Datensatz

Zusammenfassung

The Early-Warning and Rapid Impact Assessment with real-time GNSS in the Mediterranean (EWRICA) is a federal Ministry of Education and Research funded project (funding period: 2020-2023) that aims to develop fast kinematic and point source inversion and modeling tools combining GNSS-based near field data with traditional broadband ground velocity and accelerometer data. Fast and robust estimates of seismic source parameters are essential for reliable hazard estimates, e.g. in the frame of tsunami early warning. Hence, EWRICA aims for the development and testing of new real time seismic source inversion techniques based on local surface displacements. The resulting methods shall be applied for tsunami early warning purposes in the Mediterranean area. In this framework, this repository is a suite of four packages that can be used and combined in different ways and are ewricacore, ewricasiria, ewricagm and ewricawebapp. These four packages can be deployed in a docker container (see instructions below) to demonstrate a possible output of Early-Warning and Rapid Impact Assessment. In the Docker, a probabilistic earthquake source inversion report (ewricasiria) and a Neural network based Shake map (ewricagm) are generated for two past earthquakes whose data (event and waveform) is continuously served by GEOFON servers at regualr intervals to produce and test a real case scenario. The whole workflow is managed by ewricacore, a central unit of work that first fetches the waveform data via the seedlink protocol and event data via event bus or FDSN web service, then collects and cuts waveforms segments according to a custom configuration, and eventually triggers custom processing (ewricasiria and ewricagm in the docker, but any processing can be implemented) whenever configurable conditions are met. The final package, ewricawebapp is a web-based graphical user interface that can be opened in your local browser or deployed on your web server in order to visualize and check all output produced by the docker workflow in form of HTML pges, images and data in various formats (e.g., JSON, log text files).