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Institute
- Institut für Geowissenschaften (187) (remove)
Various techniques are utilized by the seismological community, extractive industries, energy and geoengineering companies to identify earthquake nucleation processes in close proximity to engineering operation points. These operations may comprise fluid extraction or injections, artificial water reservoir impoundments, open pit and deep mining, deep geothermal power generations or carbon sequestration. In this letter to the editor, we outline several lines of investigation that we suggest to follow to address the discrimination problem between natural seismicity and seismic events induced or triggered by geoengineering activities. These suggestions have been developed by a group of experts during several meetings and workshops, and we feel that their publication as a summary report is helpful for the geoscientific community. Specific investigation procedures and discrimination approaches, on which our recommendations are based, are also published in this Special Issue (SI) of Journal of Seismology.
Preface to the special issue "Triggered and induced seismicity: probabilities and discrimination"
(2013)
Nowadays, an increasing amount of seismic data is collected by daily observatory routines. The basic step for successfully analyzing those data is the correct detection of various event types. However, the visually scanning process is a time-consuming task. Applying standard techniques for detection like the STA/LTAtrigger still requires the manual control for classification. Here, we present a useful alternative. The incoming data stream is scanned automatically for events of interest. A stochastic classifier, called hidden Markov model, is learned for each class of interest enabling the recognition of highly variable waveforms. In contrast to other automatic techniques as neural networks or support vector machines the algorithm allows to start the classification from scratch as soon as interesting events are identified. Neither the tedious process of collecting training samples nor a time-consuming configuration of the classifier is required. An approach originally introduced for the volcanic task force action allows to learn classifier properties from a single waveform example and some hours of background recording. Besides a reduction of required workload this also enables to detect very rare events. Especially the latter feature provides a milestone point for the use of seismic devices in alpine warning systems. Furthermore, the system offers the opportunity to flag new signal classes that have not been defined before. We demonstrate the application of the classification system using a data set from the Swiss Seismological Survey achieving very high recognition rates. In detail we document all refinements of the classifier providing a step-by-step guide for the fast set up of a well-working classification system.
The knowledge of the local soil structure is important for the assessment of seismic hazards. A widespread, but time-consuming technique to retrieve the parameters of the local underground is the drilling of boreholes. Another way to obtain the shear wave velocity profile at a given location is the inversion of surface wave dispersion curves. To ensure a good resolution for both superficial and deeper layers, the used dispersion curves need to cover a wide frequency range. This wide frequency range can be obtained using several arrays of seismic sensors or a single array comprising a large number of sensors. Consequently, these measurements are time-consuming. A simpler alternative is provided by the use of the ellipticity of Rayleigh waves. The frequency dependence of the ellipticity is tightly linked to the shear wave velocity profile. Furthermore, it can be measured using a single seismic sensor. As soil structures obtained by scaling of a given model exhibit the same ellipticity curve, any inversion of the ellipticity curve alone will be ambiguous. Therefore, additional measurements which fix the absolute value of the shear wave velocity profile at some points have to be included in the inversion process. Small-scale spatial autocorrelation measurements or MASW measurements can provide the needed data. Using a theoretical soil structure, we show which parts of the ellipticity curve have to be included in the inversion process to get a reliable result and which parts can be omitted. Furthermore, the use of autocorrelation or high-frequency dispersion curves will be highlighted. The resulting guidelines for inversions including ellipticity data are then applied to real data measurements collected at 14 different sites during the European NERIES project. It is found that the results are in good agreement with dispersion curve measurements. Furthermore, the method can help in identifying the mode of Rayleigh waves in dispersion curve measurements.
The spatial distribution of soil types is controlled by a set of environmental factors such as climate, organisms, parent material and topography as well as time and space. A change of these factors will lead to a change in the spatial distribution of soil types. In this study, we use a digital soil mapping approach to improve our knowledge about major soil type distributing factors in the steppe regions of Inner Mongolia (China) which currently undergo tremendous environmental change, e.g. climate and land use change. We use Random Forests in an effort to map Reference Soil Groups according to the World Reference Base for Soil Resources (WRB) in the Xilin River catchment. We benefit from the superior prediction capabilities of RF and additional interpretive results in order to identify the major environmental factors that control spatial patterns of soil types. The nine WRB soil groups that were identified and spatially predicted for the study area are Arenosol, Calcisol, Cambisol, Chernozem, Cryosol, Gleysol, Kastanozem, Phaeozem and Regosol.
