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FEVER: Forecasting Eruptions at Volcanoes after Extended Repose

Christopher Kilburn1, Eric Newland1, Matias Clunes2, Carmen Solana 2, Philip Benson1, Erouscilla Joseph3, Giuseppe De Natale4

  • Affiliations: 1UCL Hazard Centre, Department of Earth Sciences, UCL, London, UK; 2School of the Environment and Life Sciences, University of Portsmouth, Portsmouth, UK; 3Seismic Research Centre, University of the West Indies, Trinidad and Tobago; 4INGV-Sezione di Napoli, Osservatorio Vesuviano, Napoli, Italy.

  • Presentation type: Poster

  • Presentation time: Monday 16:30 - 18:30, Room Poster Hall

  • Poster Board Number: 260

  • Programme No: 2.4.36

  • Theme 2 > Session 4

Abstract

Volcanic unrest is often described as complex and highly variable, especially after a volcano has remained several centuries in repose. The description may be convenient for managing expectations about the ability to forecast eruptions, but risks promoting a mind-set that volcanic systems are too complicated to follow a shared set of pre-eruptive trends. It is also popular to apply statistical methods on a case-by-case basis to identify combinations of behaviour that may signal an eruption. The results are empirical and cannot be transferred from one volcano to another. Project FEVER takes the opposite view; that patterns of unrest can be interpreted in terms of deterministic processes and transferable between volcanoes. At volcanoes restless after extended repose, for example, magma must break open a pathway through the crust before it erupts. The fundamental mechanics of crustal rupture occurs under restricted ranges of physical conditions and these, in turn, promote repeatable and quantifiable patterns of deformation and fracture. Our philosophy is supported by new laboratory and theoretical studies of rock failure in extension. They reveal that accelerating rates of seismicity observed before eruption are consistent with progressive strain softening in crust being stretched above a zone of increasing pressure (e.g., of magma or high-temperature fluids). The rate of softening can be quantified to constrain forecasts of rupture. It has thus the potential to enhance operational procedures -- and we will test its performance through integrating our objective, physics-based criteria into current forecasting procedures that rely on probabilistic analysis.