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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.
Martian atmospheric spectral end-members retrieval from ExoMars Thermal Infrared (TIRVIM) data
(2022)
Key knowledge about planetary composition can be recovered from the study of thermal infrared spectral range datasets.
This range has a huge diagnostic potential because it contains diagnostic absorptions from a planetary surface and atmosphere. The main goal of this study is to process and interpret the dataset from the Thermal Infrared channel (TIRVIM) which is part of the Atmospheric Chemistry Suite of the ExoMars2016 Trace Gas Orbiter mission to find and characterize dust and water ice clouds in the atmosphere.
The method employed here is based on the application of principal component analysis and target transformation techniques to extract the independent variable components present in the analyzed dataset. Spectral shapes of both atmospheric dust and water ice aerosols have been recovered from the analysis of TIRVIM data.
The comparison between our results with those previously obtained on Thermal Emission Spectrometer (TES) data and with previous analysis on TIRVIM data, validates the methodology here applied, showing that it allows to correctly recover the atmospheric spectral endmembers present in the TIRVIM data.
Moreover, comparison with atmospheric retrievals on PFS, TES and IRIS data, allowed us to assess the temporal stability and homogeneity of dust and water ice components in the Martian atmosphere over a time period of almost 50 years.
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.
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models
(2022)
Electrical resistivity tomography (ERT) aims at imaging the subsurface resistivity distribution and provides valuable information for different geological, engineering, and hydrological applications. To obtain a subsurface resistivity model from measured apparent resistivities, stochastic or deterministic inversion procedures may be employed. Typically, the inversion of ERT data results in non-unique solutions; i.e., an ensemble of different models explains the measured data equally well. In this study, we perform inference analysis of model ensembles generated using a well-established global inversion approach to assess uncertainties related to the nonuniqueness of the inverse problem. Our interpretation strategy starts by establishing model selection criteria based on different statistical descriptors calculated from the data residuals. Then, we perform cluster analysis considering the inverted resistivity models and the corresponding data residuals. Finally, we evaluate model uncertainties and residual distributions for each cluster. To illustrate the potential of our approach, we use a particle swarm optimization (PSO) algorithm to obtain an ensemble of 2D layer-based resistivity models from a synthetic data example and a field data set collected in Loon-Plage, France. Our strategy performs well for both synthetic and field data and allows us to extract different plausible model scenarios with their associated uncertainties and data residual distributions. Although we demonstrate our workflow using 2D ERT data and a PSObased inversion approach, the proposed strategy is general and can be adapted to analyze model ensembles generated from other kinds of geophysical data and using different global inversion approaches.
At the interface between the lithosphere and the atmosphere, the critical zone records the complex interactions between erosion, climate, geologic substrate, and life and can be directly monitored. Long data records (30 consecutive years for sediment yields) collected in the sparsely vegetated, steep, and small marly badland catchments of the Draix-Bleone Critical Zone Observatory (CZO), SE France, allow analyzing potential climatic controls on regolith dynamics and sediment export. Although widely accepted as a first-order control, rainfall variability does not fully explain the observed interannual variability in sediment export. Previous studies in this area have suggested that frost-weathering processes could drive regolith production and potentially modulate the observed pattern of sediment export. Here, we define sediment export anomalies as the residuals from a predictive model with annual rainfall intensity above a threshold as the control. We then use continuous soil temperature data recorded at different locations over multiple years to highlight the role of different frost-weathering processes (i.e., ice segregation versus volumetric expansion) in regolith production. Several proxies for different frost-weathering processes have been calculated from these data and compared to the sediment export anomalies, with careful consideration of field data quality. Our results suggest that frost-cracking intensity (linked to ice segregation) can explain about half (47 %-64 %) of the sediment export anomalies. In contrast, the number of freeze-thaw cycles (linked to volumetric expansion) has only a minor impact on catchment sediment response. The time spent below 0 degrees C also correlates well with the sediment export anomalies and requires fewer field data to be calculated than the frost-cracking intensity. Thus, frost-weathering processes modulate sediment export by controlling regolith production in these catchments and should be taken into account when building predictive models of sediment export from these badlands under a changing climate.
