PREEVENTS Eruption Forecasting Project

Development and testing of volcanic eruption models and forecasts through multidisciplinary data synthesis at Alaska volcanoes

Now recruiting for a database developer to join our team. Please find more details here.

Explosive volcanic eruptions pose an increasing hazard to a growing, globally connected population. Alaska has ~54 historically active volcanoes with multiple explosive eruptions per year that threaten local populations, infrastructure, and air traffic. Accurate forecasting of volcanic eruptions is challenging due to the complex and dynamic nature of volcanoes. Recent studies, however, have shown that combining multidisciplinary observations of past unrest can yield accurate forecasts of eruptions from well-monitored volcanoes. Our team at UAF has recently been awarded a National Science Foundation Prediction of and Resilience against Extreme Events (PREEVENTS) award to re-analyze and combine multidisciplinary observations of past volcanic unrest for eight Alaska volcanoes to develop a suite of eruption forecast models. These models will ultimately be provided to the Alaska Volcano Observatory (AVO) for operational use to improve AVO’s eruption forecasting capabilities and mitigate eruption hazards. We will also develop publicly available classroom modules and a distance-based continuing education course to be shared with teachers from communities near active volcanoes to help prepare the populations most directly impacted by volcanic eruptions.

This project will capitalize on the wealth of AVO data; the multidisciplinary expertise of volcano observatory scientists; and the analytical power provided by a team of graduate students, postdoctoral fellows and researchers. Research and data analysis will initially be conducted within the framework of four disciplinary themes: (1) geodesy, (2) seismology & infrasound, (3) volcanic gas geochemistry & remote sensing, and (4) petrology, geochemistry & physical volcanology, and will focus on eight recently active Alaska volcanoes (Figure 1). A graduate student cohort will work with UAF faculty, staff, postdoctoral fellows and collaborators to first analyze data within each discipline and then synthesize the data across disciplines. The multidisciplinary data will be used by two postdoctoral fellows to develop eruption forecasting models.

Figure 1: Map of Alaska’s historically active volcanoes (triangles) and the volcanoes targeted in this study. Open-system, frequently erupting target volcanoes shown in red, closed-system, intermittently erupting target volcanoes shown in blue. Maps illustrating published historical eruption deposits are shown as shaded regions. Figure modified from Mulliken et al. (2018) and Cameron et al. (2018). Figure by Katie Mulliken (now at the University of Hawaii at Hilo).

UAF Disciplinary Teams

Seismology & Infrasound

Darren Tan

Graduate Student

ptan@alaska.edu

Társilo Girona

Co Investigator

tarsilo.girona@alaska.edu

Seismic data comprises one of AVO’s monitoring pillars with over 220 stations deployed across the arc, providing rich data primed for detailed study. Most eruptive phenomena carry a distinct seismic signature suitable for eruption forecasting and modeling. Infrasound, or low frequency sound below 20 Hz, is produced when volcanic eruptions perturb the atmosphere and create sound waves. Volcano infrasound provides information on eruption processes within the shallow conduit or eruption column. Similar to seismic, different eruption styles have unique, distinctive infrasonic signatures. We will analyze the seismic and infrasound data with a set of comprehensive, automated tools utilizing modern techniques to provide data products and metrics before, during, and after eruptions from our target volcanoes.

Geodesy

Mario Angarita Vargas

Graduate Student

mfangaritasr@alaska.edu

Volcano geodesy investigates ground deformation around volcanoes, which may indicate pressure changes within volcanic systems, magma migration between them, or formation of new conduits or intrusions. In this project we will reanalyze existing GPS data and Satellite Aperature Radar (SAR) acquisitions (including new Sentinel 1A/B), and automate the (near) real-time inversion of deformation data for volcanic sources.

Volcanic Gas Geochemistry & Remote Sensing

Pablo Saunders-Shultz

Graduate Student

csaundersshultz@alaska.edu

Társilo Girona

Co Investigator

tarsilo.girona@alaska.edu

Changes in the quantity and/or composition of gases released from volcanoes can be one of the earliest indicators of volcanic unrest. Magma at depth contains dissolved volatiles (or gases) and because each volatile has a unique magma solubility, changes in volcanic gas emissions can reveal subvolcanic processes such as magma ascent and changes in conduit permeability. Satellite remote sensing data provide unique insights into volcanic activity at high temporal resolutions. Thermal infrared data in particular are useful for detecting elevated (above background) surface temperatures that may be indicative of changes in volcanic activity and associated with the release of hot gases, warming of the ground surface, and eruption of lava. For the proposed project we aim to develop automated tools to analyze existing volcanic gas and thermal remote sensing data and provide quantitative information on these parameters to help forecast eruption onset, size, duration and expected hazards.

