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Frequent and intense rainfall events demand innovative techniques to better predict the extreme rainfall dynamics. This task requires essentially the assessment of the basic types of atmospheric processes that trigger extreme rainfall, and then to examine the differences between those processes, which may help to identify key patterns to improve predictive algorithms. We employ tools from network theory to compare the spatial features of extreme rainfall over the Japanese archipelago and surrounding areas caused by two atmospheric processes: the Baiu front, which occurs mainly in June and July (JJ), and the tropical storms from August to November (ASON). We infer from complex networks of satellite-derived rainfall data, which are based on the nonlinear correlation measure of event synchronization. We compare the spatial scales involved in both systems and identify different regions which receive rainfall due to the large spatial scale of the Baiu and tropical storm systems. We observed that the spatial scales involved in the Baiu driven rainfall extremes, including the synoptic processes behind the frontal development, are larger than tropical storms, which even have long tracks during extratropical transitions. We further delineate regions of coherent rainfall during the two seasons based on network communities, identifying the horizontal (east-west) rainfall bands during JJ over the Japanese archipelago, while during ASON these bands align with the island arc of Japan.
The combined passive and active seismic TRANSALP experiment produced an unprecedented high-resolution crustal image of the Eastern Alps between Munich and Venice. The European and Adriatic Mohos (EM and AM, respectively) are clearly imaged with different seismic techniques: near-vertical incidence reflections and receiver functions (RFs). The European Moho dips gently southward from 35 km beneath the northern foreland to a maximum depth of 55 km beneath the central part of the Eastern Alps, whereas the Adriatic Moho is imaged primarily by receiver functions at a relatively constant depth of about 40 km. In both data sets, we have also detected first-order Alpine shear zones, such as the Helvetic detachment, Inntal fault and SubTauern ramp in the north. Apart from the Valsugana thrust, receiver functions in the southern part of the Eastern Alps have also observed a north dipping interface, which may penetrate the entire Adriatic crust [Adriatic Crust Interface (ACI)]. Deep crustal seismicity may be related to the ACI. We interpret the ACI as the currently active retroshear zone in the doubly vergent Alpine collisional belt. (C) 2004 Elsevier B.V. All rights reserved
Despite advanced seismological techniques, automatic source characterization for microseismic earthquakes remains difficult and challenging since current inversion and modelling of high-frequency signals are complex and time consuming. For real-time applications such as induced seismicity monitoring, the application of standard methods is often not fast enough for true complete real-time information on seismic sources. In this paper, we present an alternative approach based on recent advances in deep learning for rapid source-parameter estimation of microseismic earthquakes. The seismic inversion is represented in compact form by two convolutional neural networks, with individual feature extraction, and a fully connected neural network, for feature aggregation, to simultaneously obtain full moment tensor and spatial location of microseismic sources. Specifically, a multibranch neural network algorithm is trained to encapsulate the information about the relationship between seismic waveforms and underlying point-source mechanisms and locations. The learning-based model allows rapid inversion (within a fraction of second) once input data are available. A key advantage of the algorithm is that it can be trained using synthetic seismic data only, so it is directly applicable to scenarios where there are insufficient real data for training. Moreover, we find that the method is robust with respect to perturbations such as observational noise and data incompleteness (missing stations). We apply the new approach on synthesized and example recorded small magnitude (M <= 1.6) earthquakes at the Hellisheioi geothermal field in the Hengill area, Iceland. For the examined events, the model achieves excellent performance and shows very good agreement with the inverted solutions determined through standard methodology. In this study, we seek to demonstrate that this approach is viable for microseismicity real-time estimation of source parameters and can be integrated into advanced decision-support tools for controlling induced seismicity.
Cosmogenic nuclides are typically used to either constrain an exposure age, a burial age, or an erosion rate. Constraining the landscape history and past erosion rates in previously glaciated terrains is, however, notoriously difficult because it involves a large number of unknowns. The potential use of cosmogenic nuclides in landscapes with a complex history of exposure and erosion is therefore often quite limited. Here, we present a novel multi-nuclide approach to study the landscape evolution and past erosion rates in terrains with a complex exposure history, particularly focusing on regions that were repeatedly covered by glaciers or ice sheets during the Quaternary. The approach, based on the Markov Chain Monte Carlo (MCMC) technique, focuses on mapping the range of landscape histories that are consistent with a given set of measured cosmogenic nuclide concentrations. A fundamental assumption of the model approach is that the exposure history at the site/location can be divided into two distinct regimes: i) interglacial periods characterized by zero shielding due to overlying ice and a uniform interglacial erosion rate, and ii) glacial periods characterized by 100% shielding and a uniform glacial erosion rate. We incorporate the exposure history in the model framework by applying a threshold value to the global marine benthic delta O-18 record and include the threshold value as a free model parameter, hereby taking into account global changes in climate. However, any available information on the glacial-interglacial history at the sampling location, in particular the timing of the last deglaciation event, is readily incorporated in the model to constrain the inverse problem. Based on the MCMC technique, the model delineates the most likely exposure history, including the glacial and interglacial erosion rates, which, in turn, makes it possible to reconstruct an exhumation history at the site. We apply the model to two landscape scenarios based on synthetic data and two landscape scenarios based on paired Be-10/Al-26 data from West Greenland, which makes it possible to quantify the denudation rate at these locations. The model framework, which currently incorporates any combination of the following nuclides Be-10, Al-26, C-14, and Ne-21, is highly flexible and can be adapted to many different landscape settings. The model framework may also be used in combination with physics-based landscape evolution models to predict nuclide concentrations at different locations in the landscape. This may help validate the landscape models via comparison to measured nuclide concentrations or to devise new effective sampling strategies. (C) 2015 The Authors. Published by Elsevier B.V.
Background and Aims Dynamic processes occurring at the soil-root interface crucially influence soil physical, chemical and biological properties at a local scale around the roots, and are technically challenging to capture in situ. This study presents a novel multi-imaging approach combining fluorescence and neutron radiography that is able to simultaneously monitor root growth, water content distribution, root respiration and root exudation.