The response of rapidly compressed highly oriented pyrolytic graphite (HOPG) normal to its basal plane was investigated at a pressure of & SIM;80 GPa. Ultrafast x-ray diffraction using & SIM;100 fs pulses at the Materials Under Extreme Conditions sector of the Linac Coherent Light Source was used to probe the changes in crystal structure resulting from picosecond timescale compression at laser drive energies ranging from 2.5 to 250 mJ. A phase transformation from HOPG to a highly textured hexagonal diamond structure is observed at the highest energy, followed by relaxation to a still highly oriented, but distorted graphite structure following release. We observe the formation of a highly oriented lonsdaleite within 20 ps, subsequent to compression. This suggests that a diffusionless martensitic mechanism may play a fundamental role in phase transition, as speculated in an early work on this system, and more recent static studies of diamonds formed in impact events. Published by AIP Publishing.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
Fifteen N-butylpyridinium salts - five monometallic [C4Py](2)[MBr4] and ten bimetallic [C4Py](2)[(M0.5M0.5Br4)-M-a-Br-b] (M=Co, Cu, Mn, Ni, Zn) - were synthesized, and their structures and thermal and electrochemical properties were studied. All the compounds are ionic liquids (ILs) with melting points between 64 and 101 degrees C. Powder and single-crystal X-ray diffraction show that all ILs are isostructural. The electrochemical stability windows of the ILs are between 2 and 3 V. The conductivities at room temperature are between 10(-5) and 10(-6) S cm(-1). At elevated temperatures, the conductivities reach up to 10(-4) S cm(-1) at 70 degrees C. The structures and properties of the current bromide-based ILs were also compared with those of previous examples using chloride ligands, which illustrated differences and similarities between the two groups of ILs.
We examine sub-caldera structure and seismicity in and around the Okataina Volcanic Centre (OVC), Taupo Volcanic Zone, New Zealand, using seismic data collected over 4+ years with a temporary array of broadband and short-period seismometers, supplementing data from the permanent New Zealand seismometer network.
We derive a new 3-D image of P-wave seismic velocity for the upper crust in the region, using double-difference seismic tomography and utilising waveform cross-correlations. We subsequently relocate 6989 earthquakes which occurred in the region over the 2010-2021 time period, using the 3D velocity model.
The seismicity distribution shows spatial clusters west of Lake Rotomahana, as well as beneath Haroharo and the Makatiti Dome, inside the Okataina caldera. Beneath Makatiti Dome 90% of the events are shallower than 7.7 +/- 0.5 km.
Outside of the Okataina caldera event relocations highlight short (similar to 3-4 km long) streaks of activity in the Ngakuru graben, part of the active Taupo Rift southwest of Okataina caldera. Inside the OVC the relocated seismicity beneath Makatiti appears closely associated with low (similar to 10%) P-wave velocity anomalies, which we resolve in the similar to 5-to-8-km depth range beneath the Okataina caldera, and which are likely related to partial melt and/or fluid-volatile pathways.
Moment tensor analyses for two larger-magnitude events (M(L)4.5 and M(L)4.9) near Haroharo indicate normal faulting, with NNE-SSW fault strike, but with positive CLVD and positive isotropic components when allowing for a full moment tensor, consistent with a magmatic environment with degassing and/or fluid migration.
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.
Draft Genome Sequence of Nocardioides alcanivorans NGK65(T), a Hexadecane-Degrading Bacterium
(2022)
The Gram-positive bacterium Nocardioides alcanivorans NGK65(T) was isolated from plastic-polluted soil and cultivated on medium with polyethylene as the single carbon source. Nanopore sequencing revealed the presence of candidate enzymes for the biodegradation of polyethylene. Here, we report the draft genome of this newly described member of the terrestrial plastisphere.
The Gram-negative bacterium Paenalcaligenes niemegkensis NGK35(T) was isolated from plastic debris in an abandoned landfill.
It has the ability to grow on polyethylene and hexadecane as the sole carbon sources. Here, we report the corresponding draft genome, which contains 3.66 Mbp and is characterized by a G+C content of 52.1%.
