Modelling eruptive source parameters in distributed volcanic fields

Abstract

Vent opening hazard models are routinely used as inputs for assessing distal volcanic hazards (lava flows, tephra fallout) in distributed volcanic fields. These vent opening hazard models have traditionally relied on the location of mapped vents; seldom have they taken into account how vents are linked in space and time. We show that inputs needed to appropriately model distal hazards are fundamentally different than thoses required to model near-vent hazards (ground deformation). We provide a computational model to obtain more appropriate eruptive source parameters (ESPs) for distal volcanic hazard sources and show the utility of our code through three examples. The code's strength is that it links events based on the spatio-temporal relationships of vents through heirarchical clustering. The development of the code and its strenghts and weaknesses are discussed. This work challenges previous ideas about ESPs and we hope this work leads to further improvement in hazard assessment methods.

Spatio-temporal forecasting of future volcanism at Harrat Khaybar, Saudi Arabia

“…One caution around the Harrat Khaybar "flare-up" is the assumption that each vent records an individual eruption, and that eruptions are of the same volume throughout the history of the field. It is common in many distributed volcanic fields that multiple vents are simultaneously produced during a single event (e.g., Muffler et al 2011;Bevilacqua et al 2017;Gallant et al 2018Gallant et al , 2021Connor et al 2019;Downs et al 2020). An example from the Arabian harrats is the 1256 AD event in northern Harrat Rahat that produced six scoria cones along a ~ 2.25-km-long fissure (Camp et al 1987).…”

“…We therefore maintain that period three represents a significant increase in activity consistent with the idea of a flare-up. Future probabilistic studies should assess the spatio-temporal relationships between vents in the harrat and consider modeling eruptive events to account for multiple vent eruptions (e.g., Condit and Connor 1996;Cappello et al 2013;Runge et al 2014;Gallant et al 2018Gallant et al , 2021Nieto-Torres and Martin Del Pozzo 2019). That would result in a better spatio-temporal estimation of future volcanic events.…”

“…Three hundred eighty-four volcanic vents were identified in our study at Harrat Khaybar. Whereas volcanic events might be associated with multiple vents (e.g., Condit and Connor 1996;Muffler et al 2011;Runge et al 2014;Gallant et al 2018Gallant et al , 2021Nieto-Torres and Martin Del Pozzo 2019;Downs et al 2020), in this work, a vent is assumed to represent an individual volcanic event (e.g., Bebbington and Cronin 2011;El Difrawy et al 2013;Bertin et al 2019;Connor et al 2019). These vents belong to different volcanic morphologies, including: scoria cones, small-shield shield volcanoes, tuff cones, and a composite volcano.…”

“…The pre 600 ka vents are highly eroded and show a wide age range while the post 600 ka vents are relatively well-preserved and have better temporal constraints. Therefore, we break the last 600 ka eruptions into four even size periods although we acknowledge that there are significant uncertainties in these eruptive periods since only ~ 4% of the vents have definitive ages, which is a common situation in poorly dated volcanic fields (e.g., Connor et al 2013;El Difrawy et al 2013;Gallant et al 2018Gallant et al , 2021Nieto-Torres and Martin Del Pozzo 2019;Valentine et al 2021).…”

Probabilistic Volcanic Hazard Assessment of the 22.5–28°S Segment of the Central Volcanic Zone of the Andes

“…An additional hindrance is that, even for 'monogenetic' vents, it is not certain that each volcanic vent represents a single eruptive episode (Runge et al, 2014;Báez et al, 2016;Bevilacqua et al, 2017;Connor et al, 2018;Gallant et al, 2021). This uncertainty, along with the likely presence of buried and eroded vents, can be examined through statistical (Runge et al, 2014), morphometric (Nieto-Torres andMartin Del Pozzo, 2019), and spatio-temporal clustering (Gallant et al, 2021) techniques. However, due to the large study area and the availability of age and volume information in the Bertin et al (2022) database (each volcanic deposit includes an age and volume range), here we followed an alternative approach.…”