuming laboratory analyses, the method helps to promote the sediment reuse as a practice of soil and water conservation.
The Walker Circulation (WC) is an east-west trending band of atmospheric circulation cells along the equator and the predominant controller of heat and moisture transport in the tropics. Its variability is closely linked to the sea-surface temperature (SST) changes across the Pacific, the Indian and the Atlantic Oceans and can have pronounced effects on the humidity regimes of the adjacent continents. In recent years, the evolution of the WC during the Plioand Pleistocene epochs has been intensely studied in the context of the effectiveness of the tropics in modulating global climate change (e.g., the intensification of Northern Hemisphere glaciation). However, the onset of the modern WC pattern as well as its global impact during the Plioand Pleistocene is controversially assessed in the literature. For its onset, previous studies have suggested dates ranging between 2.4 and 0.8 million years ago (Myr), while its argued impact ranges from crucially influencing the increase of Northern Hemisphere ice sheet growth by channelling heat and moisture from the tropics into the high latitudes to having no effect on global ice volume changes. In order to achieve a comprehensive understanding of the spatiotemporal evolution of the WC during this time frame, we statistically analysed 30 globally distributed SST records covering the low and high latitudes between 3.5 and 1.5 Myr, encompassing the Late Pliocene to Early Pleistocene. We utilized a statistical change-point regression model to determine significant change points in the SST evolution of the (sub)-tropics and high latitudes that potentially relate to changes in the WC. We find that the WC experienced a multifaceted evolution between the Late Pliocene and the Early Pleistocene with significant transitional steps at-2.7 and-2.1 Ma. Our results suggest after the Late Pliocene, a pre-modern WC set in, which was characterized by a progressively strengthened Pacific Walker Cell alongside a weakened Indian Ocean Walker Cell. This change was potentially triggered by the constriction of the Indonesian seaway, an important transmitter between the Pacific and Indian Ocean. The ensuing mode of the WC intensified until-2.1 Myr, when SST values around the global scale signalled a progressive strengthening of the Indian Walker Cell in phase with the progressive strengthening of the Pacific and Atlantic Cells. Our findings indicate that a shift from a pre-modern to a modern-like WC potentially only occurred during the mid-Pleistocene.
The Arctic is rich in aquatic systems and experiences rapid warming due to climate change. The accelerated warming causes permafrost thaw and the mobilization of organic carbon.
When dissolved organic carbon is mobilized, this DOC can be transported to aquatic systems and degraded in the water bodies and further downstream. Here, we analyze the influence of different landscape components on DOC concentrations and export in a small (6.45 km(2)) stream catchment in the Lena River Delta.
The catchment includes lakes and ponds, with the flow path from Pleistocene yedoma deposits across Holocene non-yedoma deposits to the river outlet. In addition to DOC concentrations, we use radiocarbon dating of DOC as well as stable oxygen and hydrogen isotopes (delta O-18 and delta D) to assess the origin of DOC.
We find significantly higher DOC concentrations in the Pleistocene yedoma area of the catchment compared to the Holocene non-yedoma area with medians of 5 and 4.5 mg L-1 (p < 0.05), respectively. When yedoma thaw streams with high DOC concentration reach a large yedoma thermokarst lake, we observe an abrupt decrease in DOC concentration, which we attribute to dilution and lake processes such as mineralization. The DOC ages in the large thermokarst lake (between 3,428 and 3,637 C-14 y BP) can be attributed to a mixing of mobilized old yedoma and Holocene carbon.
Further downstream after the large thermokarst lake, we find progressively younger DOC ages in the stream water to its mouth, paired with decreasing DOC concentrations. This process could result from dilution with leaching water from Holocene deposits and/or emission of ancient yedoma carbon to the atmosphere. Our study shows that thermokarst lakes and ponds may act as DOC filters, predominantly by diluting incoming waters of higher DOC concentrations or by re-mineralizing DOC to CO2 and CH4.
Nevertheless, our results also confirm that the small catchment still contributes DOC on the order of 1.2 kg km(-2) per day from a permafrost landscape with ice-rich yedoma deposits to the Lena River.
Ground motion with strong-velocity pulses can cause significant damage to buildings and structures at certain periods; hence, knowing the period and velocity amplitude of such pulses is critical for earthquake structural engineering.
However, the physical factors relating the scaling of pulse periods with magnitude are poorly understood.
In this study, we investigate moderate but damaging earthquakes (M-w 6-7) and characterize ground- motion pulses using the method of Shahi and Baker (2014) while considering the potential static-offset effects.