Eight d-metal-containing N-butylpyridinium ionic liquids (ILs) with the nominal composition (C4Py)2[Ni0.5M0.5Cl4] or (C4Py)2[Zn0.5M0.5Cl4] (M = Cu, Co, Mn, Ni, Zn; C4Py = N-butylpyridinium) were synthesized, characterized, and investigated for their optical properties. Single crystal and powder X-ray analysis shows that the compounds are isostructural to existing examples based on other d-metal ions. Inductively coupled plasma optical emission spectroscopy measurements confirm that the metal/metal ratio is around 50 : 50. UV-Vis spectroscopy shows that the optical absorption can be tuned by selection of the constituent metals. Moreover, the compounds can act as an optical sensor for the detection of gases such as ammonia as demonstrated via a simple prototype setup.
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.
During the last 5 Ma the Earth's ocean-atmosphere system passed through several major transitions, many of which are discussed as possible triggers for human evolution. A classic in this context is the possible influence of the closure of the Panama Strait, the intensification of Northern Hemisphere Glaciation, a stepwise increase in aridity in Africa, and the first appearance of the genus Homo about 2.5 - 2.7 Ma ago. Apart from the fact that the correlation between these events does not necessarily imply causality, many attempts to establish a relationship between climate and evolution fail due to the challenge of precisely localizing an a priori unknown number of changes potentially underlying complex climate records. The kernel-based Bayesian inference approach applied here allows inferring the location, generic shape, and temporal scale of multiple transitions in established records of Plio-Pleistocene African climate. By defining a transparent probabilistic analysis strategy, we are able to identify conjoint changes occurring across the investigated terrigenous dust records from Ocean Drilling Programme (ODP) sites in the Atlantic Ocean (ODP 659), Arabian (ODP 721/722) and Mediterranean Sea (ODP 967). The study indicates a two-step transition in the African climate proxy records at (2.35-2.10) Ma and (1.70 - 1.50) Ma, that may be associated with the reorganization of the Hadley-Walker Circulation. .
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.
Here I present a comparison between two of the most widely used reduced-complexity models for the representation of sediment transport and deposition processes, namely the transport-limited (or TL) model and the under-capacity (or xi-q) model more recently developed by Davy and Lague (2009). Using both models, I investigate the behavior of a sedimentary continental system of length L fed by a fixed sedimentary flux from a catchment of size A(0) in a nearby active orogen through which sediments transit to a fixed base level representing a large river, a lake or an ocean. This comparison shows that the two models share the same steady-state solution, for which I derive a simple 1D analytical expression that reproduces the major features of such sedimentary systems: a steep fan that connects to a shallower alluvial plain. The resulting fan geometry obeys basic observational constraints on fan size and slope with respect to the upstream drainage area, A(0). The solution is strongly dependent on the size of the system, L, in comparison to a distance L-0, which is determined by the size of A(0), and gives rise to two fundamentally different types of sedimentary systems: a constrained system where L < L-0 and open systems where L > L-0. I derive simple expressions that show the dependence of the system response time on the system characteristics, such as its length, the size of the upstream catchment area, the amplitude of the incoming sedimentary flux and the respective rate parameters (diffusivity or erodibility) for each of the two models. I show that the xi-q model predicts longer response times. I demonstrate that although the manner in which signals propagates through the sedimentary system differs greatly between the two models, they both predict that perturbations that last longer than the response time of the system can be recorded in the stratigraphy of the sedimentary system and in particular of the fan. Interestingly, the xi-q model predicts that all perturbations in the incoming sedimentary flux will be transmitted through the system, whereas the TL model predicts that rapid perturbations cannot. I finally discuss why and under which conditions these differences are important and propose observational ways to determine which of the two models is most appropriate to represent natural systems.
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.
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.
