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Here we assess the potential implementation of earthquake early warning (EEW) across Europe, where there is a clear need for measures that mitigate seismic risk. EEW systems consist of seismic networks and mathematical models/algorithms capable of real-time data telemetry that alert stakeholders (e.g., civil-protection authorities, the public) to an earthquake's nucleation seconds before shaking occurs at target sites. During this time, actions can be taken that might decrease detrimental impacts. We investigate distributions of EEW lead times available across various parts of the Euro-Mediterranean region, based on seismicity models and seismic network density. We then determine the potential usefulness of these times for EEW purposes by defining their spatial relationship with population exposure, seismic hazard, and an alert accuracy proxy, using well-established earthquake-engineering tools for measuring the impacts of earthquakes. Our mapped feasibility results show that, under certain conditions, EEW could be effective for some parts of Europe. The viability of earthquake early warning (EEW) in Europe is highly dependent on the magnitude of the ongoing earthquake and the ground-shaking threshold for alert issuance. The potential effectiveness of EEW is highest for Turkey, Italy, and Greece. [ABSTRACT FROM AUTHOR]

This paper presents a geospatial methodology for zoning the earthquake-induced soil liquefaction risk at a continental scale and set-up in a Geographic Information System (GIS) environment by coupling data-driven and knowledge-driven approaches. It is worth mentioning that liquefaction is a phenomenon of soil instability occurring at a very local spatial scale; thus, the mega-zonation of liquefaction risk at a continental scale is a hard facing challenge. Since the risk from natural disasters is the convolution of hazard, vulnerability, and exposure, the liquefaction risk mapping is based on the combination of geospatial explanatory variables, available at the continental scale, of the previously listed three assumed independent random variables. First, by applying a prediction model calibrated for Europe, the probability of liquefaction is mapped for the whole continent. Then, the Analytical Hierarchy Process (AHP) is adopted to identify areas that have a high risk of liquefaction, taking into account proxy data for exposure. The maps are computed for different levels of severity of ground shaking specified by three return periods (i.e., 475, 975, and 2475 years). A broad variety of stakeholders would benefit from the outcomes of this study, such as civil protection organizations, insurance and re-insurance companies, and infrastructure operators. [ABSTRACT FROM AUTHOR]