Petrology, Geochemistry & Physical Volcanology

We will use geological observations and geochemical analyses of historical eruption products from our target volcanoes to constrain conceptual, geochemical, and physical eruption models, as well as to characterize eruptive behavior to inform both short and long-term eruption forecasts.

Petrographic observations, mineral phase thermobarometry, mineral diffusion/dissolution profiles, and melt inclusion volatile concentrations will provide insights into magma properties and storage conditions, the timing of magma recharge and ascent prior to eruption, and the likely eruption trigger.

Petrological data will be evaluated to identify temporal trends that may correlate with eruptive activity that could be used in near-real-time for short-term eruption forecasts.

Petrological data, maps of volcanic deposits, and eruption histories will be used to constrain past eruption sizes, their products and extents to inform long-term probabilistic eruption forecasts.

Target Volcanoes

The following Alaska volcanoes targeted in this study encompass a range of eruptive behaviors and signs of unrest. In particular we selected four frequently erupting, open-system volcanoes (from west to east: Cleveland, Shishaldin, Pavlof and Veniaminof) and four intermittently erupting, closed-system volcanoes (from west to east: Okmok, Bogoslof, Augustine and Redoubt). Through data reanalysis and multidisciplinary synthesis we will advance our understanding of these dynamic systems and identify commonalities in unrest signatures.

Cleveland (photo Izbekov)

Shishaldin (photo Fee)

Pavlof (photo Lopez)

Veniaminof (photo Loewen)

Okmok (photo Larsen)

Bogoslof (photo Tepp)

Augustine (photo Read)

Redoubt (photo Bull)

Modeling

Multidisciplinary data reanalysis and synthesis will be used to develop a range of simple to complex models designed to help understand these volcanic systems. Simple conceptual models will first be developed by combining geodetic and geochemical models (Figure 2). Later in the project one complex multiparameter physics-based and eight multicomponent ensemble models will be developed for the target volcanoes. These models will be used as input parameters into a probabilistic eruption forecasting framework that will incorporate geologically-derived eruption histories, geophysical and geochemical monitoring data, and expert elicitation to forecast the possible eruption outcomes and threats.

Figure 2: Conceptual model of subsurface conditions for different phases of unrest prior to and during the 2009 eruption of Redoubt volcano, based on independent and complementary petrologic, geodetic and seismic data. Figure from Grapenthin et al. (2013).

Collaborators

Kyle Anderson, U.S. Geological Survey - California Volcano Observatory, kranderson@usgs.gov

Israel Brewster, University of Alaska Fairbanks Geophysical Institute - Alaska Volcano Observatory, ijbrewster@alaska.edu

Cheryl Cameron, Alaska Division of Geological & Geophysical Surveys - Alaska Volcano Observatory, cheryl.cameron@alaska.gov

Laura Clor, U.S. Geological Survey - Volcano Emissions Project, lclor@usgs.gov

Michelle Coombs, U.S. Geological Survey - Alaska Volcano Observatory, mcoombs@usgs.gov

Scott Crass, Alaska Division of Geological & Geophysical Surveys - Alaska Volcano Observatory, scott.crass@alaska.gov

Hannah Dietterich, U.S. Geological Survey - Alaska Volcano Observatory, hdietterich@usgs.gov

Matt Haney, U.S. Geological Survey - Alaska Volcano Observatory, mhaney@usgs.gov

Alicia Hotovec-Ellis, U.S. Geological Survey - California Volcano Observatory, ahotovec-ellis@usgs.gov

Peter Kelly, U.S. Geological Survey - Volcano Emissions Project, pkelly@usgs.gov

Christoph Kern, U.S. Geological Survey - Volcano Emissions Project, ckern@usgs.gov

Matt Loewen, U.S. Geological Survey - Alaska Volcano Observatory, mloewen@usgs.gov

Jake Lowenstern, U.S. Geological Survey - Volcano Disaster Assistance Project, jlwnstrn@usgs.gov

Warner Marzocchi, University of Naples Federico II, warner.marzocchi@unina.it

Tina Neal, U.S. Geological Survey - Alaska Volcano Observatory, tneal@usgs.gov

Jeremy Pesicek, U.S. Geological Survey - Volcano Disaster Assistance Project, jpesicek@usgs.gov

John Power, U.S. Geological Survey - Alaska Volcano Observatory, jpower@usgs.gov

Janet Schaefer, Alaska Division of Geological & Geophysical Surveys - Alaska Volcano Observatory, janet.schaefer@alaska.gov

Lori Schoening, University of Alaska Fairbanks Geophysical Institute, llschoening@alaska.edu

Kristi Wallace, U.S. Geological Survey - Alaska Volcano Observatory, kwallace@usgs.gov

News Items

Sifting Volcanic Paydirt To Help Forecast Eruptions (Ned Rozell), Alaska Science Forum, 3 October 2019. Reposted in the AGU Blogosphere "The Field" on 7 October 2019.