PyBetUnrest implements the version of the probabilistic model BET (Bayesian Event Tree), called BET_UNREST, specifically developed to include the forecasting of non-magmatic unrest and related hazards, by adding a dedicated "non-magmatic" branch to the event tree's structure. Probabilities are calculated at each node by merging prior models and past data with new incoming monitoring data, and the results can be updated any time new data have been collected. Monitoring data are weighted through pre-defined thresholds of anomaly, as in the previous only magmatic tool called BET_EF (BET for Eruption Forecasting, Marzocchi et al., 2008). PyBetUnrest is equipped with a Graphical User Interface aiming to create a user-friendly, open-access, and straightforward tool to support short-term volcanic forecasting.

A general user guide for all PyBet tools can be found at https://vhub.org/wiki/PyBetToolsUserGuide and more datails on the PyBetUnrest tool can be found in Tonini et al. (2016). PyBetUnrest has been developed in the frame of the FP7 VUELCO project.

References

Marzocchi W., Sandri L., Selva J. (2008) BET_EF: a probabilistic tool for long- and short-term eruption forecasting. Bull Volcanol., 70:623–632. doi:10.1007/s00445-007-0157-y

Tonini R., Sandri L., Rouwet D., Corentin C., Marzocchi W., Suparjan (2016) A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano, Geochem. Geophys. Geosyst., 17, doi: 10.1002/2016GC006327.

Researchers should cite this work as follows:

• Roberto Tonini; Laura Sandri; dmitri rouwet (2016), "PyBetUnrest," https://theghub.org/resources/betunrest.

  BibTex | EndNote

1. Bayesian inference
2. BET_UNREST
3. eruption forecasting
4. magmatic unrest
5. non-magmaticunrest
6. probabilistic analysis