The current awareness of the high importance of urban green leads to a stronger need for tools to comprehensively represent urban green and its benefits. A common scientific approach is the development of urban ecosystem services (UES) based on remote sensing methods at the city or district level. Urban planning, however, requires fine-grained data that match local management practices. Hence, this study linked local biotope and tree mapping methods to the concept of ecosystem services. The methodology was tested in an inner-city district in SW Germany, comparing publicly accessible areas and non-accessible courtyards. The results provide area-specific [m(2)] information on the green inventory at the microscale, whereas derived stock and UES indicators form the basis for comparative analyses regarding climate adaptation and biodiversity. In the case study, there are ten times more micro-scale green spaces in private courtyards than in the public space, as well as twice as many trees. The approach transfers a scientific concept into municipal planning practice, enables the quantitative assessment of urban green at the microscale and illustrates the importance for green stock data in private areas to enhance decision support in urban development. Different aspects concerning data collection and data availability are critically discussed.
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.
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 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.
An earthquake swarm affected the Bransfield Strait, Antarctica, a unique rift basin in transition from intra-arc rifting to ocean spreading. The swarm, counting similar to 85,000 volcano-tectonic earthquakes since August 2020, is located close to the Orca submarine volcano, previously considered inactive. Simultaneously, geodetic data reported up to similar to 11 cm north-westward displacement over King George Island. We use a broad variety of geophysical data and methods to reveal the complex migration of seismicity, accompanying the intrusion of 0.26-0.56 km(3) of magma. Strike-slip earthquakes mark the intrusion at depth, while shallower normal faulting the similar to 20 km long lateral growth of a dike. Seismicity abruptly decreased after a Mw 6.0 earthquake, suggesting the magmatic dike lost pressure with the slipping of a large fault. A seafloor eruption is likely, but not confirmed by sea surface temperature anomalies. The unrest documents episodic magmatic intrusion in the Bransfield Strait, providing unique insights into active continental rifting.
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.
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.
Seismicity models are probabilistic forecasts of earthquake rates to support seismic hazard assessment.
Physics-based models allow extrapolating previously unsampled parameter ranges and enable conclusions on underlying tectonic or human-induced processes.
The Coulomb Failure (CF) and the rate-and-state (RS) models are two widely used physics-based seismicity models both assuming pre-existing populations of faults responding to Coulomb stress changes.
The CF model depends on the absolute Coulomb stress and assumes instantaneous triggering if stress exceeds a threshold, while the RS model only depends on stress changes.
Both models can predict background earthquake rates and time-dependent stress effects, but the RS model with its three independent parameters can additionally explain delayed aftershock triggering.
This study introduces a modified CF model where the instantaneous triggering is replaced by a mean time-to-failure depending on the absolute stress value.
For the specific choice of an exponential dependence on stress and a stationary initial seismicity rate, we show that the model leads to identical results as the RS model and reproduces the Omori-Utsu relation for aftershock decays as well stress-shadowing effects.
Thus, both CF and RS models can be seen as special cases of the new model. However, the new stress response model can also account for subcritical initial stress conditions and alternative functions of the mean time-to-failure depending on the problem and fracture mode.
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.
The immense advances in computer power achieved in the last decades have had a significant impact in Earth science, providing valuable research outputs that allow the simulation of complex natural processes and systems, and generating improved forecasts. The development and implementation of innovative geoscientific software is currently evolving towards a sustainable and efficient development by integrating models of different aspects of the Earth system. This will set the foundation for a future digital twin of the Earth. The codification and update of this software require great effort from research groups and therefore, it needs to be preserved for its reuse by future generations of geoscientists. Here, we report on Geo-Soft-CoRe, a Geoscientific Software & Code Repository, hosted at the archive DIGITAL.CSIC. This is an open source, multidisciplinary and multiscale collection of software and code developed to analyze different aspects of the Earth system, encompassing tools to: 1) analyze climate variability; 2) assess hazards, and 3) characterize the structure and dynamics of the solid Earth. Due to the broad range of applications of these software packages, this collection is useful not only for basic research in Earth science, but also for applied research and educational purposes, reducing the gap between the geosciences and the society. By providing each software and code with a permanent identifier (DOI), we ensure its self-sustainability and accomplish the FAIR (Findable, Accessible, Interoperable and Reusable) principles. Therefore, we aim for a more transparent science, transferring knowledge in an easier way to the geoscience community, and encouraging an integrated use of computational infrastructure.
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.
