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Using rapid probabilistic flow modelling to support hazard assessment during unrest crises at data-poor volcanic islands

Ailsa Naismith1, Benjamin Clarke1,2, Susanna Jenkins1, Christina Widiwijayanti1, Heruningtyas Desi Purnamasarti3

  • Affiliations: 1Earth Observatory of Singapore (EOS), Nanyang Technological University (NTU), Singapore, Singapore 2Asian School of the Environment (ASE), Nanyang Technological University (NTU), Singapore, Singapore 3Centre for Volcanology and Geological Hazard Mitigation (CVGHM), Bandung, Indonesia

  • Presentation type: Poster

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

  • Poster Board Number: 170

  • Programme No: 2.2.34

  • Theme 2 > Session 2

Abstract

Populated volcanic islands present major challenges to hazard assessment and risk management when the volcano enters a period of unrest. Their small size means settlements are often located close to the crater and within potential hazard footprints.  Volcanoes with longer quiescence pose further complexity due to scarcer knowledge of prior eruptive hazards or impacts. Sangihe Besar is a volcanic island in Indonesia whose volcano, Gunung Awu, has a history of phreatic and phreatomagmatic eruptions that have caused fatalities from volcanic flow and tsunami hazards. Awu recently entered a new period of unrest, reigniting concerns about potentially hazardous eruptive scenarios. Modelling scenarios can constrain the spatial range and intensity of associated hazards, which may subsequently inform risk reduction actions for Awu's population. However, the complexity of Awu's previous fatal eruptions (dome-lake interaction with latency) and paucity of stratigraphic data from previous eruptions complicates this undertaking. We deal with large epistemic uncertainty through an 'impacts-focused' approach, modelling column-collapse pyroclastic flows across a broad parameter space to identify the minimum eruption source parameters (ESPs) that could generate sectoral impacts. These ESPs may be linked to potential eruptive scenarios that could evolve in a future crisis. We explore how model outputs may complement existing hazard maps and overlay available exposure datasets to evaluate potential inundation of populated areas. This work demonstrates the utility of open-source models to rapidly provide preliminary probabilistic hazard assessments at data-poor volcanic islands newly in unrest.