Other language confidence: 0.9860087736822816
Greece is Europe’s most seismically active nation, as it is being deformed by an active subduction system and one of the world’s fastest-spreading rifts. Onshore active faults pose seismic hazard that cannot be reliably assessed in the absence of a comprehensive map of potential earthquake sources. Here, we use high-resolution Digital Elevation Models (DEMs), in conjunction with hillshades and slope models, to map and characterise faults in Greece at a scale of 1:25000. The Active Faults Greece (AFG) database records a total of 3815 fault-traces assigned to 892 interpreted faults. Of the AFG traces, 53% were mapped here for the first time, with their geometries and slip-sense constrained by displacement of landscape features. AFG includes >2000 active and 1632 probably active fault-traces, while 30 traces result from historic surface-rupturing earthquakes since 464 BC. About 57% of faults exhibit strong depositional control (DC) on sedimentation patterns, with active faults being characterised by approximately equal numbers of sharp (32%), moderate (29%) and rounded (29%) scarps. AFG is the first fault database in Greece generated using nationwide interpretation of geomorphology and has applications in paleoseismology, seismic-hazard assessment, mineral-resources exploration, and resilience planning. Data Access: - Download archive version via GFZ Data Services (upper left) - Web-Map Server: https://experience.arcgis.com/experience/a6c85b1edf9d4d17a3f01a70cef6d2b2 - GIS Users: https://services2.arcgis.com/T7iULq65Kp9Elquk/arcgis/rest/services/Active_Faults_Greece/FeatureServer - Layerfiles for use in ArcGIS Pro and QGIS: https://noaig.maps.arcgis.com/sharing/rest/content/items/4b93c25b931744dabc4851abf9c8ae38/data
This package provides a set of tools to read, manipulate and convert seismic waveforms generated by DAS systems. In particular, the ones saved in TDMs format: - dasconv: This utility lets you convert and manipulate seismic waveforms in TDMs format and export them into MiniSEED. - tdmsws (experimental) - a stand-alone implementation of the FDSN Dataselect web service, which is able to serve miniSEED data extracted from a folder with TDMS files.
This data collection contains inundation maps in Lima and Callao (Peru) based on tsunami simulations with two numerical wave propagation and run-up models (Tsunami-HySEA and TsunAWI) for a range of Manning values between 0.015 and 0.06, where constant values were applied in the whole model domain. The simulations were carried out in the framework of the RIESGOS project (https://www.riesgos.de/en/). The source is based on the historic event from October 1746, the parameters are derived from the study Jimenez et al. (2013). The moment magnitude is prescribed to Mw 9.0, the source area is split into five sub-faults, with inhomogeneous slip distribution and static deformation at time zero (this means no kinematic source model). The flow depth distribution in Lima/Callao after four hours simulation time obtained by the two models is interpolated to raster files and provided in geoTIFF format.
This dataset presented herein originates from the JAGUARS (The Japanese German Underground Acoustic Emission Research in South Africa) project, which took place from 2007 to 2009 in Mponeng Gold Mine, South Africa. Project partners included Ritsumeikan University, Earthquake Research Institute University of Tokyo and Tohuku University in Japan, the German Research Center for Geosciences Potsdam and Gesellschaft für Materialprüfung und Geophysik GMuG mbH in Germany, as well as the Council for Scientific and Industrial Research in Johannesburg, Seismogen CC in Cartonville, Anglo Gold Ashanti Ltd and the Institute of Mining Seismology in the Republic of South Africa. This publication forms part of the Geo-INQUIRE initiative (HORIZON-INFRA-2021-SERV-01 call, project number 101058518). It is cross-referenced on the EPISODES Platform (https://episodesplatform.eu/?lang=en#episode:JAGUARS (not yet existing)), which is managed by the EPOS TCS AH (European Plate Observing System Thematic Core Service Anthropogenic Hazards). Within the EPISODES Platform, the datasets are consolidated into an “episode” titled “JAGUARS: Mining induced picoseismicity associated with gold mining”. The EPISODES Platform offers open access to the integrated research infrastructures of the EPOS TCS AH, enabling users to download data and utilize a range of basic online visualization tools to graphically represent and process the datasets directly within their personal workspace.
