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\begin{document}

\title{The stability and collapse of lava domes: insight from UAS-derived 4D
structure and slope stability models}



\author[1]{Brett Carr}%
\author[1]{Einat Lev}%
\author[2]{Loÿc Vanderkluysen}%
\author[2]{Danielle Moyer}%
\author[3]{Gayatri Marliyani}%
\author[4]{Amanda Clarke}%
\affil[1]{Lamont-Doherty Earth Observatory}%
\affil[2]{Drexel University}%
\affil[3]{Gadjah Mada University}%
\affil[4]{Arizona State University}%


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  \date{May 22, 2024}


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\begin{abstract}
Lava domes form by the effusive eruption of viscous lava and are
inherently unstable and prone to collapse. Dome collapses can generate
pyroclastic flows and trigger explosive eruptions and thus represent a
significant natural hazard. Many processes may contribute to the
instability and collapse of lava domes, including advance of the dome
margins, overtopping of confining topography, internal gas overpressure,
and gravitational instability of the dome structure. Collapses that
result from these processes can generally be grouped into two types:
active and passive. Active collapses are driven by processes associated
with active lava effusion, (e.g. dome growth or gas pressurization),
while passive collapses are not directly associated with eruptive
activity and can be triggered by overtopping of topographic obstacles or
weakening of the dome structure. We use data collected by uncrewed
aerial systems (UAS, commonly called `drones') and a slope stability
model to both identify and assess the stability of potential collapse
sites for both passive and active processes. We collected visual and
thermal infrared images by UAS and used structure-from-motion
photogrammetry to generate thermal maps and digital elevation models
(DEMs) of two example lava domes at Sinabung Volcano (Sumatra,
Indonesia) and Merapi Volcano (Java, Indonesia). We evaluate the
stability of erupted lava using the Scoops3D numerical model to assess
the risk of passive and active collapses, including an assessment of the
effect of lava material properties and internal pore pressure on the
dome stability. We compare the collapse risk from Scoops3D with
UAS-derived temperature maps and DEM differencing to evaluate the
stability, size, and location of observed or potential collapses. We
test whether Scoops3D can hindcast the sites and magnitudes of passive
collapses at Sinabung that occurred in 2014 and 2015 and assess the
stability of the remaining lava dome (growth has ended in spring 2018).
For both volcanoes. Through application of these techniques, we are able
to evaluate the collapse risk due to multiple processes that may act
contemporaneously to generate dome instability. This study demonstrates
how identification and classification of individual collapse mechanisms
can be used to assess hazards at dome-forming volcanoes.%
\end{abstract}%



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