Methods Germinated seeds of white lupins (Lupinus albus) were planted in boron-free glass rhizotrons. After 11 d, the rhizotrons were wetted from the bottom and time series of fluorescence and neutron images were taken during the subsequent day and night cycles for 13 d. The following day (i.e. 25 d after planting) the rhizotrons were again wetted from the bottom and the measurements were repeated. Fluorescence sensor foils were attached to the inner sides of the glass and measurements of oxygen and pH were made on the basis of fluorescence intensity. The experimental set-up allowed for simultaneous fluorescence imaging and neutron radiography.
Key Results The interrelated patterns of root growth and distribution in the soil, root respiration, exudation and water uptake could all be studied non-destructively and at high temporal and spatial resolution. The older parts of the root system with greater root-length density were associated with fast decreases of water content and rapid changes in oxygen concentration. pH values around the roots located in areas with low soil water content were significantly lower than the rest of the root system.
Conclusions The results suggest that the combined imaging set-up developed here, incorporating fluorescence intensity measurements, is able to map important biogeochemical parameters in the soil around living plants with a spatial resolution that is sufficiently high enough to relate the patterns observed to the root system.
A modern pollen dataset from China and Mongolia (18-52 degrees N, 74-132 degrees E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables - mean annual precipitation (P-ann): 35-2091 mm, mean annual temperature (T-ann): -12.1-25.8 degrees C, mean temperature in the coldest month (Mt(co).): -33.8-21.7 degrees C, and mean temperature in the warmest month (Mt(wa)): 03-29.8 degrees C. Modern pollen-climate relationships are assessed using canonical correspondence analysis (CCA), Huisman-Olff-Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that P-ann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r(2)) and root mean square error of prediction (RMSEP). Mt(co) and Mt(wa) may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power. (C) 2014 Elsevier B.V. All rights reserved.
AimFossil pollen spectra from lake sediments in central and western Mongolia have been used to interpret past climatic variations, but hitherto no suitable modern pollen-climate calibration set has been available to infer past climate changes quantitatively. We established such a modern pollen dataset and used it to develop a transfer function model that we applied to a fossil pollen record in order to investigate: (1) whether there was a significant moisture response to the Younger Dryas event in north-western Mongolia; and (2) whether the early Holocene was characterized by dry or wet climatic conditions.
LocationCentral and western Mongolia.
MethodsWe analysed pollen data from surface sediments from 90 lakes. A transfer function for mean annual precipitation (P-ann) was developed with weighted averaging partial least squares regression (WA-PLS) and applied to a fossil pollen record from Lake Bayan Nuur (49.98 degrees N, 93.95 degrees E, 932m a.s.l.). Statistical approaches were used to investigate the modern pollen-climate relationships and assess model performance and reconstruction output.
ResultsRedundancy analysis shows that the modern pollen spectra are characteristic of their respective vegetation types and local climate. Spatial autocorrelation and significance tests of environmental variables show that the WA-PLS model for P-ann is the most valid function for our dataset, and possesses the lowest root mean squared error of prediction.
Main conclusionsPrecipitation is the most important predictor of pollen and vegetation distributions in our study area. Our quantitative climate reconstruction indicates a dry Younger Dryas, a relatively dry early Holocene, a wet mid-Holocene and a dry late Holocene.
Aim: Fossil pollen spectra from lake sediments on the Tibetan Plateau have been used for qualitative climate reconstruction, but no modern pollen-climate calibration set based on lake sediments is available to infer past climate quantitatively. This study aims to develop such a dataset and apply it to fossil data. Location: The Tibetan Plateau, between 30 and 40 degrees N and 87 and 103 degrees E. Methods: We collected surface sediments from 112 lakes and analysed them palynologically. The lakes span a wide range of mean annual precipitation (P-ann; 31-1022 mm), mean annual temperature (T-ann; -6.5 to 1 degrees C), and mean July temperature (T-July; 2.6-19.7 degrees C). Redundancy analysis showed that the modern pollen spectra are characteristic of their respective vegetation types and local climate. Transfer functions for P-ann, T-ann and T-July were developed with weighted averaging partial least squares. Model performance was assessed by leave-one-out cross-validation. Results: The root mean square errors of prediction (RMSEP) were 104 mm (P-ann), 1.18 degrees C (T-ann) and 1.17 degrees C (T-July). The RMSEPs, when expressed as percentages of the gradient sampled, were 10.6% (P-ann), 15.7% (T-ann) and 11.9% (T-July). These low values indicate the good performance of our models. An application of the models to fossil pollen spectra covering the last c. 50 kyr yielded realistic results for Luanhaizi Lake in the Qilian Mountains on the north-eastern Tibetan Plateau (modern P-ann 480 mm; T-ann-1 degrees C). T-ann and P-ann values similar to present ones were reconstructed for late Marine Isotope Stage 3, with minimum values for the Last Glacial Maximum (c. 300 mm and 2 degrees C below present), and maximum values for the early Holocene (c. 70 mm and 0.5 degrees C greater than present). Main conclusions: The modern pollen-climate calibration set will potentially be useful for quantitative climate reconstructions from lake-sediment pollen spectra from the Tibetan Plateau, an area of considerable climatic and biogeographical importance.
Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.
The features of Middle Miocene deposits in the Puna-Eastern Cordillera transition (Valles Calchaquies) indicate that Cenozoic deformation, sedimentation and volcanism follow a complex spatiotemporal relationship. The intense volcanic activity recorded in the eastern Puna border between 14 and 11.5 Ma coincides with the occurrence of one of the most important deformation events of the Neogene tectonic evolution in the region. Studies performed across the Puna-Eastern Cordillera transition show different relationships between volcanic deposits of ca. 13.5-12.1 Ma and the Oligocene-Miocene Angastaco Formation. In this paper we describe the ash-flow tuff deposits which are the first of this type found concordant in the sedimentary fill of Valles Calchaquies. Several analyses performed on these pyroclastic deposits allow a correlation to be made with the Alto de Las Lagunas Ignimbrite (ca. 13.5 Ma) of the Pucarilla-Cerro Tipillas Volcanic Complex located in the Puna. Outcrops of the ca. 13.5 Ma pyroclastic deposits are recognised within the Puna and the Valle Calchaqui. However, in the southern prolongation of the Valle de Hualfin (Tiopampa-Pucarilla depression) that separates the Puna from the Valle Calchaqui at these latitudes, these deposits are partially eroded and buried, and thus their occurrence is recorded only by abundant volcanic clasts included in conglomerates of the Angastaco Formation. The sedimentation of the Angastaco Formation was aborted at ca. 12 Ma in the Tiopampa-Pucarilla depression by the Pucarilla Ignimbrite, which unconformably covers the synorogenic units. On the contrary, in the Valle Calchaqui the sedimentation of the Angastaco Formation continued until the Late Miocene. The different relationships between the Miocene Angastaco Formation and the ignimbrites with ages of ca. 13.5 and ca. 12 Ma reveal that in this short period (-1.5 m.y.) a significant deformation event took place and resulted in marked palaeogeographic changes, as evidenced by stratigraphic-sedimentological and chronological records in the Angastaco Formation. (C) 2017 Elsevier B.V. All rights reserved.
