Cordilleran Section - 117th Annual Meeting - 2021

Paper No. 14-11
Presentation Time: 10:20 AM

STATISTICAL ANALYSIS OF THE EFFECTS OF SAMPLING BIAS ON THE DISTRIBUTION OF HISTORIC ERUPTIONS AT SIX HIGH-THREAT CASCADES VOLCANOES


SHAMLOO, Hannah, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331; School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, TILL, Christy B., School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 and KENT, Adam J.R., College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331

Effective volcanic forecasting requires a thorough understanding of a volcano’s eruptive history, including both the timing of eruptions and the repose time between eruptions. However, we currently lack conceptual models for the processes that govern repose time at a specific volcano. While a number of studies rely on repose time for probabilistic hazard assessment, little work has focused on longer-term patterns of repose time for a volcano as a whole, as well as the underlying geologic mechanisms controlling these patterns. We examine the cumulative distribution of recorded eruptions through time compiled from the literature at six well-studied, high- to very high-threat Cascade volcanoes. Their cumulative eruption distribution patterns fall into two categories; Mt. Adams, Mt. Lassen, and Mt. Rainer maintain a broadly constant frequency of eruptions through time (stationary behavior) between 600 ka and present, whereas Mt. St. Helens, Middle Sister, and South Sister show an increase in frequency of eruptions through time with a transition around 100 ka (non-stationary behavior). We apply bootstrap Monte Carlo modeling to test whether the variable behavior in these distributions is result of geologic processes or sampling bias towards younger and more voluminous eruptive deposits. We find that preferably sampling younger eruptions (<100 ky) in both real Cascade volcano and synthetic datasets causes originally non-stationary distributions to appear as stationary. However, when preferably sampling both larger volume and younger eruptions, it is more difficult to change a non-stationary distribution to a stationary one by sampling bias alone. Our modeling also indicates that the calculated average repose time is affected by these types of sampling bias. Tectonic stress regime does not appear to be a primary control on repose time and increasing silica content of magma composition shows an apparent negative correlation with average repose time – although further work needs to be done on a broader range of magma compositions and over the volcano’s full eruptive history to confirm this. These results have implications regarding our ability to understand the eruptive history of the Cascade arc and other volcanoes deduced from the most commonly available long-term records – the age of erupted rocks through time.