Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
NH2.5 | Analysis of submarine volcanic activity and relative effects by means of advanced monitoring systems
Analysis of submarine volcanic activity and relative effects by means of advanced monitoring systems
Convener: Francesco Marchese | Co-conveners: Simon Plank, Emanuele Ciancia
The recent eruptions of Fukutoku-Oka-no-ba (Japan) and Hunga Tonga-Hunga Ha’apai (Tonga) volcano, which triggered a catastrophic tsunami due to the collapse of the Hunga caldera in January 2022, have shown that submarine volcanoes cannot only pose a serious threat to the population and infrastructure of the coastal areas in their immediate neighborhood but also a high potential risk to regions far away from the source. Submarine volcanoes located in shallow waters may also inject significant amount of volcanic ash and gases in the atmosphere. However, the operational monitoring of submarine volcanoes remains a challenge because of the lack of systematic in-situ measurements, such as water sampling for physio-chemical parameters (e.g., turbidity, sea surface temperature, chemical composition, salinity). Moreover, although permanent arrays (e.g., seismic networks) can provide continuous information on the volcanic processes in the deep ocean, they are generally located at regional distances from the sub-marine volcanoes. An effective and continuous monitoring of underwater volcanic activity is essential for recognizing possible signs of unrest that could prelude to potentially destructive tsunamigenic eruptions.
This session focuses on methods (e.g., satellite data-based identification and mapping of discolored water or floating pumice rafts) and systems (e.g., seismometer and hydroacoustic arrays) developed for analyzing submarine volcanic activity. Contributions to the monitoring of recent submarine eruptions (e.g., Anak-Krakatau, Late’iki, Home Reef, Kavachi) and relative effects are welcome, with a particular focus on results achieved by using multidisciplinary, integrated and innovative approaches of data analysis (e.g., statistical and machine learning techniques).