We confirm that the within-event variability of the pulses is large. The identified pulses in this study are mostly from strike-slip-like earthquakes. We further perform simulations using the freq uency-wavenumber algorithm to investigate the causes of the variability of the pulse periods within and between events for moderate strike-slip earthquakes.
We test the effect of fault dips, and the impact of the asperity locations and sizes. The simulations reveal that the asperity properties have a high impact on the pulse periods and amplitudes at nearby stations.
Our results emphasize the importance of asperity characteristics, in addition to earthquake magnitudes for the occurrence and properties of pulses produced by the forward directivity effect.
We finally quantify and discuss within- and between-event variabilities of pulse properties at short distances.
It is widely recognized that collisional mountain belt topography is generated by crustal thickening and lowered by river bedrock erosion, linking climate and tectonics(1-4). However, whether surface processes or lithospheric strength control mountain belt height, shape and longevity remains uncertain. Additionally, how to reconcile high erosion rates in some active orogens with long-term survival of mountain belts for hundreds of millions of years remains enigmatic. Here we investigate mountain belt growth and decay using a new coupled surface process(5,6) and mantle-scale tectonic model(7). End-member models and the new non-dimensional Beaumont number, Bm, quantify how surface processes and tectonics control the topographic evolution of mountain belts, and enable the definition of three end-member types of growing orogens: type 1, non-steady state, strength controlled (Bm > 0.5); type 2, flux steady state(8), strength controlled (Bm approximate to 0.4-0.5); and type 3, flux steady state, erosion controlled (Bm < 0.4). Our results indicate that tectonics dominate in Himalaya-Tibet and the Central Andes (both type 1), efficient surface processes balance high convergence rates in Taiwan (probably type 2) and surface processes dominate in the Southern Alps of New Zealand (type 3). Orogenic decay is determined by erosional efficiency and can be subdivided into two phases with variable isostatic rebound characteristics and associated timescales. The results presented here provide a unified framework explaining how surface processes and lithospheric strength control the height, shape, and longevity of mountain belts.
The 100 km wide Merida Andes extend from the Colombian/Venezuelan border to the Coastal Cordillera. The mountain chain and its associated major strike-slip fault systems in western Venezuela formed due to oblique convergence of the Caribbean with the South American Plates and the north-eastwards expulsion of the North Andean Block. Due to the limited knowledge of lithospheric structures related to the formation of the Merida Andes research projects have been developed to illuminate this zone with deep geophysical data. In this study, we present three-dimensional inversion of broadband magnetotelluric data, collected along a 240 km long profile crossing the Merida Andes and the Maracaibo and Barinas-Apure foreland basins. The distribution of the stations limits resolution of the model to off-profile features. Combining 3D inversion of synthetic data sets derived from 3D modelling with 3D inversion of measured data, we could derive a 10 to 15 km wide corridor with good lateral resolution to develop hypotheses about the origin of deep-reaching anomalies of high electrical conductivity. The Merida Andes appear generally as electrically resistive structures, separated by anomalies associated with the most important fault systems of the region, the Bocono and Valera faults. Sensitivity tests suggest that the Valera Fault reaches to depths of up to 12 km and the Bocono Fault to more than 35 km depth. Both structures are connected to a sizeable conductor located east of the profile at 12-15 km depth. We propose that the high conductivity associated with this off-profile conductor may be related to the detachment of the Trujillo Block. We also identified a conductive zone that correlates spatially with the location of a gravity low, possibly representing a SE tilt of the Maracaibo Triangular Block under the mountain chain to great depths (>30 km). The relevance of these tectonic blocks in our models at crustal depths seems to be consistent with proposed theories that describe the geodynamics of western Venezuela as dominated by floating blocks or orogens. Our results stress the importance of the Trujillo Block for the current tectonic evolution of western Venezuela and confirm the relevance of the Bocono Fault carrying deformation to the lower crust and upper mantle. The Barinas-Apure and the Maracaibo sedimentary basins are imaged as electrically conductive with depths of 4 to 5 km and 5 to 10 km, respectively. The Barinas-Apure basin is imaged as a simple 1D structure, in contrast to the Maracaibo Basin, where a series of conductive and resistive bodies could be related to active deformation causing the juxtaposition of older geological formations and younger basin sediments.
Modern pollen-vegetation-climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen-vegetation-climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.
