Integration of stochastic models for long-term eruption forecasting into a Bayesian event tree scheme: a basis method to estimate the probability of volcanic unrest

2013 ◽  
Vol 75 (2) ◽  
Author(s):  
Alexander Garcia-Aristizabal ◽  
Jacopo Selva ◽  
Eisuke Fujita
Keyword(s):  
Stochastic Models ◽  
Event Tree ◽  
Eruption Forecasting ◽  
Volcanic Unrest ◽  
Bayesian Event Tree ◽  
Basis Method

Bayesian event tree for eruption forecasting (BET_EF) at Vesuvius, Italy: a retrospective forward application to the 1631 eruption

2009 ◽  
Vol 71 (7) ◽  
pp. 729-745 ◽  
Author(s):  
Laura Sandri ◽  
Emanuela Guidoboni ◽  
Warner Marzocchi ◽  
Jacopo Selva
Keyword(s):  
Event Tree ◽  
Eruption Forecasting ◽  
Bayesian Event Tree

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

2016 ◽  
Vol 17 (7) ◽  
pp. 2539-2555 ◽  
Author(s):  
Roberto Tonini ◽  
Laura Sandri ◽  
Dmitri Rouwet ◽  
Corentin Caudron ◽  
Warner Marzocchi ◽  
...  
Keyword(s):  
Event Tree ◽  
Volcanic Unrest ◽  
Bayesian Event Tree ◽  
Kawah Ijen

Probabilistic Tephra Hazard Assessment of Campi Flegrei, Italy

2021 ◽  
Author(s):  
Beatriz Martínez Montesinos ◽  
Manuel Titos ◽  
Laura Sandri ◽  
Sara Barsotti ◽  
Giovanni Macedonio ◽  
...  
Keyword(s):  
Hazard Assessment ◽  
Wide Spectrum ◽  
Numerical Code ◽  
Campi Flegrei ◽  
Computational Domain ◽  
Event Tree ◽  
Hazard Maps ◽  
Event Tree Analysis ◽  
Short And Long Term

<p>Campi Flegrei is an active volcano located in one of the most densely inhabited areas in Europe and under high-traffic air routes. There, the Vesuvius Observatory’s surveillance system, which continuously monitors volcanic seismicity, soil deformations and gas emissions, highlights some variations in the state of the volcanic activity. It is well known that fragmented magma injected into the atmosphere during an explosive volcanic eruption poses a threat to human lives and air-traffic. For this reason, powerful tools and computational resources to generate extensive and high-resolution hazard maps taking into account a wide spectrum of events, including those of low probability but high impact, are important to provide decision makers with quality information to develop short- and long- term emergency plans. To this end, in the framework of the Center of Excellence for Exascale in Solid Earth (ChEESE), we show the potential of HPC in Probabilistic Volcanic Hazard Assessment. On the one hand, using the ChEESE's flagship Fall3D numerical code and taking advance of the PRACE-awarded resources at CEA/TGCC-HPC facility in France, we perform thousands of simulations of tephra deposition and airborne ash concentration at different flight levels exploring the natural variability and uncertainty on the eruptive conditions on a 3D-grid covering a 2 km-resolution 2000 km x 2000 km computational domain. On the other hand, we create short- and long-term workflows, by updating current Bayesian-Event-Tree-Analysis-based prototype tools, to make them capable of analyze the large amount of information generated by the Fall3D simulations that finally gives rise to the hazard maps for Campi Flegrei.</p>

scholarly journals A method for multi-hazard mapping in poorly known volcanic areas: an example from Kanlaon (Philippines)

2013 ◽  
Vol 13 (8) ◽  
pp. 1929-1943 ◽  
Author(s):  
M. Neri ◽  
G. Le Cozannet ◽  
P. Thierry ◽  
C. Bignami ◽  
J. Ruch
Keyword(s):  
Land Use Planning ◽  
Volcanic Hazards ◽  
Mapping Method ◽  
Hazard Mapping ◽  
Hazard Map ◽  
Event Tree ◽  
Planning Decisions ◽  
Civil Defence ◽  
Term Data

