The main purpose of this software is to provide a graphically supported computation of long-term probabilities of volcanic hazardous phenomena (i.e., lava flows, tephra fall, pyroclastic flows, lahars, etc.) through the Bayesian Event Tree model for Volcanic Hazard (BET_VH, Marzocchi et al., 2010). The model represents a flexible tool to provide probabilities of any specific event at which we are interested in, by merging all the available information, such as models, a priori beliefs, and past data. It is mainly based on a Bayesian procedure, in order to quantify the aleatory and epistemic uncertainty characterizing the impact of volcanic eruptions in terms of hazard assessment. The method deals only with long-term forecasting, therefore in principle it can be useful for land use planning. This version introduces as main outputs the Hazard Curves (HC), showing the exceeding probability as function of the chosen intensity measure (e.g., the tephra load in kg/m2). The HC are provided together with their uncertainties (percentiles) through Bayesian inference and the user can explore the hazard results visualizing both Probability and Hazard Maps. 

For further information you can visit the group at https://vhub.org/groups/webet

References:

Marzocchi W., Sandri L., Selva J. (2010) BETVH: a probabilistic tool for long-term volcanic hazard assessment, Bull. Volcanol., 72, 705-716, DOI:10.1007/s00445-010-0357-8

Tonini R., Sandri L., Thompson M. A. (2015) PyBetVH: a Python tool for probabilistic volcanic hazard assessment and for generation of Bayesian hazard curves and maps, Comput. Geosci., doi:10.1016/j.cageo.2015.02.017

Researchers should cite this work as follows:

• Roberto Tonini; Laura Sandri; Jacopo Selva; Warner Marzocchi (2016), "PyBetVH," https://theghub.org/resources/betvh.

  BibTex | EndNote

1. Bayesian inference
2. bet_vh
3. hazard curves
4. hazard maps
5. probability map
6. pvha
7. volcanic hazard assessment