This manuscript proposes a method to assess hydrological drought in semi-arid environments under high impoundment rate and applies it to the semi-arid Jaguaribe River basin in Brazil. It analyzes droughts (1) in the largest reservoir systems; (2) in the Upper Basin, considering 4744 reservoirs, 800 wells and almost 18,000 cisterns; and (3) in reservoirs of different sizes during multiyear droughts. Results show that the water demand is constrained in the basin; hydrological and meteorological droughts are often out of phase; there is a negative correlation between storage level and drought severity; and the small systems cannot cope with long-term droughts.
The Pleistocene archeological record in East Africa has revealed unusual accumulations of Acheulean handaxes at prehistoric sites. In particular, there has been intensive debate concerning whether the artifact accumulation at the Middle Pleistocene Olorgesailie (Southern Kenya Rift) and Kariandusi (Central Kenya Rift) sites were a result of fluvial reworking or of in situ deposition by hominids. We used a two-step approach to test the hypothesis of fluvial reworking. Firstly, the behavior of handaxes in water currents was investigated in a current flume and the flow threshold required to reorientate the handaxes was determined. The results of these experiments suggested that, in relatively high energy and non-steady flow conditions, handaxes will reorientate themselves perpendicular to the current direction. Secondly, an automated image analysis routine was developed and applied to archeological plans from three Acheulean sites, two at Olorgesailie and one at Kariandusi, in order to determine the orientations of the handaxes. A Rayleigh test was then applied to the orientation data to test for a preferred orientation. The results revealed that the handaxes at the Upper Kariandusi Site and the Olorgesailie Main Site Mid Trench had a preferential orientation, suggesting reworking by a paleocurrent. The handaxes from the Olorgesailie Main Site H/6A, however, appeared to be randomly oriented and in situ deposition by the producers therefore remains a possibility.
We apply and evaluate a recent machine learning method for the automatic classification of seismic waveforms. The method relies on Dynamic Bayesian Networks (DBN) and supervised learning to improve the detection capabilities at 3C seismic stations. A time-frequency decomposition provides the basis for the required signal characteristics we need in order to derive the features defining typical "signal" and "noise" patterns. Each pattern class is modeled by a DBN, specifying the interrelationships of the derived features in the time-frequency plane. Subsequently, the models are trained using previously labeled segments of seismic data. The DBN models can now be compared against in order to determine the likelihood of new incoming seismic waveform segments to be either signal or noise. As the noise characteristics of seismic stations varies smoothly in time (seasonal variation as well as anthropogenic influence), we accommodate in our approach for a continuous adaptation of the DBN model that is associated with the noise class. Given the difficulty for obtaining a golden standard for real data (ground truth) the proof of concept and evaluation is shown by conducting experiments based on 3C seismic data from the International Monitoring Stations, BOSA and LPAZ.
Ancient evaporite deposits are geological archives of depositional environments characterized by a long‐term negative precipitation balance and bear evidence for global ocean element mass balance calculations. Here, Cretaceous selenite pseudomorphs from western Anatolia (‘Rosetta Marble’) — characterized by their exceptional morphological preservation — and their ‘marine’ geochemical signatures are described and interpreted in a process‐oriented context. These rocks recorded Late Cretaceous high‐pressure/low‐temperature, subduction‐related metamorphism with peak conditions of 1·0 to 1·2 GPa and 300 to 400°C. Metre‐scale, rock‐forming radiating rods, now present as fibrous calcite marble, clearly point to selenitic gypsum as the precursor mineral. Stratigraphic successions are recorded along a reconstructed proximal to distal transect. The cyclical alternation of selenite beds and radiolarian ribbon‐bedded cherts in the distal portions are interpreted as a two type of seawater system. During arid intervals, shallow marine brines cascaded downward into basinal settings and induced precipitation. During more humid times, upwelling‐induced radiolarian blooms caused the deposition of radiolarite facies. Interestingly, there is no comparable depositional setting known from the Cenozoic world. Meta‐selenite geochemical data (δ13C, δ18O and 87Sr/86Sr) plot within the range of reconstructed middle Cretaceous seawater signatures. Possible sources for the 13C‐enriched (mean 2·2‰) values include methanogenesis, gas hydrates and cold seep fluid exhalation. Spatially resolved component‐specific analysis of a rock slab displays isotopic variances between meta‐selenite crystals (mean δ13C 2·2‰) and host matrix (mean δ13C 1·3‰). The Cretaceous evaporite‐pseudomorphs of Anatolia represent a basin wide event coeval with the Aptian evaporites of the Proto‐Atlantic and the pseudomorphs share many attributes, including lateral distribution of 600 km and stratigraphic thickness of 1·5 to 2·0 km, with the evaporites formed during the younger Messinian salinity crisis. The Rosetta Marble of Anatolia may represent the best‐preserved selenite pseudomorphs worldwide and have a clear potential to act as a template for the study of meta‐selenite in deep time.