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.
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.
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.
The Gofa Province and the Chew Bahir Basin of southern Ethiopia constitute tectonically active regions, where the Southern Main Ethiopian Rift converges with the Northern Kenya Rift through a wide zone of extensional deformation with several north to northeast-trending, left-stepping en-e & PRIME;chelon basins. This sector of the Southern Main Ethiopian Rift is characterized by a semi-arid climate and a largely uniform lithology, and thus provides ideal conditions for studying the different parameters that define the tectonic and geomorphic features of this complex kinematic transfer zone. In this study, the degree of tectonic activity, spatiotemporal variations in extension, and the nature of kinematic linkage between different fault systems of the transfer zone are constrained by detailed quantitative geomorphic analysis of river catchments and focused field work. We analyzed fluvial and landscape morphometric characteristics in combination with structural, seismicity, and climatic data to better evaluate the tectono-geomorphic history of this transfer zone. Our data reveal significant north-south variations in the degree of extension from the Sawula Basin in the north (mature) to the Chew Bahir Basin in the south (juvenile). First, normalized channel-steepness indices and the spatial arrangement of knickpoints in footwall-draining streams suggest a gradual, southward shift in extensional deformation and recent tectonic activity. Second, based on 1-k(m) radius local relief and mean-hillslope maximum values that are consistent with ksn anomalies, we confirm strain localization within zones of fault interaction. Third, morphometric indices such as hypsometry, basin asymmetry factor, and valley floor width to valley height ratio also indicate a north to south gradient in tectonic activity, highlighting the importance of such a wide transfer zone with diffuse extension linking different rift segments during the break-up of continental crust.
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.
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.
Hydraulic-driven fractures play a key role in subsurface energy technologies across several scales. By injecting fluid at high hydraulic pressure into rock with intrinsic low permeability, in-situ stress field and fracture development pattern can be characterised as well as rock permeability can be enhanced. Hydraulic fracturing is a commercial standard procedure for enhanced oil and gas production of rock reservoirs with low permeability in petroleum industry. However, in EGS utilization, a major geological concern is the unsolicited generation of earthquakes due to fault reactivation, referred to as induced seismicity, with a magnitude large enough to be felt on the surface or to damage facilities and buildings. Furthermore, reliable interpretation of hydraulic fracturing tests for stress measurement is a great challenge for the energy technologies. Therefore, in this cumulative doctoral thesis the following research questions are investigated. (1): How do hydraulic fractures grow in hard rock at various scales?; (2): Which parameters control hydraulic fracturing and hydro-mechanical coupling?; and (3): How can hydraulic fracturing in hard rock be modelled?
In the laboratory scale study, several laboratory hydraulic fracturing experiments are investigated numerically using Irazu2D that were performed on intact cubic Pocheon granite samples from South Korea applying different injection protocols. The goal of the laboratory experiments is to test the concept of cyclic soft stimulation which may enable sustainable permeability enhancement (Publication 1).
In the borehole scale study, hydraulic fracturing tests are reported that were performed in boreholes located in central Hungary to determine the in-situ stress for a geological site investigation. At depth of about 540 m, the recorded pressure versus time curves in mica schist with low dip angle foliation show atypical evolution. In order to provide explanation for this observation, a series of discrete element computations using Particle Flow Code 2D are performed (Publication 2).
In the reservoir scale study, the hydro-mechanical behaviour of fractured crystalline rock due to one of the five hydraulic stimulations at the Pohang Enhanced Geothermal site in South Korea is studied. Fluid pressure perturbation at faults of several hundred-meter lengths during hydraulic stimulation is simulated using FracMan (Publication 3).
The doctoral research shows that the resulting hydraulic fracturing geometry will depend “locally”, i.e. at the length scale of representative elementary volume (REV) and below that (sub-REV), on the geometry and strength of natural fractures, and “globally”, i.e. at super-REV domain volume, on far-field stresses. Regarding hydro-mechanical coupling, it is suggested to define separate coupling relationship for intact rock mass and natural fractures. Furthermore, the relative importance of parameters affecting the magnitude of formation breakdown pressure, a parameter characterising hydro-mechanical coupling, is defined. It can be also concluded that there is a clear gap between the capacity of the simulation software and the complexity of the studied problems. Therefore, the computational time of the simulation of complex hydraulic fracture geometries must be reduced while maintaining high fidelity simulation results. This can be achieved either by extending the computational resources via parallelization techniques or using time scaling techniques. The ongoing development of used numerical models focuses on tackling these methodological challenges.
