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Journal Article

Dynamische und hochauflösende Aktivitätsvorhersagen und Folgenabschätzung von Erdbeben

Authors
/persons/resource/ds

Schorlemmer,  Danijel
Vol. 6, Issue 1 (2016), GFZ Journal 2016, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
2.6 Seismic Hazard and Stress Field, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/hainzl

Hainzl,  Sebastian
Vol. 6, Issue 1 (2016), GFZ Journal 2016, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
2.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/zang

Zang,  Arno
Vol. 6, Issue 1 (2016), GFZ Journal 2016, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
2.6 Seismic Hazard and Stress Field, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/fcotton

Cotton,  Fabrice
Vol. 6, Issue 1 (2016), GFZ Journal 2016, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
2.6 Seismic Hazard and Stress Field, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

External Ressource
Fulltext (public)

GFZ_syserde.06.01.06.pdf
(Publisher version), 477KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Schorlemmer, D., Hainzl, S., Zang, A., Cotton, F. (2016): Dynamische und hochauflösende Aktivitätsvorhersagen und Folgenabschätzung von Erdbeben. - System Erde, 6, 1, 38-43.
https://doi.org/10.2312/GFZ.syserde.06.01.6


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_1504384
Abstract
The nucleation of earthquakes and their seismic waves cannot be predicted in a deterministic sense. However probabilistic hazard and risk estimations can be conducted which help to increase the preparedness and reduce the vulnerability of societies. Those estimations are based on the rapidly growing number of empirical earthquake data recorded by seismic networks or known from historical or geological studies, which show that earthquakes are not randomly occurring. They typically occur clustered in space and time with specific characteristics such as the Gutenberg-Richter law for the frequency-magnitude distribution. Seismicity models have to account for earthquake interactions to avoid erroneous estimations of the activity level and spatial distribution of future activity. Additionally, the vulnerability of societies is changing with with time, because of the dynamic reconstruction and growth of cities in earthquake-prone regions. Thus new sophisticated models, strategies, and methods have to be developed and tested for all components of the earthquake risk chain to improve our probabilistic hazard and risk estimations.