Unexpected M3.2 earthquake hits Brandenburg/Germany on 10/18/2024: Location, moment tensor, ShakeMap

On 18 October 2024 at 12:50 local time (10:50 UTC) an unexpected earthquake of magnitude 3.2 hit the Federal State of Brandenburg/Germany halfway between the small cities of Herzberg and Doberlug-Kirchhain. The event was clearly felt by people nearby and swiftly detected and located by SeisComP. A precise analysis of this event is important since seismicity is low and no comparable event is know in the region for the past 500 years.

This event highlights the capability of SeisComP and gempa modules for robust and rapid detection and analysis of small earthquakes, providing valuable insights to seismicity even in regions with sparse seismic networks.

We have automatically detected and processed the event in real-time using our autonomous SeisComP system enhanced by scanloc, ccloc and sceval as the fundamental processing modules for monitoring local earthquakes in a dedicated pipeline. The automatic system allowed the initial detection and location only 26 seconds after the earthquake occurred. A stable magnitude estimation of 3.2 was available after only 1 minute without any dedicated tuning for rapid amplitude measurement.

We estimate the depth of the event to be near 14 km consistently by manual and automatic solutions. However, the monitoring network is sparse in the region and the closest station, station GR.CLL of the German Regional Seismic Network at Collm observatory , is still 50 km away. Therefore, the depth estimate has significant uncertainty but we find a source depth within 11 and 16 km reasonable from inversion of arrival times.

While all automatic solutions rely on data from stations institutionally operated, for manual processing a few RaspberryShake stations could be integrated resulting in an improved azimuthal coverage.

scolv with map of the event location and details for the first automatic solution made with scanloc only 26 s after the event occurred. The solution is based on 9 early automatic arrival picks of P and S phases for which the travel times are shown in the diagram.

scolv with map of the event location and information for the last automatic solution. This solution is made up of 53 P and S phase picks for which the travel times are shown in the diagram.

scolv showing the manual solution which is very close to the automatic one. Phase arrivals have been repicked manually for a subset of the closest stations including a publicly available RaspberryShake station in Potsdam.

Waveforms due to the event viewed and manually processed in the scolv phase picker window show clear waveforms including clear P and S waves and first-motion polarities.

Initial focal mechanisms manually inferred from first-motion P-wave polarities are highly non-unique due to missing stations covering the focal sphere. An inversion of waveforms using our powerful and user-friendly scmtv for interactive moment-tensor inversion supports NW-SE normal faulting. The moment tensor has a vanishing isotropic but a large double-couple component. For inversion we used pre-computed Green’s functions sampled at 16 Hz and 3-component full waveforms windowed around P and S phases and filtered between 0.5 and 2 seconds period.

scolv showing additionally the focal mechanism inferred by moment-tensor inversion. The fault-plane solution compares well with observed P-phase first-motion polarities.

Moment tensor inversion by scmtv reveals normal faulting consistent with first-motion polarities and high double-couple but vanishing isotropic components.

Using our SIGMA module, the calculated moment tensor and GMPEs we have estimated the area within which the event was probably felt by people. With SIGMA we have also computed relevant seismic engineering parameters and compared observations with predictions by GMPEs for identifying the most suitable GMPE for this region.

Shakemap showing MMI created by our SIGMA module using our moment tensor and the GMPE by Kotha et al., 2020. Based on this calculation, the event was felt within a few kilometers distance from the epicenter.

Seismic engineering parameters were calculated for most used stations by SIGMA.