The steady increase of ground-motion data not only allows new possibilities but also comes with new challenges in the development of ground-motion models (GMMs). Data classification techniques (e.g., cluster analysis) do not only produce deterministic classifications but also probabilistic classifications (e.g., probabilities for each datum to belong to a given class or cluster). One challenge is the integration of such continuous classification in regressions for GMM development such as the widely used mixed-effects model. We address this issue by introducing an extension of the mixed-effects model to incorporate data weighting. The parameter estimation of the mixed-effects model, that is, fixed-effects coefficients of the GMMs and the random-effects variances, are based on the weighted likelihood function, which also provides analytic uncertainty estimates. The data weighting permits for earthquake classification beyond the classical, expert-driven, binary classification based, for example, on event depth, distance to trench, style of faulting, and fault dip angle. We apply Angular Classification with Expectation-maximization, an algorithm to identify clusters of nodal planes from focal mechanisms to differentiate between, for example, interface- and intraslab-type events. Classification is continuous, that is, no event belongs completely to one class, which is taken into account in the ground-motion modeling. The theoretical framework described in this article allows for a fully automatic calibration of ground-motion models using large databases with automated classification and processing of earthquake and ground-motion data. As an example, we developed a GMM on the basis of the GMM by Montalva et al. (2017) with data from the strong-motion flat file of Bastias and Montalva (2016) with similar to 2400 records from 319 events in the Chilean subduction zone. Our GMM with the data-driven classification is comparable to the expert-classification-based model. Furthermore, the model shows temporal variations of the between-event residuals before and after large earthquakes in the region.
Computer-based simulation models are frequently used in hydrological research and engineering but also in other fields of environmental sciences. New case studies often require existing model concepts to be adapted. Extensions may be necessary due to the peculiarities of the studied natural system or subtleties of anthropogenic control. In other cases, simplifications must be made in response to scarce data, incomplete knowledge, or restrictions set by the spatio-temporal scale of application. This paper introduces an open-source modeling framework called ECHSE designed to cope with the above-mentioned challenges. It provides a lightweight infrastructure for the rapid development of new, reusable simulation tools and, more importantly, the safe modification of existing formulations. ECHSE-based models treat the simulated system as a collection of interacting objects. Although feedbacks are generally supported, the majority of the objects' interactions is expected to be of the feed-forward type. Therefore, the ECHSE software is particularly useful in the context of hydrological catchment modeling. Conversely, it is unsuitable, e.g., for fully hydrodynamic simulations and groundwater flow modeling. The focus of the paper is put on a comprehensible outline of the ECHSE's fundamental concepts and limitations. For the purpose of illustration, a specific, ECHSE-based solution for hydrological catchment modeling is presented which has undergone testing in a number of river basins. (C) 2015 Elsevier Ltd. All rights reserved.
A total of 271 pollen records were selected from a large collection of both raw and digitized pollen spectra from eastern continental Asia (70 degrees-135 degrees E and 18 degrees-55 degrees N). Following pollen percentage recalculations, taxonomic homogenization, and age-depth model revision, the pollen spectra were interpolated at a 500-year resolution and a taxonomically harmonized and temporally standardized fossil pollen dataset established with 226 pollen taxa, covering the last 22 cal lea. Of the 271 pollen records, 85% were published since 1990, with reliable chronologies and high temporal resolutions; of these, 50% have raw data with complete pollen assemblages, ensuring the quality of this dataset The pollen records available for each 500-year time slice are well distributed over all main vegetation types and climatic zones of the study area, making their pollen spectra suitable for paleovegetation and paleoclimate research. Such a dataset can be used as an example for the development of similar datasets for other regions of the world.
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.
Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.
We present a new autoclave that enables in situ characterization of hydrothermal fluids at high pressures and high temperatures at synchrotron x-ray radiation sources. The autoclave has been specifically designed to enable x-ray absorption spectroscopy in fluids with applications to mineral solubility and element speciation analysis in hydrothermal fluids in complex compositions. However, other applications, such as Raman spectroscopy, in high-pressure fluids are also possible with the autoclave. First experiments were run at pressures between 100 and 600 bars and at temperatures between 25 degrees C and 550 degrees C, and preliminary results on scheelite dissolution in fluids of different compositions show that the autoclave is well suited to study the behavior of ore-forming metals at P-T conditions relevant to the Earth's crust.
A hydrochemical approach to quantify the role of return flow in a surface flow-dominated catchment
(2017)
Stormflow generation in headwater catchments dominated by subsurface flow has been studied extensively, yet catchments dominated by surface flow have received less attention. We addressed this by testing whether stormflow chemistry is controlled by either (a) the event-water signature of overland flow, or (b) the pre-event water signature of return flow. We used a high-resolution hydrochemical data set of stormflow and end-members of multiple storms in an end-member mixing analysis to determine the number of end-members needed to explain stormflow, characterize and identify potential end-members, calculate their contributions to stormflow, and develop a conceptual model of stormflow. The arrangement and relative positioning of end-members in stormflow mixing space suggest that saturation excess overland flow (26-48%) and return flow from two different subsurface storage pools (17-53%) are both similarly important for stormflow. These results suggest that pipes and fractures are important flow paths to rapidly release stored water and highlight the value of within-event resolution hydrochemical data to assess the full range and dynamics of flow paths.
Lacustrine sediments have been widely used to investigate past climatic and environmental changes on millennial to seasonal time scales. Sedimentary archives of lakes in mountainous regions may also record non-climatic events such as earthquakes. We argue herein that a set of 64 annual laminae couplets reconciles a stratigraphically inconsistent accelerator mass spectrometry (AMS) C-14 chronology in a similar to 4-m-long sediment core from Lake Mengda, in the north-eastern Tibetan Plateau. The laminations suggest the lake was formed by a large landslide, triggered by the 1927 Gulang earthquake (M = 8.0). The lake sediment sequence can be separated into three units based on lithologic, sedimentary, and isotopic characteristics. Starting from the bottom of the sequence, these are: (1) unweathered, coarse, sandy valley-floor deposits or landslide debris that pre-date the lake, (2) landslide-induced, fine-grained soil or reworked landslide debris with a high organic content, and (3) lacustrine sediments with low organic content and laminations. These annual laminations provide a high-resolution record of anthropogenic and environmental changes during the twentieth century, recording enhanced sediment input associated with two phases of construction activities. The high mean sedimentation rates of up to 4.8 mm year(-1) underscore the potential for reconstructing such distinct sediment pulses in remote, forested, and seemingly undisturbed mountain catchments.