Although phytoliths are recognized as an important proxy for paleoenvironmental reconstruction, the quantitative relationship between phytoliths and climate is still debated. In order to provide an improved basis for phytolith-based paleoclimate reconstructions, a representative modern phytolith dataset is essential. Here, we synthesize a modern topsoil phytolith dataset for Northeast China, analyze its climatic significance, and apply it to a fossil phytolith series from the Hani peat core in Northeast China. The dataset comprises 660 topsoil phytolith assemblages from 289 sample sites. We compiled modern meteorological data to assess the quantitative relationship between the phytolith assemblages and climatic variables. Detrended correspondence analysis (DCA) and Redundancy analysis (RDA) were used to determine the dominant climatic variable influencing the phytolith distributions. The results showed that mean annual temperature (MAT) is the dominant variable controlling the spatial distribution of phytoliths, accounting for 8.91% of the total variance. Transfer function based on inverse deshrinking locally-weighted weighted averaging (LWWA_Inv) was developed for MAT (R-_boot(2) = 0.86, RMSEP = 1.02 degrees C). Applying the LWWA_Inv transfer function to fossil phytolith records from the Hani peat core enables quantitative inferences to be made about Holocene climate changes in Northeast China. Overall, combined with the LWWA_Inv method, the topsoil phytolith dataset of Northeast China can be used for reliable quantitative MAT reconstruction.
Van Allen Probes measurements revealed the presence of the most unusual structures in the ultra-relativistic radiation belts. Detailed modeling, analysis of pitch angle distributions, analysis of the difference between relativistic and ultra-realistic electron evolution, along with theoretical studies of the scattering and wave growth, all indicate that electromagnetic ion cyclotron (EMIC) waves can produce a very efficient loss of the ultra-relativistic electrons in the heart of the radiation belts. Moreover, a detailed analysis of the profiles of phase space densities provides direct evidence for localized loss by EMIC waves. The evolution of multi-MeV fluxes shows dramatic and very sudden enhancements of electrons for selected storms. Analysis of phase space density profiles reveals that growing peaks at different values of the first invariant are formed at approximately the same radial distance from the Earth and show the sequential formation of the peaks from lower to higher energies, indicating that local energy diffusion is the dominant source of the acceleration from MeV to multi-MeV energies. Further simultaneous analysis of the background density and ultra-relativistic electron fluxes shows that the acceleration to multi-MeV energies only occurs when plasma density is significantly depleted outside of the plasmasphere, which is consistent with the modeling of acceleration due to chorus waves.
Fast-localized electron loss, resulting from interactions with electromagnetic ion cyclotron (EMIC) waves, can produce deepening minima in phase space density (PSD) radial profiles. Here, we perform a statistical analysis of local PSD minima to quantify how readily these are associated with radiation belt depletions. The statistics of PSD minima observed over a year are compared to the Versatile Electron Radiation Belts (VERB) simulations, both including and excluding EMIC waves. The observed minima distribution can only be achieved in the simulation including EMIC waves, indicating their importance in the dynamics of the radiation belts. By analyzing electron flux depletions in conjunction with the observed PSD minima, we show that, in the heart of the outer radiation belt (L* < 5), on average, 53% of multi-MeV electron depletions are associated with PSD minima, demonstrating that fast localized loss by interactions with EMIC waves are a common and crucial process for ultra-relativistic electron populations.
We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 ± 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 ± 0.2 ka recurrence time for Mw~7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.
As the recent permafrost thawing of northern Asia proceeds due to anthropogenic climate change, precise and detailed palaeoecological records from past warm periods are essential to anticipate the extent of future permafrost variations. Here, based on the modern relationship between permafrost and vegetation (represented by pollen assemblages), we trained a Random Forest model using pollen and permafrost data and verified its reliability to reconstruct the history of permafrost in northern Asia during the Holocene. An early Holocene (12-8 cal ka BP) strong thawing trend, a middle-to-late Holocene (8-2 cal ka BP) relatively slow thawing trend, and a late Holocene freezing trend of permafrost in northern Asia are consistent with climatic proxies such as summer solar radiation and Northern Hemisphere temperature. The extensive distribution of permafrost in northern Asia inhibited the spread of evergreen coniferous trees during the early Holocene warming and might have decelerated the enhancement of the East Asian summer monsoon (EASM) by altering hydrological processes and albedo. Based on these findings, we suggest that studies of the EASM should consider more the state of permafrost and vegetation in northern Asia, which are often overlooked and may have a profound impact on climate change in this region.
Reconstructing thermal histories in thrust belts is commonly used to infer the age and rates of thrusting and hence the driving mechanisms of orogenesis.