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.
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.
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.
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.
Understanding and constraining the source of geodetic deformation in volcanic areas is an important component of hazard assessment. Here, we analyse deformation and seismicity for one year before the March 2021 Fagradalsfjall eruption in Iceland. We generate a high-resolution catalogue of 39,500 earthquakes using optical cable recordings and develop a poroelastic model to describe three pre-eruptional uplift and subsidence cycles at the Svartsengi geothermal field, 8 km west of the eruption site. We find the observed deformation is best explained by cyclic intrusions into a permeable aquifer by a fluid injected at 4 km depth below the geothermal field, with a total volume of 0.11 ± 0.05 km3 and a density of 850 ± 350 kg m–3. We therefore suggest that ingression of magmatic CO2 can explain the geodetic, gravity and seismic data, although some contribution of magma cannot be excluded.
Despite more than half a century of hominin fossil discoveries in eastern Africa, the regional environmental context of hominin evolution and dispersal is not well established due to the lack of continuous palaeoenvironmental records from one of the proven habitats of early human populations, particularly for the Pleistocene epoch. Here we present a 620,000-year environmental record from Chew Bahir, southern Ethiopia, which is proximal to key fossil sites. Our record documents the potential influence of different episodes of climatic variability on hominin biological and cultural transformation. The appearance of high anatomical diversity in hominin groups coincides with long-lasting and relatively stable humid conditions from similar to 620,000 to 275,000 years bp (episodes 1-6), interrupted by several abrupt and extreme hydroclimate perturbations. A pattern of pronounced climatic cyclicity transformed habitats during episodes 7-9 (similar to 275,000-60,000 years bp), a crucial phase encompassing the gradual transition from Acheulean to Middle Stone Age technologies, the emergence of Homo sapiens in eastern Africa and key human social and cultural innovations. Those accumulative innovations plus the alignment of humid pulses between northeastern Africa and the eastern Mediterranean during high-frequency climate oscillations of episodes 10-12 (similar to 60,000-10,000 years bp) could have facilitated the global dispersal of H. sapiens.
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.
40Ar/39Ar dating of a hydrothermal pegmatitic buddingtonite–muscovite assemblage from Volyn, Ukraine
(2022)
We determined Ar-40/Ar-39 ages of buddingtonite, occurring together with muscovite, with the laser-ablation method. This is the first attempt to date the NH4-feldspar buddingtonite, which is typical for sedimentary-diagenetic environments of sediments, rich in organic matter, or in hydrothermal environments, associated with volcanic geyser systems. The sample is a hydrothermal breccia, coming from the Paleoproterozoic pegmatite field of the Korosten Plutonic Complex, Volyn, Ukraine. A detailed characterization by optical methods, electron microprobe analyses, backscattered electron imaging, and IR analyses showed that the buddingtonite consists of euhedral-appearing platy crystals of tens of micrometers wide, 100 or more micrometers in length, which consist of fine-grained fibers of <= 1 mu m thickness. The crystals are sector and growth zoned in terms of K-NH4-H3O content. The content of K allows for an age determination with the Ar-40/Ar-39 method, as well as in the accompanying muscovite, intimately intergrown with the buddingtonite. The determinations on muscovite yielded an age of 1491 +/- 9 Ma, interpreted as the hydrothermal event forming the breccia. However, buddingtonite apparent ages yielded a range of 563 +/- 14 Ma down to 383 +/- 12 Ma, which are interpreted as reset ages due to Ar loss of the fibrous buddingtonite crystals during later heating. We conclude that buddingtonite is suited for Ar-40/Ar-39 age determinations as a supplementary method, together with other methods and minerals; however, it requires a detailed mineralogical characterization, and the ages will likely represent minimum ages.