A comprehensive hydrometeorological dataset is presented spanning the period 1 January 201131 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km(2)) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution (similar to km(2), similar to min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km(2), 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Meteo-France (including 2m air temperature, atmospheric pressure, 2 m relative humidity, 10m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 to 116 km(2)) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling.
Reliable hydrological monitoring is the basis for sound water management in drained wetlands. Since statistical methods cannot be employed for unobserved or sparsely monitored areas, the primary design (first set-up) may be arbitrary in most instances. The objective of this paper is therefore to provide a guideline for designing the initial hydrological monitoring network. A scheme is developed that handles different parts of monitoring and hydrometry in wetlands, focusing on the positioning of surface water and groundwater gauges. For placement of the former, control units are used which correspond to areas whose water levels can be regulated separately. The latter are arranged depending on hydrological response units, defined by combinations of soil type and land use, and the chosen surface water monitoring sites. A practical application of the approach is shown for an investigation area in the Spreewald region in north-east Germany. The presented scheme leaves a certain degree of freedom to its user, allowing the inclusion of expert knowledge or special concerns. Based on easily obtainable data, the developed hydrological network serves as a first step in the iterative procedure of monitoring network optimisation. Copyright (c) 2013 John Wiley & Sons, Ltd.
Growing attention to phytoplankton mixotrophy as a trophic strategy has led to significant revisions of traditional pelagic food web models and ecosystem functioning. Although some empirical estimates of mixotrophy do exist, a much broader set of in situ measurements are required to (i) identify which organisms are acting as mixotrophs in real time and to (ii) assess the contribution of their heterotrophy to biogeochemical cycling. Estimates are needed through time and across space to evaluate which environmental conditions or habitats favour mixotrophy: conditions still largely unknown. We review methodologies currently available to plankton ecologists to undertake estimates of plankton mixotrophy, in particular nanophytoplankton phago-mixotrophy. Methods are based largely on fluorescent or isotopic tracers, but also take advantage of genomics to identify phylotypes and function. We also suggest novel methods on the cusp of use for phago-mixotrophy assessment, including single-cell measurements improving our capacity to estimate mixotrophic activity and rates in wild plankton communities down to the single-cell level. Future methods will benefit from advances in nanotechnology, micromanipulation and microscopy combined with stable isotope and genomic methodologies. Improved estimates of mixotrophy will enable more reliable models to predict changes in food web structure and biogeochemical flows in a rapidly changing world.
A ground motion logic tree for seismic hazard analysis in the stable cratonic region of Europe
(2020)
Regions of low seismicity present a particular challenge for probabilistic seismic hazard analysis when identifying suitable ground motion models (GMMs) and quantifying their epistemic uncertainty. The 2020 European Seismic Hazard Model adopts a scaled backbone approach to characterise this uncertainty for shallow seismicity in Europe, incorporating region-to-region source and attenuation variability based on European strong motion data. This approach, however, may not be suited to stable cratonic region of northeastern Europe (encompassing Finland, Sweden and the Baltic countries), where exploration of various global geophysical datasets reveals that its crustal properties are distinctly different from the rest of Europe, and are instead more closely represented by those of the Central and Eastern United States. Building upon the suite of models developed by the recent NGA East project, we construct a new scaled backbone ground motion model and calibrate its corresponding epistemic uncertainties. The resulting logic tree is shown to provide comparable hazard outcomes to the epistemic uncertainty modelling strategy adopted for the Eastern United States, despite the different approaches taken. Comparison with previous GMM selections for northeastern Europe, however, highlights key differences in short period accelerations resulting from new assumptions regarding the characteristics of the reference rock and its influence on site amplification.
Deep hydrothermal Mo, W, and base metal mineralization at the Sweet Home mine (Detroit City portal) formed in response to magmatic activity during the Oligocene. Microthermometric data of fluid inclusions trapped in greisen quartz and fluorite suggest that the early-stage mineralization at the Sweet Home mine precipitated from low- to medium-salinity (1.5-11.5 wt% equiv. NaCl), CO2-bearing fluids at temperatures between 360 and 415 degrees C and at depths of at least 3.5 km. Stable isotope and noble gas isotope data indicate that greisen formation and base metal mineralization at the Sweet Home mine was related to fluids of different origins. Early magmatic fluids were the principal source for mantle-derived volatiles (CO2, H2S/SO2, noble gases), which subsequently mixed with significant amounts of heated meteoric water. Mixing of magmatic fluids with meteoric water is constrained by delta H-2(w)-delta O-18(w) relationships of fluid inclusions. The deep hydrothermal mineralization at the Sweet Home mine shows features similar to deep hydrothermal vein mineralization at Climax-type Mo deposits or on their periphery. This suggests that fluid migration and the deposition of ore and gangue minerals in the Sweet Home mine was triggered by a deep-seated magmatic intrusion. The findings of this study are in good agreement with the results of previous fluid inclusion studies of the mineralization of the Sweet Home mine and from Climax-type Mo porphyry deposits in the Colorado Mineral Belt.
Advances in the field of seismic interferometry have provided a basic theoretical interpretation to the full spectrum of the microtremor horizontal-to-vertical spectral ratio [H/V(f)]. The interpretation has been applied to ambient seismic noise data recorded both at the surface and at depth. The new algorithm, based on the diffuse wavefield assumption, has been used in inversion schemes to estimate seismic wave velocity profiles that are useful input information for engineering and exploration seismology both for earthquake hazard estimation and to characterize surficial sediments. However, until now, the developed algorithms are only suitable for on land environments with no offshore consideration. Here, the microtremor H/V(z, f) modelling is extended for applications to marine sedimentary environments for a 1-D layered medium. The layer propagator matrix formulation is used for the computation of the required Green’s functions. Therefore, in the presence of a water layer on top, the propagator matrix for the uppermost layer is defined to account for the properties of the water column. As an application example we analyse eight simple canonical layered earth models. Frequencies ranging from 0.2 to 50 Hz are considered as they cover a broad wavelength interval and aid in practice to investigate subsurface structures in the depth range from a few meters to a few hundreds of meters. Results show a marginal variation of 8 per cent at most for the fundamental frequency when a water layer is present. The water layer leads to variations in H/V peak amplitude of up to 50 per cent atop the solid layers.