In areas where ancient basins have been incorporated into the orogenic wedge, a quantitative reconstruction of the thermal history helps distinguish among potential mechanisms responsible for heating events.
We present such a reconstruction for the Ischigualasto-Villa Union basin in the western Pampean Ranges of Argentina, where Triassic rifting and late Cretaceous-Cenozoic retroarc foreland basin development has been widely documented, including Miocene flat-slab subduction.
We report results of organic and inorganic thermal indicators acquired along three stratigraphic sections, including vitrinite reflectance and X-ray diffractometry in claystones and new thermochronological [(apatite fission-track and apatite and zircon [U-Th]/He)] analyses.
Despite up to 5 km-thick Cenozoic overburden and unlike previously thought, the thermal peak in the basin is not due to Cenozoic burial but occurred in the Triassic, associated with a high heat flow of up to 90 mWm(-2) and <2 km of burial, which heated the base of the Triassic strata to similar to 160 degrees C. Following exhumation, attested by the development of an unconformity between the Triassic and Late-Cretaceous-Cenozoic sequences, Cenozoic re-burial increased the temperature to similar to 110 degrees C at the base of the Triassic section and only similar to 50 degrees C 7 km upsection, suggesting a dramatic decrease in the thermal gradient.
The onset of Cenozoic cooling occurred at similar to 10(-8) Ma, concomitant with sediment accumulation and thus preceding the latest Miocene onset of thrusting that has been independently documented by stratigraphic-cross-cutting relationships.
We argue that the onset of cooling is associated with lithospheric refrigeration following establishment of flat-slab subduction, leading to the eastward displacement of the asthenospheric wedge beneath the South American plate.
Our study places time and temperature constraints on flat-slab cooling that calls for a careful interpretation of exhumation signals in thrustbelts inferred from thermochronology only.
The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen-evergreen transition zone in Central Yakutia and the tundra-taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, ). The dataset includes structure-from-motion (SfM) point clouds and red-green-blue (RGB) and red-green-near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, ). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch ( and ) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, ). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species. Larix gmeliniiLarix cajanderiDataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, ). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. <br /> The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra-taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.
Increasing arctic coastal erosion rates imply a greater release of sediments and organic matter into the coastal zone. With 213 sediment samples taken around Herschel Island-Qikiqtaruk, Canadian Beaufort Sea, we aimed to gain new insights on sediment dynamics and geochemical properties of a shallow arctic nearshore zone. Spatial characteristics of nearshore sediment texture (moderately to poorly sorted silt) are dictated by hydrodynamic processes, but ice-related processes also play a role. We determined organic matter (OM) distribution and inferred the origin and quality of organic carbon by C/N ratios and stable carbon isotopes delta C-13. The carbon content was higher offshore and in sheltered areas (mean: 1.0 wt.%., S.D.: 0.9) and the C/N ratios also showed a similar spatial pattern (mean: 11.1, S.D.: 3.1), while the delta C-13 (mean: -26.4 parts per thousand VPDB, S.D.: 0.4) distribution was more complex. We compared the geochemical parameters of our study with terrestrial and marine samples from other studies using a bootstrap approach. Sediments of the current study contained 6.5 times and 1.8 times less total organic carbon than undisturbed and disturbed terrestrial sediments, respectively. Therefore, degradation of OM and separation of carbon pools take place on land and continue in the nearshore zone, where OM is leached, mineralized, or transported beyond the study area.
Boreal forests cover over half of the global permafrost area and protect underlying permafrost. Boreal forest development, therefore, has an impact on permafrost evolution, especially under a warming climate.
Forest disturbances and changing climate conditions cause vegetation shifts and potentially destabilize the carbon stored within the vegetation and permafrost. Disturbed permafrost-forest ecosystems can develop into a dry or swampy bush- or grasslands, shift toward broadleaf- or evergreen needleleaf-dominated forests, or recover to the pre-disturbance state.
An increase in the number and intensity of fires, as well as intensified logging activities, could lead to a partial or complete ecosystem and permafrost degradation. We study the impact of forest disturbances (logging, surface, and canopy fires) on the thermal and hydrological permafrost conditions and ecosystem resilience.
We use a dynamic multilayer canopy-permafrost model to simulate different scenarios at a study site in eastern Siberia. We implement expected mortality, defoliation, and ground surface changes and analyze the interplay between forest recovery and permafrost. We find that forest loss induces soil drying of up to 44%, leading to lower active layer thicknesses and abrupt or steady decline of a larch forest, depending on disturbance intensity.