Model and prediction performances of the RF model are high with an Out-of-Bag error of 51.6% for the model and a misclassification error for the predicted map of 28.9%. The main controlling factors of soil type distribution are land use, a set of topographic variables, geology and climate. However, land use and climate are of major importance and topography and geology are of minor importance. The visualizations of the predictions, the variable importance measures as result of RF and the comparisons of these with the spatial distribution of the environmental factors delivered additional, quantitative information of these controlling factors and revealed that intensively grazed areas are subjected to soil degradation. However, most of the area is still governed by natural soil forming processes which are driven by climate, topography and geology. Most importantly though, our study revealed that a shift towards warmer temperatures and lower precipitation regimes will lead to a change of the spatial distribution of RSGs towards steppe soils that store less carbon, i.e. a decrease of spatial extent of Phaeozems and an increase of spatial extent of Chernozems and Kastanozems.
From the Middle Eocene to Early Oligocene, the Earth experienced the most significant climatic cooling of the Cenozoic era. The Eocene-Oligocene transition (EOT) represents the culmination of this climatic cooling, leading to the onset of the Antarctic glaciation and, consequently, to the beginning of the present-day icehouse world. Whereas the response of deep-sea systems to this climate transition has been widely studied, its impact on the shallow-water carbonate realm is poorly constrained. Here, the sedimentary expression of the EOT in two shallow-marine carbonate successions (Nago and San Valentino, northern Italy) belonging to the Calcare di Nago Formation is presented. The chronostratigraphic framework was constructed by integrating litho-, bio-, and isotope-stratigraphic data (C and Sr isotopes), allowing to correlate these shallow-marine successions with pelagic sections in central Italy (Massignano), Tanzania (TOP Sites 12 and 17), and the Indian Ocean (ODP Site 744). Within several sections in northern Italy, including Nago and San Valentino, a Priabonian (Late Eocene) transgression is recorded. Oxygen isotopes of ODP Site 744 show a coeval negative shift of 0.4 parts per thousand., suggesting a glacio-eustatic origin for this transgression. In the Nago and San Valentino sections, no prominent sequence boundary has been detected that would indicate a rapid sea-level drop occurring together with the positive shift in delta O-18 defining the EOT-1 cooling event. Instead, a gradual shallowing of the depositional environment is observed. At TDP Sites 12 and 17, the EOT-1 is followed by a negative shift in delta O-18 of around 0.4 parts per thousand, which correlates with a relative deepening of the environment in the studied sections and suggests a melting pulse between EOT-1 and the Oligocene isotope event 1 (Oi-1). The positive delta O-18 shift related to the Oi-1 translates in San Valentino into a change in carbonate factory from a photozoan association dominated by larger benthic foraminifera, corals, and red algae to a heterozoan association dominated by bryozoans. The same bryozoan fades occurs in several Italian localities near the Eocene-Oligocene boundary. This fades is interpreted to represent an analogue of modern cool-water carbonates and results from a cooling pulse of at least regional scale, associated to the Oi-1 event.
Architectural analysis of the Late Cretaceous alveolinaceans of the Caribbean palaeobioprovince has made it possible to separate four genera: Praechubbina, Chubbinella gen. nov., Chubbina and Caribalveolina. The first three genera belong to the family Rhapydioninidae, while the fourth is placed in the family Alveolinidae. Two species, Praechubbina breviclaustra and P. oxchucensis sp. nov., represent the primitive genus Praechubbina, while the species cardenasensis and obesa, previously ascribed to this genus, must be reassigned respectively to Chubbinella gen. nov. and Caribalveolina. The species Chubbina jamaicensis, C. macgillavryi and C. fourcadei sp. nov. complete the inventory of Chubbina. The alveolinid genus Caribalveolina comprises two species, C. obesa and C. michaudi. Caribbean alveolinaceans include two successive assemblages. The lower assemblage is characterized by Praechubbina oxchucensis, P. brevisclaustra, Chubbinella cardenasensis and Caribalveolina obesa. The upper assemblage is represented by the genus Chubbina, with C. fourcadei, C. jamaicensis and C. macgillavryi, and Caribalveolina michaudi. The age of the lower assemblage is uncertain (probably Late CampanianEarly Maastrichtian), while the upper assemblage has been dated by strontium isotope stratigraphy as Late Maastrichtian.
