Prediction of Volcanic Activity and Related Earthquakes

Prediction of volcanic activity and related earthquakes requires the identification of their precursors through multi-parametric monitoring. Significant real-time changes can indicate the imminence of an upcoming event. High-confidence identification of reactivation of magmatic activity and subsequent volcanic eruptions and associated earthquakes are best achieved within a complete probabilistic framework.

The proposed monitoring systems tested within the GEOWARN project may significantly help to identify useful precursors and therefore improve our capability to warn of volcanic hazards, impending eruptions and the probability of occurrence of large earthquakes.

In the case of a reactivation, implementation of real-time monitoring into the early warning system would then additionally permit volcanic eruption prediction (long-term, or the step from yellow to orange) or forecast (the short-term step from orange to red).

The fundamental framework of the "Volcano Early Warning System" consists of a complete geo-spatial database containing all geographic, geologic and geophysical information of the volcanic field and its underground, from which the knowledge of the volcanic behaviour emerges. This is an absolute requirement for the installation of the appropriate monitoring systems and the possibility of reliably interpreting their resulting data.

Each "Volcano Early Warning System" would need to be customized to the volcanic field and the geotectonic environment due to the high diversity from one volcano to the other. In addition to its primary early warning function, the GEOWARN system can additionally be used for volcanic eruption prediction and forecasting when connected with real-time monitoring surveillance.

The "Volcano Early Warning System" comprises five steps:

(1) Measurements (episodic and systematic monitoring);

(2) Identification of appropriate precursors (deterministic approach, based on theory, experiment, analysis and observation);

(3) Correlation analysis of precursors (statistical estimators, correlation values and error calculations);

(4) Rating and ranking of correlation values;

(5) Combination of monitoring results with baseline data (maps) and visualizations on screen.

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