Only after surface fires, the most common disturbances, inducing low mortality rates, forests can recover and overpass pre-disturbance leaf area index values. We find that the trajectory of larch forests after surface fires is dependent on the precipitation conditions in the years after the disturbance. Dryer years can drastically change the direction of the larch forest development within the studied period.
LegacyPollen 1.0
(2022)
Here we describe the LegacyPollen 1.0, a dataset of 2831 fossil pollen records with metadata, a harmonized taxonomy, and standardized chronologies.
A total of 1032 records originate from North America, 1075 from Europe, 488 from Asia, 150 from Latin America, 54 from Africa, and 32 from the Indo-Pacific.
The pollen data cover the late Quaternary (mostly the Holocene). The original 10 110 pollen taxa names (including variations in the notations) were harmonized to 1002 terrestrial taxa (including Cyperaceae), with woody taxa and major herbaceous taxa harmonized to genus level and other herbaceous taxa to family level.
The dataset is valuable for synthesis studies of, for example, taxa areal changes, vegetation dynamics, human impacts (e.g., deforestation), and climate change at global or continental scales.
The harmonized pollen and metadata as well as the harmonization table are available from PANGAEA (https://doi.org/10.1594/PANGAEA.929773; Herzschuh et al., 2021). R code for the harmonization is provided at Zenodo (https://doi.org/10.5281/zenodo.5910972; Herzschuh et al., 2022) so that datasets at a customized harmonization level can be easily established.
Wildfires play an essential role in the ecology of boreal forests.
In eastern Siberia, fire activity has been increasing in recent years, challenging the livelihoods of local communities. Intensifying fire regimes also increase disturbance pressure on the boreal forests, which currently protect the permafrost beneath from accelerated degradation.
However, long-term relationships between changes in fire regime and forest structure remain largely unknown.
We assess past fire-vegetation feedbacks using sedimentary proxy records from Lake Satagay, Central Yakutia, Siberia, covering the past c. 10,800 years.
Results from macroscopic and microscopic charcoal analyses indicate high amounts of burnt biomass during the Early Holocene, and that the present-day, low-severity surface fire regime has been in place since c. 4,500 years before present.
A pollen-based quantitative reconstruction of vegetation cover and a terrestrial plant record based on sedimentary ancient DNA metabarcoding suggest a pronounced shift in forest structure toward the Late Holocene.
Whereas the Early Holocene was characterized by postglacial open larch-birch woodlands, forest structure changed toward the modern, mixed larch-dominated closed-canopy forest during the Mid-Holocene.
We propose a potential relationship between open woodlands and high amounts of burnt biomass, as well as a mediating effect of dense larch forest on the climate-driven intensification of fire regimes.
Considering the anticipated increase in forest disturbances (droughts, insect invasions, and wildfires), higher tree mortality may force the modern state of the forest to shift toward an open woodland state comparable to the Early Holocene.
Such a shift in forest structure may result in a positive feedback on currently intensifying wildfires.
These new long-term data improve our understanding of millennial-scale fire regime changes and their relationships to changes of vegetation in Central Yakutia, where the local population is already being confronted with intensifying wildfire seasons.
Through its magnetic activity, the Sun governs the conditions in Earth's vicinity, creating space weather events, which have drastic effects on our space- and ground-based technology.
One of the most important solar magnetic features creating the space weather is the solar wind that originates from the coronal holes (CHs).
The identification of the CHs on the Sun as one of the source regions of the solar wind is therefore crucial to achieve predictive capabilities.
In this study, we used an unsupervised machine-learning method, k-means, to pixel-wise cluster the passband images of the Sun taken by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory in 171, 193, and 211 angstrom in different combinations.
Our results show that the pixel-wise k-means clustering together with systematic pre- and postprocessing steps provides compatible results with those from complex methods, such as convolutional neural networks.
More importantly, our study shows that there is a need for a CH database where a consensus about the CH boundaries is reached by observers independently.
This database then can be used as the "ground truth," when using a supervised method or just to evaluate the goodness of the models.