As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2023-001_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
This version of Quakeledger (V.1.0) is a Python3 program that can also be used as a WPS (Web Processing Service). It returns the available earthquake events contained within a given local database (so called catalogue) that must be customised beforehand (e.g. historical, expert and/or stochastic events). This is a rewrite from: https://github.com/GFZ-Centre-for-Early-Warning/quakeledger and https://github.com/bpross-52n/quakeledger. In these original codes, an earthquake catalogue had to be initially provided in .CSV format. The main difference with this version is that, this code is refactored and uses a SQLITE database. The user can find the parser code in: “quakeledger/assistance/import_csv_in_sqlite.py”
SEVA is a scalable exploration tool that supports users to conduct change detection based on optical Sentinel-2 satellite observations. It supports the following essential steps of change detection: a) exploration and selection of optical satellite images to recognize proper data for the current application scenario, b) automated extraction of changes from the optical satellite images, c) analysis of errors and d) assessment and interpretation of the extracted changes.
This data set includes the results of digital image correlation of ten brittle-viscous experiments on crustal extension and four benchmark experiments performed at the Tectonic Modelling Lab of the University of Bern (UB). The experiments demonstrate the differences in rift development in orthogonal versus rotation extension. Detailed descriptions of the experiments and monitoring techniques can be found in Zwaan et al. (2019) to which this data set is supplementary. Additional background information concerning the general modelling approach are available in Zwaan et al. (2016).. The data presented here consist of movies displaying digital image correlation (DIC) derived surface and internal displacement fields as well as profiles of the lateral cumulative surface displacements.Digital photographs of the experimental surface and digital image cross section of the computed CT-scans were analyzed with DIC (Adam et al., 2005, 2013) techniques to quantify displacements in the image plane at high precision (<0.1 mm). DIC was undertaken with the software DaVis 8.0 (LaVision) applying 2D-DIC (FFT-legacy) multipass processing with a final interrogation window size of 32x32 (CT: 12x12) pixels and 50% (CT: 25%) overlap.
The River Plume Workflow is part of the Flood Event Explorer (FEE, Eggert et al., 2022), developed at the GFZ German Research Centre for Geosciences in close collaboration with Helmholtz-Zentrum Hereon. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). The focus of the River Plume Workflow is the impact of riverine flood events on the marine environment. At the end of a flood event chain, an unusual amount of nutrients and pollutants is washed into the North Sea, which can have consequences, such as increased algae blooms. The workflow aims to enable users to detect a river plume in the North Sea and to determine its spatio-temporal extent. Identifying river plume candidates can either happen manually in the visual interface or also through an automatic anomaly detection algorithm, using Gaussian regression. In both cases a combination of observational data, namely FerryBox transects and satellite data, and model data are used. Once a river plume candidate is found, a statistical analysis supplies additional detail on the anomaly and helps to compare the suspected river plume to the surrounding data. Simulated trajectories of particles starting on the FerryBox transect at the time of the original observation and modelled backwards and forwards in time help to verify the origin of the river plume and allow users to follow the anomaly across the North Sea. An interactive map enables users to load additional observational data into the workflow, such as ocean colour satellite maps, and provides them with an overview of the flood impacts and the river plume’s development on its way through the North Sea. In addition, the workflow offers the functionality to assemble satellite-based chlorophyll observations along model trajectories as a time series. They allow scientists to understand processes inside the river plume and to determine the timescales on which these developments happen. For example, chlorophyll degradation rates in the Elbe river plume are currently investigated using these time series. The workflow's added value lies in the ease with which users can combine observational FerryBox data with relevant model data and other datasets of their choice. Furthermore, the workflow allows users to visually explore the combined data and contains methods to find and highlight anomalies. The workflow’s functionalities also enable users to map the spatio-temporal extent of the river plume and investigate the changes in productivity that occur in the plume. All in all, the River Plume Workflow simplifies the investigation and monitoring of flood events and their impacts in marine environments.
The Digital Earth Flood Event Explorer supports geoscientists and experts to analyse flood events along the process cascade event generation, evolution and impact across atmospheric, terrestrial, and marine disciplines. It applies the concept of scientific workflows and the component-based Data Analytics Software Framework (DASF, Eggert and Dransch, 2021) to an exemplary showcase. It aims at answering the following geoscientific questions: - How does precipitation change over the course of the 21st century under different climate scenarios over a certain region? - What are the main hydro-meteorological controls of a specific flood event? - What are useful indicators to assess socio-economic flood impacts? - How do flood events impact the marine environment? - What are the best monitoring sites for upcoming flood events? The Flood Event Explorer developed scientific workflows for each geoscientific question providing enhanced analysis methods from statistics, machine learning, and visual data exploration that are implemented in different languages and software environments, and that access data form a variety of distributed databases. The collaborating scientists are from different Helmholtz research centers and belong to different scientific fields such as hydrology, climate-, marine-, and environmental science, and computer- and data science. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/).
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