Effusion rate trends at Etna and Krafla and their implications for eruptive mechanisms

Abstract

Using effusion rates obtained from ground- and satellite-based data we build a data set of 381 effusion rate measurements during effusive activity at Etna and Krafla between 1980 and 1999. This allows us to construct detailed effusion rate curves for six fissure-fed eruptions at Etna and Krafla and four summit-fed eruptions at Etna. These define two trends: Type I and II. Type I trends have effusion rates that rise rapidly to an initial peak, before declining more slowly, resulting in an exponential decrease in eruption rate and declining growth in cumulative volume. Type II trends are characterised by steady effusion and eruption rates, and hence a linear increase in cumulative volume. The former is typical of fissure eruptions and can be explained by tapping of an enclosed, pressurised system. The latter are typical of persistent Etnean summit eruptions, plus one persistent effusive eruption at Stromboli (1985–1986) examined here, and can be explained by overflow of the time-averaged magma supply.We use our effusion rate data to assess the magma balance at Etna (1980–1995) and Krafla (1975–1984). Between 1980 and 1995, Etna was supplied at a time-averaged rate of 6.8±2.3m3s−1 of which 13% was erupted. At Krafla 817±30×106m3 was erupted and intruded during 1975–1984, and the ratio of erupted to intruded volume was 0.3. At Etna there is evidence for intrusion of the unerupted magma within and beneath the edifice, as well as storage in the central magma column. At Krafla unerupted magma was intruded into a rift zone, but an increasing proportion of the supply was erupted from 1980 onwards, a result of the rift zone capacity being reached. Magma intruded prior to an eruptive event may also be entrained and/or pushed out during eruption to contribute to the initial high effusion rate phases of Type I events.The detail in our effusion rate curves was only possible using a thermal approach which estimates effusion rates using satellite data. We look forward to analysing satellite-derived effusion rate trends in real-time using data from current and soon-to-be-launched sensors.