Urban surface runoff management via best management practices (BMP) and low impact development (LID) has earned significant recognition owing to positive environmental and ecological impacts. However, due to the complexity of the parameters involved, the estimation of LID efficiency in attenuating the urban surface runoff at the watershed scale is challenging. A planning analysis of employing Green Roofs and Infiltration Trenches as BMPs/LIDs practices for urban surface runoff control is presented in this study. A multi-objective optimization decision-making framework is established by coupling SWMM (Storm Water Management Model) with NSGA-II models to check the performance of BMPs/LIDs concerning the cost-benefit analysis of LID at the watershed scale. Two urbanized areas belonging to Central Delhi in India were used as case studies. The results showed that the SWMM model is useful in simulating optimization problems for managing urban surface runoff. The optimum scenarios efficiently minimized the urban runoff volume while maintaining the BMPs/LIDs implementation costs and size. With BMPs/LIDs implementation, the reduction in runoff volume increases as expenses increase initially; however, there is no noticeable reduction in flood volume after a certain threshold. Contrasted with the haphazard arrangement of BMPs/LIDs, the proposed approach demonstrates 22%-24% runoff reductions for the same expenditures in watershed 1 and 23%-26% in watershed 2. The result of the study provides insights into planning and management of the urban surface runoff control with LID practices. The proposed framework assists the hydrologists in optimum selection and placements of BMPs/LIDs practices to acquire the most extreme ecological advantages with the least expenses.
We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES-15 measurements of 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling GOES-15 flux values and an upper boundary condition scaling factor (BF). The GOES-15 flux model utilizes an input and feedback delay of 2 and 2 time steps (i.e., 5 min time steps) with the most efficient number of hidden layers set to 10. Magnetic local time, Dst, Kp, solar wind dynamic pressure, AE, and solar wind velocity were found to perform as predicative indicators of GOES-15 flux and therefore were used as the exogenous inputs. The NARX-derived upper boundary condition scaling factor was used in conjunction with the Versatile Electron Radiation Belt (VERB) code to produce reconstructions of the radiation belts during the period of July-November 1990, independent of in-situ observations. Here, Kp was chosen as the sole exogenous input to be more compatible with the VERB code. This Combined Release and Radiation Effects Satellite-era reconstruction showcases the potential to use these neural network-derived boundary conditions as a method of hindcasting the historical radiation belts. This study serves as a companion paper to another recently published study on reconstructing the radiation belts during Solar Cycles 17-24 (Saikin et al., 2021, ), for which the results featured in this paper were used.
High pressure and high temperature experiments performed with laser-heated diamond anvil cells (LH-DAC) are being extensively used in geosciences to study matter at conditions prevailing in planetary interiors. Due to the size of the apparatus itself, the samples that are produced are extremely small, on the order of few tens of micrometers. There are several ways to analyze the samples and extract physical, chemical or structural information, using either in situ or ex situ methods. In this paper, we compare two nanoprobe techniques, namely nano-XRF and NanoSIMS, that can be used to analyze recovered samples synthetized in a LH-DAC. With these techniques, it is possible to extract the spatial distribution of chemical elements in the samples. We show the results for several standards and discuss the importance of proper calibration for the acquisition of quantifiable results. We used these two nanoprobe techniques to retrieve elemental ratios of dilute species (few tens of ppm) in quenched experimental molten samples relevant for the formation of the iron-rich core of the Earth. We finally discuss the applications of such probes to constrain the partitioning of trace elements between metal and silicate phases, with a focus on moderately siderophile elements, tungsten and molybdenum.
Extracting information about past tectonic or climatic environmental changes from sedimentary records is a key objective of provenance research. Interpreting the imprint of such changes remains challenging as signals might be altered in the sediment-routing system.
We investigate the sedimentary provenance of the Oligocene/Miocene Upper Austrian Northern Alpine Foreland Basin and its response to the tectonically driven exhumation of the Tauern Window metamorphic dome (28 +/- 1 Ma) in the Eastern European Alps by using the unprecedented combination of Nd isotopic composition of bulk-rock clay-sized samples and partly previously published multi-proxy (Nd isotopic composition, trace-element geochemistry, U-Pb dating) sand-sized apatite single-grain analysis.
The basin offers an excellent opportunity to investigate environmental signal propagation into the sedimentary record because comprehensive stratigraphic and seismic datasets can be combined with present research results. The bulk-rock clay-sized fraction epsilon Nd values of well-cutting samples from one well on the northern basin slope remained stable at similar to-9.7 from 27 to 19 Ma but increased after 19 Ma to similar to-9.1. In contrast, apatite single-grain distributions, which were extracted from 22 drill-core samples, changed significantly around 23.3 Ma from apatites dominantly from low-grade (<upper amphibolite-facies) metamorphic sources with Permo-Mesozoic and late Variscan U-Pb ages and epsilon Nd values of -4.4 to dominantly high-grade metamorphic apatites with late Variscan U-Pb ages and epsilon Nd values of -2.2.
