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A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano

Author
Organization
Abstract
Although most of volcanic hazard studies focus on magmatic eruptions, volcanic hazardous events can also occur when no migration of magma can be recognized. Examples are tectonic and hydrothermal unrest that may lead to phreatic eruptions. Recent events (e.g., Ontake eruption on September 2014) have demonstrated that phreatic eruptions are still hard to forecast, despite being potentially very hazardous. For these reasons, it is of paramount importance to identify indicators that define the condition of nonmagmatic unrest, in particular for hydrothermal systems. Often, this type of unrest is driven by movement of fluids, requiring alternative monitoring setups, beyond the classical seismic-geodetic-geochemical architectures. Here we present a new version of the probabilistic BET (Bayesian Event Tree) model, specifically developed to include the forecasting of nonmagmatic unrest and related hazards. The structure of the new event tree differs from the previous schemes by adding a specific branch to detail nonmagmatic unrest outcomes. A further goal of this work consists in providing a user-friendly, open-access, and straightforward tool to handle the probabilistic forecast and visualize the results as possible support during a volcanic crisis. The new event tree and tool are here applied to Kawah Ijen stratovolcano, Indonesia, as exemplificative application. In particular, the tool is set on the basis of monitoring data for the learning period 2000-2010, and is then blindly applied to the test period 2010-2012, during which significant unrest phases occurred.
Keywords
volcanic unrest and hazard quantification, magmatic and hydrothermal systems, real time analysis, CRATER LAKE, PROBABILISTIC HAZARD, TEPHRA FALLOUT, NEW-ZEALAND, COSTA-RICA, LONG-TERM, BET-EF, ERUPTION, INDONESIA, GEOCHEMISTRY

Citation

Please use this url to cite or link to this publication:

MLA
Tonini, Roberto et al. “A New Bayesian Event Tree Tool to Track and Quantify Volcanic Unrest and Its Application to Kawah Ijen Volcano.” GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS 17.7 (2016): 2539–2555. Print.
APA
Tonini, R., Sandri, L., Rouwet, D., Caudron, C., & Marzocchi, W. (2016). A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano. GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS, 17(7), 2539–2555.
Chicago author-date
Tonini, Roberto, Laura Sandri, Dmitri Rouwet, Corentin Caudron, and Warner Marzocchi. 2016. “A New Bayesian Event Tree Tool to Track and Quantify Volcanic Unrest and Its Application to Kawah Ijen Volcano.” Geochemistry Geophysics Geosystems 17 (7): 2539–2555.
Chicago author-date (all authors)
Tonini, Roberto, Laura Sandri, Dmitri Rouwet, Corentin Caudron, and Warner Marzocchi. 2016. “A New Bayesian Event Tree Tool to Track and Quantify Volcanic Unrest and Its Application to Kawah Ijen Volcano.” Geochemistry Geophysics Geosystems 17 (7): 2539–2555.
Vancouver
1.
Tonini R, Sandri L, Rouwet D, Caudron C, Marzocchi W. A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano. GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS. 2016;17(7):2539–55.
IEEE
[1]
R. Tonini, L. Sandri, D. Rouwet, C. Caudron, and W. Marzocchi, “A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano,” GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS, vol. 17, no. 7, pp. 2539–2555, 2016.
@article{8541418,
  abstract     = {Although most of volcanic hazard studies focus on magmatic eruptions, volcanic hazardous events can also occur when no migration of magma can be recognized. Examples are tectonic and hydrothermal unrest that may lead to phreatic eruptions. Recent events (e.g., Ontake eruption on September 2014) have demonstrated that phreatic eruptions are still hard to forecast, despite being potentially very hazardous. For these reasons, it is of paramount importance to identify indicators that define the condition of nonmagmatic unrest, in particular for hydrothermal systems. Often, this type of unrest is driven by movement of fluids, requiring alternative monitoring setups, beyond the classical seismic-geodetic-geochemical architectures. Here we present a new version of the probabilistic BET (Bayesian Event Tree) model, specifically developed to include the forecasting of nonmagmatic unrest and related hazards. The structure of the new event tree differs from the previous schemes by adding a specific branch to detail nonmagmatic unrest outcomes. A further goal of this work consists in providing a user-friendly, open-access, and straightforward tool to handle the probabilistic forecast and visualize the results as possible support during a volcanic crisis. The new event tree and tool are here applied to Kawah Ijen stratovolcano, Indonesia, as exemplificative application. In particular, the tool is set on the basis of monitoring data for the learning period 2000-2010, and is then blindly applied to the test period 2010-2012, during which significant unrest phases occurred.},
  author       = {Tonini, Roberto and Sandri, Laura and Rouwet, Dmitri and Caudron, Corentin and Marzocchi, Warner},
  issn         = {1525-2027},
  journal      = {GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS},
  keywords     = {volcanic unrest and hazard quantification,magmatic and hydrothermal systems,real time analysis,CRATER LAKE,PROBABILISTIC HAZARD,TEPHRA FALLOUT,NEW-ZEALAND,COSTA-RICA,LONG-TERM,BET-EF,ERUPTION,INDONESIA,GEOCHEMISTRY},
  language     = {eng},
  number       = {7},
  pages        = {2539--2555},
  title        = {A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano},
  url          = {http://dx.doi.org/10.1002/2016gc006327},
  volume       = {17},
  year         = {2016},
}

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