The present study proposes a General Probabilistic Framework (GPF) for uncertainty and global sensitivity analysis of deterministic models in which, in addition to scalar inputs, non-scalar and correlated inputs can be considered as well. The analysis is conducted with the variance-based approach of Sobol/Saltelli where first and total sensitivity indices are estimated. The results of the framework can be used in a loop for model improvement, parameter estimation or model simplification. The framework is applied to SWAP, a 113 hydrological model for the transport of water, solutes and heat in unsaturated and saturated soils. The sources of uncertainty are grouped in five main classes: model structure (soil discretization), input (weather data), time-varying (crop) parameters, scalar parameters (soil properties) and observations (measured soil moisture). For each source of uncertainty, different realizations are created based on direct monitoring activities. Uncertainty of evapotranspiration, soil moisture in the root zone and bottom fluxes below the root zone are considered in the analysis. The results show that the sources of uncertainty are different for each output considered and it is necessary to consider multiple output variables for a proper assessment of the model. Improvements on the performance of the model can be achieved reducing the uncertainty in the observations, in the soil parameters and in the weather data. Overall, the study shows the capability of the GPF to quantify the relative contribution of the different sources of uncertainty and to identify the priorities required to improve the performance of the model. The proposed framework can be extended to a wide variety of modelling applications, also when direct measurements of model output are not available.
A 741-cm-long laminated sediment core, covering the last 10,800 years was collected from Lake Zigetang, central Tibetan Plateau (90.9 degrees E, 32.0 degrees N, 4560m a.s.l.), and analysed palynologically at 69 horizons. Biome reconstruction suggests a dominance of temperate steppe vegetation (mainly Artemisia and Poaceae) on the central Tibetan Plateau during the first half of the Holocene (10.8-4.4 cal. ka BP), while alpine steppes with desert elements (mainly Cyperaceae, Poaceae, Chenopodiaceae, and characteristic high-alpine herb families) tend to dominate the second half (4.4-0 cal. ka BP). The Artemisia/Cyperaceae ratio-a semi-quantitative measure for summer temperature-indicates a general cooling trend throughout the Holocene. Dense temperate steppe vegetation and maximum desert plant withdrawal, however, indicate that a suitable balance of wet and warm conditions for optimum vegetation growth likely occurred during the middle Holocene (7.3-4.4 cal. ka BP). Severe Early Holocene cold events have been reconstructed for 8.7-8.3 and similar to 7.4 cal. ka BP. (c) 2006 Elsevier Ltd and INQUA. All rights reserved.
In this paper we evaluate different methods to predict soil erosion processes. We derived different layers of predictor variables for the study area in the Northern Chianti, Italy, describing the soil-lithologic complex, land use, and topographic characteristics. For a subcatchment of the Orme River, we mapped erosion processes by interpreting aerial photographs and field observations. These were classified as erosional response units (ERU), i.e. spatial areas of homogeneous erosion processes. The ERU were used as the response variable in the soil erosion modelling process. We applied two models i) bootstrap aggregation (Random Forest: RF), and ii) stochastic gradient boosting (TreeNet: TN) to predict the potential spatial distribution of erosion processes for the entire Orme River catchment. The models are statistically evaluated using training data and a set of performance parameters such as the area under the receiver operating characteristic curve (AUC), Cohen's Kappa, and pseudo R2. Variable importance and response curves provide further insight into controlling factors of erosion. Both models provided good performance in terms of classification and calibration; however, TN outperformed RF. Similar classes such as active and inactive landslides can be discriminated and well interpreted by considering response curves and relative variable importance. The spatial distribution of the predicted erosion susceptibilities generally follows topographic constraints and is similar for both models. Hence, the model-based delineation of ERU on the basis of soil and terrain information is a valuable tool in geomorphology; it provides insights into factors controlling erosion processes and may allow the extrapolation and prediction of erosion processes in unsurveyed areas.
The application of nanoscale zero-valent iron (nZVI) for subsurface remediation of groundwater contaminants is a promising new technology, which can be understood as alternative to the permeable reactive barrier technique using granular iron. Dechlorination of organic contaminants by zero-valent iron seems promising. Currently, one limitation to widespread deployment is the fast agglomeration and sedimentation of nZVI in colloidal suspensions, even more so when in soils and sediments, which limits the applicability for the treatment of sources and plumes of contamination. Colloid-supported nZVI shows promising characteristics to overcome these limitations. Mobility of Carbo-Iron Colloids (CIC) - a newly developed composite material based on finely ground activated carbon as a carrier for nZVI - was tested in a field application: In this study, a horizontal dipole flow field was established between two wells separated by 53 m in a confined, natural aquifer. The injection/extraction rate was 500 L/h. Approximately 12 kg of CIC was suspended with the polyanionic stabilizer carboxymethyl cellulose. The suspension was introduced into the aquifer at the injection well. Breakthrough of CIC was observed visually and based on total particle and iron concentrations detected in samples from the extraction well. Filtration of water samples revealed a particle breakthrough of about 12% of the amount introduced. This demonstrates high mobility of CIC particles and we suggest that nZVI carried on CIC can be used for contaminant plume remediation by in-situ formation of reactive barriers. (C) 2015 Elsevier B.V. All rights reserved.
A fast and sensitive method for the continuous determination of methane (CH4) and its stable carbon isotopic values (delta C-13-CH4) in surface waters was developed by applying a vacuum to a gas/liquid exchange membrane and measuring the extracted gases by a portable cavity ring-down spectroscopy analyser (M-CRDS). The M-CRDS was calibrated and characterized for CH4 concentration and delta C-13-CH4 with synthetic water standards. The detection limit of the M-CRDS for the simultaneous determination of CH4 and delta C-13-CH4 is 3.6 nmol L-1 CH4. A measurement precision of CH4 concentrations and delta C-13-CH4 in the range of 1.1%, respectively, 1.7 parts per thousand (1 sigma) and accuracy (1.3%, respectively, 0.8 parts per thousand [1 sigma]) was achieved for single measurements and averaging times of 10 min. The response time tau of 57 +/- 5 s allow determination of delta C-13-CH4 values more than twice as fast than other methods. The demonstrated M-CRDS method was applied and tested for Lake Stechlin (Germany) and compared with the headspace-gas chromatography and fast membrane CH4 concentration methods. Maximum CH4 concentrations (577 nmol L-1) and lightest delta C-13-CH4 (-35.2 parts per thousand) were found around the thermocline in depth profile measurements. The M-CRDS-method was in good agreement with other methods. Temporal variations in CH4 concentration and delta C-13-CH4 obtained in 24 h measurements indicate either local methane production/oxidation or physical variations in the thermocline. Therefore, these results illustrate the need of fast and sensitive analyses to achieve a better understanding of different mechanisms and pathways of CH4 formation in aquatic environments.