Abstract. Hazard mapping in poorly known volcanic areas is complex since much evidence of volcanic and non-volcanic hazards is often hidden by vegetation and alteration. In this paper, we propose a semi-quantitative method based on hazard event tree and multi-hazard map constructions developed in the frame of the FP7 MIAVITA project. We applied this method to the Kanlaon volcano (Philippines), which is characterized by poor geologic and historical records. We combine updated geological (long-term) and historical (short-term) data, building an event tree for the main types of hazardous events at Kanlaon and their potential frequencies. We then propose an updated multi-hazard map for Kanlaon, which may serve as a working base map in the case of future unrest. The obtained results extend the information already contained in previous volcanic hazard maps of Kanlaon, highlighting (i) an extensive, potentially active ~5 km long summit area striking north–south, (ii) new morphological features on the eastern flank of the volcano, prone to receiving volcanic products expanding from the summit, and (iii) important riverbeds that may potentially accumulate devastating mudflows. This preliminary study constitutes a basis that may help local civil defence authorities in making more informed land use planning decisions and in anticipating future risk/hazards at Kanlaon. This multi-hazard mapping method may also be applied to other poorly known active volcanoes.

Integrated Electricity–Gas Operations Planning in Long-term Hydroscheduling Based on Stochastic Models

2010 ◽  
pp. 149-175 ◽  
Author(s):  
B. Bezerra ◽  
L. A. Barroso ◽  
R. Kelman ◽  
B. Flach ◽  
M. L. Latorre ◽  
...  
Keyword(s):  
Stochastic Models ◽  
Operations Planning

A Theory of the Decreasing Term Structure of Discount Rates

2012 ◽  
Author(s):  
Christian Gollier
Keyword(s):  
Economic Growth ◽  
Random Walk ◽  
Term Structure ◽  
Stochastic Models ◽  
Driving Force ◽  
Parametric Uncertainty ◽  
Statistical Dependence ◽  
Discount Rates ◽  
Individual Preferences

This chapter aims to provide a unified theoretical foundation to the term structure of discount rates. To do this the chapter develops a benchmark model based on two assumptions: individual preferences toward risk, and the nature of the uncertainty over economic growth. Previously, it was shown that constant relative risk aversion, combined with a random walk for the growth of log consumption, yields a flat term structure for efficient discount rates. In this chapter, these two assumptions are relaxed by using a stochastic dominance approach. Stochastic models of economic growth with mean-reversion, Markov switches, and parametric uncertainty all exhibit some forms of positive statistical dependence of successive growth rates. Because this tends to magnify the long-term risk, it is the driving force of the decreasing nature of the term structure.

A long-term volcanic hazard event tree for Teide-Pico Viejo stratovolcanoes (Tenerife, Canary Islands)

2008 ◽  
Vol 178 (3) ◽  
pp. 543-552 ◽  
Author(s):  
J. Martí ◽  
W.P. Aspinall ◽  
R. Sobradelo ◽  
A. Felpeto ◽  
A. Geyer ◽  
...  
Keyword(s):  
Canary Islands ◽  
Volcanic Hazard ◽  
Event Tree

scholarly journals Computing for Numeracy: How Safe is Your COVID-19 Social Bubble?

Numeracy ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Charles Connor
Keyword(s):  
Small Groups ◽  
Assisted Living ◽  
Event Tree ◽  
Risk Of Infection ◽  
Assisted Living Facility ◽  
Web Based ◽  
The Social ◽  
Bayesian Event Tree

The COVID-19 pandemic has led many people to form social bubbles. These social bubbles are small groups of people who interact with one another but restrict interactions with the outside world. The assumption in forming social bubbles is that risk of infection and severe outcomes, like hospitalization, are reduced. How effective are social bubbles? A Bayesian event tree is developed to calculate the probabilities of specific outcomes, like hospitalization, using example rates of infection in the greater community and example prior functions describing the effectiveness of isolation by members of the social bubble. The probabilities are solved for two contrasting examples: members of an assisted living facility and members of a classroom, including their teacher. A web-based calculator is provided so readers can experiment with the Bayesian event tree and learn more about these probabilities by modeling their own social bubble.

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