The change in apatite single-grain distributions at 23.3 Ma is interpreted to result from the exposure of a new Upper Austroalpine source nappe with less negative epsilon Nd values triggered by the ongoing Tauern Window exhumation. Combining these data with the clay-sized bulk-rock epsilon Nd values reveals that the provenance changed 4-5 Myrs later at 19 Ma in the clay-sized fraction.
Reasons for the delayed provenance-change recording are rooted in the characteristics of the applied methods.
Whereas single-grain distributions of orogen-wide sediment-routing systems can be dominated by geographically small areas with high erosion and mineral fertility rates, bulk-rock methods integrate over the entire drainage basin, thus diminishing extreme values. Hence, by combining these two methods, spatial information are uncovered, enabling a previously unattained understanding of the underlying environmental change.
A 3-D crustal shear wave velocity model and Moho map below the Semail Ophiolite, eastern Arabia
(2022)
The Semail Ophiolite in eastern Arabia is the largest and best-exposed slice of oceanic lithosphere on land. Detailed knowledge of the tectonic evolution of the shallow crust, in particular during and after ophiolite obduction in Late Cretaceous times is contrasted by few constraints on physical and compositional properties of the middle and lower continental crust below the obducted units. The role of inherited, pre-obduction crustal architecture remains therefore unaccounted for in our understanding of crustal evolution and the present-day geology. Based on seismological data acquired during a 27-month campaign in northern Oman, Ambient Seismic Noise Tomography and Receiver Function analysis provide for the first time a 3-D radially anisotropic shear wave velocity (V-S) model and a consistent Moho map below the iconic Semail Ophiolite. The model highlights deep crustal boundaries that segment the eastern Arabian basement in two distinct units. The previously undescribed Western Jabal Akhdar Zone separates Arabian crust with typical continental properties and a thickness of similar to 40-45 km in the northwest from a compositionally different terrane in the southeast that is interpreted as a terrane accreted during the Pan-African orogeny in Neoproterozoic times. East of the Ibra Zone, another deep crustal boundary, crustal thickness decreases to 30-35 km and very high lower crustal V-S suggest large-scale mafic intrusions into, and possible underplating of the Arabian continental crust that occurred most likely during Permian breakup of Pangea. Mafic reworking is sharply bounded by the (upper crustal) Semail Gap Fault Zone, northwest of which no such high velocities are found in the crust. Topography of the Oman Mountains is supported by a mild crustal root and Moho depth below the highest topography, the Jabal Akhdar Dome, is similar to 42 km. Radial anisotropy is robustly resolved in the upper crust and aids in discriminating dipping allochthonous units from autochthonous sedimentary rocks that are indistinguishable by isotropic V-S alone. Lateral thickness variations of the ophiolite highlight the Haylayn Ophiolite Massif on the northern flank of Jabal Akhdar Dome and the Hawasina Window as the deepest reaching unit. Ophiolite thickness is similar to 10 km in the southern and northern massifs, and <= 5 km elsewhere.
The Kolumbo submarine volcano in the southern Aegean (Greece) is associated with repeated seismic unrest since at least two decades and the causes of this unrest are poorly understood. We present a ten-month long microseismicity data set for the period 2006-2007. The majority of earthquakes cluster in a cone-shaped portion of the crust below Kolumbo. The tip of this cone coincides with a low Vp-anomaly at 2-4 km depth, which is interpreted as a crustal melt reservoir. Our data set includes several earthquake swarms, of which we analyze the four with the highest events numbers in detail. Together the swarms form a zone of fracturing elongated in the SW-NE direction, parallel to major regional faults. All four swarms show a general upward migration of hypocenters and the cracking front propagates unusually fast, compared to swarms in other volcanic areas. We conclude that the swarm seismicity is most likely triggered by a combination of pore-pressure perturbations and the re-distribution of elastic stresses. Fluid pressure perturbations are induced likely by obstructions in the melt conduits in a rheologically strong layer between 6 and 9 km depth. We conclude that the zone of fractures below Kolumbo is exploited by melts ascending from the mantle and filling the crustal melt reservoir. Together with the recurring seismic unrest, our study suggests that a future eruption is probable and monitoring of the Kolumbo volcanic system is highly advisable.