Past climatic change can be reconstructed from sedimentary archives by a number of proxies. However, few methods exist to directly estimate hydrological changes and even fewer result in quantitative data, impeding our understanding of the timing, magnitude and mechanisms of hydrological changes. Here we present a novel approach based on delta H-2 values of sedimentary lipid biomarkers in combination with plant physiological modeling to extract quantitative information on past changes in relative humidity. Our initial application to an annually laminated lacustrine sediment sequence from western Europe deposited during the Younger Dryas cold period revealed relative humidity changes of up to 15% over sub-centennial timescales, leading to major ecosystem changes, in agreement with palynological data from the region. We show that by combining organic geochemical methods and mechanistic plant physiological models on well characterized lacustrine archives it is possible to extract quantitative ecohydrological parameters from sedimentary lipid biomarker delta H-2 data.
The molecular biomarker composition of two sediment cores from Sanabria Lake (NW Iberian Peninsula) and a survey of modern plants in the watershed provide a reconstruction of past vegetation and landscape dynamics since deglaciation. During a proglacial stage in Lake Sanabria (prior to 14.7 cal ka BP), very low biomarker concentration and carbon preference index (CPI) values similar to 1 suggest that the n-alkanes could have derived from eroded ancient sediment sources or older organic matter with high degree of maturity. During the Late glacial (14.7-11.7 cal ka BP) and the Holocene (last 11.7 cal ka BP) intervals with higher biomarker and triterpenoid concentrations (high %nC(29) , nC(31) alkanes), higher CPI and average carbon length (ACL), and lower P-aq (proportion of aquatic plants) are indicative of major contribution of vascular land plants from a more forested watershed (e.g. Mid Holocene period 7.0-4.0 cal ka BP). Lower biomarker concentrations (high %nC(27) alkanes), CPI and ACL values responded to short phases with decreased allochthonous contribution into the lake that correspond to centennial-scale periods of regional forest decline (e.g. 4-3 ka BP, Roman deforestation after 2.0 ka, and some phases of the LIA, seventeenth-nineteenth centuries). Human activities in the watershed were significant during early medieval times (1.3-1.0 cal ka BP) and since 1960 CE, in both cases associated with relatively higher productivity stages in the lake (lower biomarker and triterpenoid concentrations, high %nC(23) and %nC(31) respectively, lower ACL and CPI values and higher P-aq). The lipid composition of Sanabria Lake sediments indicates a major allochthonous (watershed-derived) contribution to the organic matter budget since deglaciation, and a dominant oligotrophic status during the lake history. The study constrains the climate and anthropogenic forcings and watershed versus lake sources in organic matter accumulation processes and helps to design conservation and management policies in mountain, oligotrophic lakes.
Earthquake localization is both a necessity within the field of seismology, and a prerequisite for further analysis such as source studies and hazard assessment. Traditional localization methods often rely on manually picked phases. We present an alternative approach using deep learning that once trained can predict hypocenter locations efficiently. In seismology, neural networks have typically been trained with either single-station records or based on features that have been extracted previously from the waveforms. We use three-component full-waveform records of multiple stations directly. This means no information is lost during preprocessing and preparation of the data does not require expert knowledge. The first convolutional layer of our deep convolutional neural network (CNN) becomes sensitive to features that characterize the waveforms it is trained on. We show that this layer can therefore additionally be used as an event detector. As a test case, we trained our CNN using more than 2000 earthquake swarm events from West Bohemia, recorded by nine local three-component stations. The CNN successfully located 908 validation events with standard deviations of 56.4 m in east-west, 123.8 m in north-south, and 136.3 m in vertical direction compared to a double-difference relocated reference catalog. The detector is sensitive to events with magnitudes down to M-L = -0.8 with 3.5% false positive detections.
We present an experimental approach to study the three-dimensional microstructure of gas diffusion layer (GDL) materials under realistic compression conditions. A dedicated compression device was designed that allows for synchrotron-tomographic investigation of circular samples under well-defined compression conditions. The tomographic data provide the experimental basis for stochastic modeling of nonwoven GDL materials. A plain compression tool is used to study the fiber courses in the material at different compression stages. Transport relevant geometrical parameters, such as porosity, pore size, and tortuosity distributions, are exemplarily evaluated for a GDL sample in the uncompressed state and for a compression of 30 vol.%. To mimic the geometry of the flow-field, we employed a compression punch with an integrated channel-rib-profile. It turned out that the GDL material is homogeneously compressed under the ribs, however, much less compressed underneath the channel. GDL fibers extend far into the channel volume where they might interfere with the convective gas transport and the removal of liquid water from the cell. (C) 2015 AIP Publishing LLC.
In this study we investigate a dayside, midlatitude plasma depletion (DMLPD) encountered on 22 May 2014 by the Swarm and GRACE satellites, as well as ground-based instruments. The DMLPD was observed near Puerto Rico by Swarm near 10 LT under quiet geomagnetic conditions at altitudes of 475-520 km and magnetic latitudes of similar to 25 degrees-30 degrees. The DMLPD was also revealed in total electron content observations by the Saint Croix station and by the GRACE satellites (430 km) near 16 LT and near the same geographic location. The unique Swarm constellation enables the horizontal tilt of the DMLPD to be measured (35 degrees clockwise from the geomagnetic east-west direction). Ground-based airglow images at Arecibo showed no evidence for plasma density depletions during the night prior to this dayside event. The C/NOFS equatorial satellite showed evidence for very modest plasma density depletions that had rotated into the morningside from nightside. However, the equatorial depletions do not appear related to the DMLPD, for which the magnetic apex height is about 2500 km. The origins of the DMLPD are unknown, but may be related to gravity waves.