Species distribution models are useful for identifying driving environmental factors that determine earthworm distributions as well as for predicting earthworm distribution patterns and abundances at different scales. However, due to large efforts in data acquisition, studies on larger scales are rare and often focus on single species or earthworms in general. In this study, we use boosted regression tree models (BRTs) for predicting the distribution of the three functional earthworm types, i.e. anecics, endogeics and epigeics, in an agricultural area in Baden-Wurttemberg (Southwest Germany).
First, we predicted presence and absence and later earthworm abundances, considering predictors depicting land management, topography, and soil conditions as well as biotic interaction by using the abundance of the other functional earthworm types. The final presence-absence models performed reasonably well, with explained deviances between 24 and 51% after crossvalidation. Models for abundances of anecics and endogeics were less successful, since the high small-scale variability and patchiness in earthworm abundance influenced the representativeness of the field measurements. This resulted in a significant model uncertainty, which is practically very difficult to overcome with earthworm sampling campaigns at the catchment scale.
Results showed that management practices (i.e. disturbances), topography, soil conditions, and biotic interactions with other earthworm groups are the most relevant predictors for spatial distribution (incidence) patterns of all three functional groups. The response curves and contributions of predictors differ for the three functional earthworm types. Epigeics are also controlled by topographic features, endogeics by soil parameters.
Sophisticated methods have been developed and become standard in analysing floods as well as for assessing flood risk. However, increasingly critique of the current standards and scientific practice can be found both in the flood hydrology community as well as in the risk community who argue that the considerable amount of information already available on natural disasters has not been adequately deployed and brought to effective use. We describe this phenomenon as a failure to synthesize knowledge that results from barriers and ignorance in awareness, use and management of the entire spectrum of relevant content, that is, data, information and knowledge. In this paper we argue that the scientific community in flood risk research ignores event-specific analysis and documentations as another source of data. We present results from a systematic search that includes an intensive study on sources and ways of information dissemination of flood-relevant publications. We obtain 186 documents that contain information on the sources, pathways, receptors and/or consequences for any of the 40 strongest trans-basin floods in Germany in the period 1952-2002. This study therefore provides the most comprehensive metadata collection of flood documentations for the considered geographical space and period. A total of 87.5% of all events have been documented, and especially the most severe floods have received extensive coverage. Only 30% of the material has been produced in the scientific/academic environment, and the majority of all documents (about 80%) can be considered grey literature (i.e. literature not controlled by commercial publishers). Therefore, ignoring grey sources in flood research also means ignoring the largest part of knowledge available on single flood events (in Germany). Further, the results of this study underpin the rapid changes in information dissemination of flood event literature over the last decade. We discuss the options and obstacles of incorporating this data into the knowledge-building process in light of the current technological developments and international, interdisciplinary debates for data curation.
The potential of weather radar observations for hydrological and meteorological research and applications is undisputed, particularly with increasing world-wide radar coverage. However, several barriers impede the use of weather radar data. These barriers are of both scientific and technical nature. The former refers to inherent measurement errors and artefacts, the latter to aspects such as reading specific data formats, geo-referencing, visualisation. The radar processing library wradlib is intended to lower these barriers by providing a free and open source tool for the most important steps in processing weather radar data for hydro-meteorological and hydrological applications. Moreover, the community-based development approach of wradlib allows scientists to share their knowledge about efficient processing algorithms and to make this knowledge available to the weather radar community in a transparent, structured and well-documented way.