IUGG (PRAGA 2015)


image

VOLCANBOX: a new software platform to minimise volcanic risk                           Stefania Bartolini, Joan Martí, Rosa Sobradelo

One of the most important tasks of modern volcanology is to minimise the risk of volcanic eruptions. Their impact can affect considerably human life and the environment. It is clear that a volcanic eruption, although it can be at the same time fascinating and impressive, presents similar or even more problems than more frequent natural events. It is possible to live near a volcanic area if we consider the benefits that volcanoes can gives us, but it is important to be aware of the existing threat and to know how to minimise the risk. Understanding the potential evolution of a volcanic crisis is crucial for designing effective mitigation strategies. In this work we present an integrated software platform specially designed to assess and manage volcanic risk, VOLCANBOX. This new platform contains user-friendly free e-tools able to be used with personal computers specifically addressed to long- and short-term hazard assessment, vulnerability analysis, decision-making, and volcanic risk management. E-tools are developed in QGIS, the more widely used free open source Geographic Information System, and are designed to be implemented before an emergency, to identify optimum mitigating actions and how these may change as new information is obtained. Furthermore, e-tools contained in the VOLCANBOX allow to identify the most appropriate probabilistic and statistical techniques for volcanological data analysis and treatment in the context of quantitative hazard and risk assessment. Forecasting volcanic eruptions and predicting the most probable scenarios are subjected to a high degree of uncertainty, which needs to be quantified and clearly explained when transmitting scientific information to decision makers. 

Keywords: Volcanic susceptibility, Hazard assessment, Vulnerability analysis, Decision making


Short-term volcanic hazard assessment through Bayesian inference: retrospective application to the Pinatubo 1991 volcanic crisis                           Joan Martí, Rosa Sobradelo

One of the most challenging aspects of managing a volcanic crisis is the interpretation of the monitoring data, so as to anticipate to the evolution of the unrest and implement timely mitigation actions. An unrest episode may include different stages or time intervals of increasing activity that may or may not precede a volcanic eruption, depending on the causes of the unrest (magmatic, geothermal or tectonic). Therefore, one of the main goals in monitoring volcanic unrest is to forecast whether or not such increase of activity will end up with an eruption, and if this is the case, how, when, and where this eruption will take place. As an alternative method to expert elicitation for assessing and merging monitoring data and relevant past information, we present a probabilistic method to transform precursory activity into the probability of experiencing a significant variation by the next time interval (i.e. the next step in the unrest), given its preceding evolution, and by further estimating the probability of the occurrence of a particular eruptive scenario combining monitoring and past data. With the 1991 Pinatubo volcanic crisis as a reference, we have developed such a method to assess short-term volcanic hazard using Bayesian inference.

Keywords: Short term forecasting, Precursors, Unrest indicators


Probabilistic approach to decision-making under uncertainty during volcanic crises: Retrospective application to the El Hierro (Spain) 2011 volcanic crisis  Joan Martí, Rosa Sobradelo, Christopher Kilburn, Carmen López

Understanding the potential evolution of a volcanic crisis is crucial to improving the design of effective mitigation strategies. This is especially the case for volcanoes close to densely-populated regions, where inappropriate decisions may trigger widespread loss of life, economic disruption and public distress. An outstanding goal for improving the management of volcanic crises, therefore, is to develop objective, real-time methodologies for evaluating how an emergency will develop and how scientists communicate with decision makers. Here we present a new model BADEMO (Bayesian Decision Model) that applies a general and flexible, probabilistic approach to managing volcanic crises. The model combines the hazard and risk factors that decision makers need for a holistic analysis of a volcanic crisis. These factors include eruption scenarios and their probabilities of occurrence, the vulnerability of populations and their activities, and the costs of false alarms and failed forecasts. The model can be implemented before an emergency, to identify actions for reducing the vulnerability of a district; during an emergency, to identify the optimum mitigating actions and how these may change as new information is obtained; and after an emergency, to assess the effectiveness of a mitigating response and, from the results, to improve strategies before another crisis occurs. As illustrated by a retrospective analysis of the 2011 eruption of El Hierro, in the Canary Islands, BADEMO provides the basis for quantifying the uncertainty associated with each recommended action as an emergency evolves, and serves as a mechanism for improving communications between scientists and decision makers.

 Keywords: Decision-making, Volcanic crises, Communicating probabilities, Expected losses

© GVB-CSIC 2015