Compound natural hazards likeEl Ninoevents cause high damage to society, which to manage requires reliable risk assessments. Damage modelling is a prerequisite for quantitative risk estimations, yet many procedures still rely on expert knowledge, and empirical studies investigating damage from compound natural hazards hardly exist. A nationwide building survey in Peru after theEl Ninoevent 2017 - which caused intense rainfall, ponding water, flash floods and landslides - enables us to apply data-mining methods for statistical groundwork, using explanatory features generated from remote sensing products and open data. We separate regions of different dominant characteristics through unsupervised clustering, and investigate feature importance rankings for classifying damage via supervised machine learning. Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. The slope length and steepness factor ranks high for mountains and canyons. Partial dependence plots further hint at amplified vulnerability in rural areas. An example of an empirical damage probability map, developed with a random forest model, is provided to demonstrate the technical feasibility.
Protection of natural or semi-natural ecosystems is an important part of societal strategies for maintaining biodiversity, ecosystem services, and achieving overall sustainable development. The assessment of multiple emerging land use trade-offs is complicated by the fact that land use changes occur and have consequences at local, regional, and even global scale. Outcomes also depend on the underlying socio-economic trends. We apply a coupled, multi-scale modelling system to assess an increase in nature protection areas as a key policy option in the European Union (EU). The main goal of the analysis is to understand the interactions between policy-induced land use changes across different scales and sectors under two contrasting future socio-economic pathways. We demonstrate how complementary insights into land system change can be gained by coupling land use models for agriculture, forestry, and urban areas for Europe, in connection with other world regions. The simulated policy case of nature protection shows how the allocation of a certain share of total available land to newly protected areas, with specific management restrictions imposed, may have a range of impacts on different land-based sectors until the year 2040. Agricultural land in Europe is slightly reduced, which is partly compensated for by higher management intensity. As a consequence of higher costs, total calorie supply per capita is reduced within the EU. While wood harvest is projected to decrease, carbon sequestration rates increase in European forests. At the same time, imports of industrial roundwood from other world regions are expected to increase. Some of the aggregate effects of nature protection have very different implications at the local to regional scale in different parts of Europe. Due to nature protection measures, agricultural production is shifted from more productive land in Europe to on average less productive land in other parts of the world. This increases, at the global level, the allocation of land resources for agriculture, leading to a decrease in tropical forest areas, reduced carbon stocks, and higher greenhouse gas emissions outside of Europe. The integrated modelling framework provides a method to assess the land use effects of a single policy option while accounting for the trade-offs between locations, and between regional, European, and global scales.
Monsoon systems around the world are governed by the so-called moisture-advection feedback. Here we show that, in a minimal conceptual model, this feedback implies a critical threshold with respect to the atmospheric specific humidity q(o) over the ocean adjacent to the monsoon region. If q(o) falls short of this critical value q(o)(c), monsoon rainfall over land cannot be sustained. Such a case could occur if evaporation from the ocean was reduced, e.g. due to low sea surface temperatures. Within the restrictions of the conceptual model, we estimate q(o)(c) from present-day reanalysis data for four major monsoon systems, and demonstrate how this concept can help understand abrupt variations in monsoon strength on orbital timescales as found in proxy records.
The Upper Cretaceous (Campanian-Maastrichtian) bioclastic wedge of the Orfento Formation in the Montagna della Maiella, Italy, is compared to newly discovered contourite drifts in the Maldives. Like the drift deposits in the Maldives, the Orfento Formation fills a channel and builds a Miocene delta-shaped and mounded sedimentary body in the basin that is similar in size to the approximately 350 km(2) large coarse-grained bioclastic Miocene delta drifts in the Maldives. The composition of the bioclastic wedge of the Orfento Formation is also exclusively bioclastic debris sourced from the shallow-water areas and reworked clasts of the Orfento Formation itself. In the near mud-free succession, age-diagnostic fossils are sparse. The depositional textures vary from wackestone to float-rudstone and breccia/conglomerates, but rocks with grainstone and rudstone textures are the most common facies. In the channel, lensoid convex-upward breccias, cross-cutting channelized beds and thick grainstone lobes with abundant scours indicate alternating erosion and deposition from a high-energy current. In the basin, the mounded sedimentary body contains lobes with a divergent progradational geometry. The lobes are built by decametre thick composite megabeds consisting of sigmoidal clinoforms that typically have a channelized topset, a grainy foreset and a fine-grained bottomset with abundant irregular angular clasts. Up to 30 m thick channels filled with intraformational breccias and coarse grainstones pinch out downslope between the megabeds. In the distal portion of the wedge, stacked grainstone beds with foresets and reworked intraclasts document continuous sediment reworking and migration. The bioclastic wedge of the Orfento Formation has been variously interpreted as a succession of sea-level controlled slope deposits, a shoaling shoreface complex, or a carbonate tidal delta. Current-controlled delta drifts in the Maldives, however, offer a new interpretation because of their similarity in architecture and composition. These similarities include: (i) a feeder channel opening into the basin; (ii) an excavation moat at the exit of the channel; (iii) an overall mounded geometry with an apex that is in shallower water depth than the source channel; (iv) progradation of stacked lobes; (v) channels that pinch out in a basinward direction; and (vi) smaller channelized intervals that are arranged in a radial pattern. As a result, the Upper Cretaceous (Campanian-Maastrichtian) bioclastic wedge of the Orfento Formation in the Montagna della Maiella, Italy, is here interpreted as a carbonate delta drift.
The literature contains a sizable number of publications where weather types are used to decompose climate shifts or trends into contributions of frequency and mean of those types. They are all based on the product rule, that is, a transformation of a product of sums into a sum of products, the latter providing the decomposition. While there is nothing to argue about the transformation itself, its interpretation as a climate shift or trend decomposition is bound to fail. While the case of a climate shift may be viewed as an incomplete description of a more complex behaviour, trend decomposition indeed produces bogus trends, as demonstrated by a synthetic counterexample with well-defined trends in type frequency and mean. Consequently, decompositions based on that transformation, be it for climate shifts or trends, must not be used.
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.