Dome collapse driven block-and-ash flows on Shiveluch, and pyroclastic flows on Mount St. Helens: Deposit morphology and distribution analysis using multiparameter remote sensing- and field-based methods

• Main Author: Krippner, Janine B.
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: Kamchatka
• Online Access: http://d-scholarship.pitt.edu/32557/; http://d-scholarship.pitt.edu/32557/1/Krippner_ETD.pdf

Pyroclastic density currents are volcanic granular flows that include dome collapse-derived block-and-ash flows, and column collapse-derived pyroclastic flows. Volcanic dome-building cycles can last for years and can produce numerous collapse events that deposit block-and-ash flows up to 19 km from the dome. These impact surrounding communities and too-often result in fatalities, and populations have to be evacuated. Shiveluch in Kamchatka, Russia, is one of the world’s most active dome-building volcanoes and has produced some of the largest historical block-and-ash flows, globally. The current eruption phase of Shiveluch volcano has been ongoing since 2001 in a cycle of dome growth and collapse. Understanding these prolonged dome growth episodes and characterizing the extreme end-members in deposit size and runout range is important for investigating these hazards at Shiveluch and other similar volcanoes. This multi-spatial scale investigation links dome activity to the block-and-ash flow deposits using satellite- and field-based data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared (TIR), shortwave infrared (SWIR), and visible-near infrared (VNIR) data are used to quantify the distribution of dome collapse events and resulting deposits through time. Small-scale deposit features are identified with field and high spatial resolution (~0.5 m) WorldView-02 and QuickBird-02 panchromatic data. These block-and-ash flow deposits are compared to the well-studied Mount St. Helens 1980 column collapse pyroclastic flow deposits using historic aerial photography and airborne LiDAR data. Although these deposits are composed of different material that result from the different eruption styles, they contain similarities that reflect similar depositional processes, and differences that reflect the initiation mechanisms. These remotely-identified characteristics can help with rapid identification of the eruption style and can provide a safe and rapid assessment of eruptive products at ...