Integrated Seismic Program (ISP) is a graphical user interface designed to facilitate and provide a user-friendly framework for performing diverse common and advanced tasks in seismological research. ISP is composed of five main modules for earthquake location, time-frequency analysis and advanced signal processing, implementation of array techniques to estimate the slowness vector, seismic moment tensor inversion, and receiver function computation and analysis. In addition, several support tools are available, allowing the user to create an event database, download data from International Federation of Digital Seismograph Networks services, inspect the background noise, and compute synthetic seismograms. ISP is written in Python3, supported by several open-source and/or publicly available tools. Its modular design allows for new features to be added in a collaborative development environment.
The role of biogenic carbonate producers in the evolution of the geometries of carbonate systems has been the subject of numerous research projects. Attempts to classify modern and ancient carbonate systems by their biotic components have led to the discrimination of biogenic carbonate producers broadly into Photozoans, which are characterised by an affinity for warm tropical waters and high dependence on light penetration, and Heterozoans which are generally associated with both cool water environments and nutrient-rich settings with little to no light penetration. These broad categories of carbonate sediment producers have also been recognised to dominate in specific carbonate systems. Photozoans are commonly dominant in flat-topped platforms with steep margins, while Heterozoans generally dominate carbonate ramps. However, comparatively little is known on how these two main groups of carbonate producers interact in the same system and impact depositional geometries responding to changes in environmental conditions such as sea level fluctuation, antecedent slope, sediment transport processes, etc. This thesis presents numerical models to investigate the evolution of Miocene carbonate systems in the Mediterranean from two shallow marine domains: 1) a Miocene flat-topped platform dominated by Photozoans, with a significant component of Hetrozoans in the slope and 2) a Heterozoan distally steepened ramp, with seagrass-influenced (Photozoan) inner ramp. The overarching aim of the three articles comprising this cumulative thesis is to provide a numerical study of the role of Photozoans and Heterozoans in the evolution of carbonate system geometries and how these biotas respond to changes in environmental conditions. This aim was achieved using stratigraphic forward modelling, which provides an approach to quantitatively integrate multi-scale datasets to reconstruct sedimentary processes and products during the evolution of a sedimentary system.
In a Photozoan-dominated carbonate system, such as the Miocene Llucmajor platform in Western Mediterranean, stratigraphic forward modelling dovetailed with a robust set of sensitivity tests reveal how the geometry of the carbonate system is determined by the complex interaction of Heterozoan and Photozoan biotas in response to variable conditions of sea level fluctuation, substrate configuration, sediment transport processes and the dominance of Photozoan over Heterozoan production. This study provides an enhanced understanding of the different carbonate systems that are possible under different ecological and hydrodynamic conditions. The research also gives insight into the roles of different biotic associations in the evolution of carbonate geometries through time and space. The results further show that the main driver of platform progradation in a Llucmajor-type system is the lowstand production of Heterozoan sediments, which form the necessary substratum for Photozoan production.
In Heterozoan systems, sediment production is mainly characterised by high transport deposits, that are prone to redistribution by waves and gravity, thereby precluding the development of steep margins. However, in the Menorca ramp, the occurrence of sediment trapping by seagrass led to the evolution of distal slope steepening. We investigated, through numerical modelling, how such a seagrass-influenced ramp responds to the frequency and amplitude of sea level changes, variable carbonate production between the euphotic and oligophotic zone, and changes in the configuration of the paleoslope. The study reinforces some previous hypotheses and presents alternative scenarios to the established concepts of high-transport ramp evolution. The results of sensitivity experiments show that steep slopes are favoured in ramps that develop in high-frequency sea level fluctuation with amplitudes between 20 m and 40 m. We also show that ramp profiles are significantly impacted by the paleoslope inclination, such that an optimal antecedent slope of about 0.15 degrees is required for the Menorca distally steepened ramp to develop.
The third part presents an experimental case to argue for the existence of a Photozoan sediment threshold required for the development of steep margins in carbonate platforms. This was carried out by developing sensitivity tests on the forward models of the flat-topped (Llucmajor) platform and the distally steepened (Menorca) platform. The results show that models with Photozoan sediment proportion below a threshold of about 40% are incapable of forming steep slopes. The study also demonstrates that though it is possible to develop steep margins by seagrass sediment trapping, such slopes can only be stabilized by the appropriate sediment fabric and/or microbial binding. In the Photozoan-dominated system, the magnitude of slope steepness depends on the proportion of Photozoan sediments in the system. Therefore, this study presents a novel tool for characterizing carbonate systems based on their biogenic components.
Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process – rather than actual changes in the dynamical properties of the system – is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.
Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process – rather than actual changes in the dynamical properties of the system – is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.