You are here: Welcome to the CompletenessWeb

Welcome to the CompletenessWeb

The completeness of detection of seismic events is an important parameter for various studies using earthquake catalogs. This website presents the Probability-based Magnitude of Completeness (PMC) method, provides the necessary software codes to apply it, and delivers pre-computed completeness data for various seismic networks.

The figure below shows an example of the completeness level, MP, for the INGV network on 1 January 2008, including contour lines for MP=2.5 and MP=2.9.



The PMC method allows to compute the detection probabilities of seismic events for any given magnitude at any given location and time. It is solely based on empirical data, mainly the earthquake catalog including pick information. The method avoids the assumptions made in classical completeness estimate methods based on the Gutenberg-Richter distribution or in modeling approaches. Unlike the classical methods, it can also provide completeness estimates for seismically inactive regions and provide the user with very detailed completeness changes over time.

Please find a detailed description and references on the Method page.


We computed completeness evolutions for several networks that can be downloaded freely. Currently, we cover the following networks:

  • Southern California Seismic Network
  • Northern California Seismic Network
  • Italian National Seismic Network
  • Network of the OGS (Istituto Nazionale di Oceanografia e Geofisica Sperimentale)
  • Swiss Seismic Network
  • GeoNet New Zealand
  • Network of the Japan Meteorological Agency

Our completeness data webservice will provide your with data files in various formats and publication-ready figures.


We published several papers about the method and subsequent improvements. They can be found on the Documents pages. There we also make posters, presentations, and other material available for download.


Our Projects pages present in detail the PMC computations that we performed for various networks and provide guidance to reproduce our results. They also show further data and results that cannot be found in the data webservice.