Event trees and epistemic uncertainty in long‐term volcanic hazard assessment of Rift Volcanoes: the example of Aluto (Central Ethiopia)

Aluto is a peralkaline rhyolitic caldera located in a highly populated area in central Ethiopia. Its postcaldera eruptive activity has mainly consisted of self‐similar, pumice‐cone‐building eruptions of varying size and vent location. These eruptions are explosive, generating hazardous phenomena that could impact proximal to distal areas from the vent. Volcanic hazard assessments in Ethiopia and the East African Rift are still limited in number. In this study, we develop an event tree model for Aluto volcano. The event tree is doubly useful: It facilitates the design of a conceptual model for the volcano and provides a framework to quantify volcanic hazard. We combine volcanological data from past and recent research at Aluto, and from a tool to objectively derive analog volcanoes (VOLCANS), to parameterize the event tree, including estimates of the substantial epistemic uncertainty. Results indicate that the probability of a silicic eruption in the next 50 years is highly uncertain, ranging from 2% to 35%. This epistemic uncertainty has a critical influence on event‐tree estimates for other volcanic events, like the probability of occurrence of pyroclastic density currents (PDCs) in the next 50 years. The 90% credible interval for the latter is 5–16%, considering only the epistemic uncertainty in conditional eruption size and PDC occurrence, but 2–23% when adding the epistemic uncertainty in the probability of eruption in 50 years. Despite some anticipated challenges, we envisage that our event tree could be translated to other rift volcanoes, making it an important tool to quantify volcanic hazard in Ethiopia and elsewhere

Phreatic eruptions at crater lakes: occurrence statistics and probabilistic hazard forecast

Phreatic eruptions, although posing a serious threat to people in crater proximity, are often underestimated and have been comparatively understudied. The detailed eruption catalogue for Ruapehu Volcano (New Zealand) provides an exceptional opportunity to study the statistics of recurring phreatic explosions at a crater lake volcano. We performed a statistical analysis on this phreatic eruption database, which suggests that phreatic events at Ruapehu do not follow a Poisson process. Instead they tend to cluster, which is possibly linked to an increased heat flow during periods of a more shallow-seated magma column. Larger explosions are more likely to follow shortly after smaller events, as opposed to longer periods of quiescence. The absolute probability for a phreatic explosion to occur at Ruapehu within the next month is about 10%, when averaging over the last 70 years of recording. However, the frequency of phreatic explosions is significantly higher than the background level in years prior to magmatic episodes. Combining clast ejection simulations with a Bayesian event tree tool (PyBetVH) we perform a probabilistic assessment of the hazard due to ballistic ejecta in the summit area of Ruapehu, which is frequently visited by hikers. Resulting hazard maps show that the absolute probability for the summit to be affected by ballistics within the next month is up to 6%. The hazard is especially high on the northern lakeshore, where there is a mountain refuge. Our results contribute to the local hazard assessment as well as the general perception of hazards due to steam-driven explosions

MeMoVolc report on classification and dynamics of volcanic explosive eruptions

Classifications of volcanic eruptions were first introduced in the early twentieth century mostly based on qualitative observations of eruptive activity, and over time, they have gradually been developed to incorporate more quantitative descriptions of the eruptive products from both deposits and observations of active volcanoes. Progress in physical volcanology, and increased capability in monitoring, measuring and modelling of explosive eruptions, has highlighted shortcomings in the way we classify eruptions and triggered a debate around the need for eruption classification and the advantages and disadvantages of existing classification schemes. Here, we (i) review and assess existing classification schemes, focussing on subaerial eruptions; (ii) summarize the fundamental processes that drive and parameters that characterize explosive volcanism; (iii) identify and prioritize the main research that will improve the understanding, characterization and classification of volcanic eruptions and (iv) provide a roadmap for producing a rational and comprehensive classification scheme. In particular, classification schemes need to be objective-driven and simple enough to permit scientific exchange and promote transfer of knowledge beyond the scientific community. Schemes should be comprehensive and encompass a variety of products, eruptive styles and processes, including for example, lava flows, pyroclastic density currents, gas emissions and cinder cone or caldera formation. Open questions, processes and parameters that need to be addressed and better characterized in order to develop more comprehensive classification schemes and to advance our understanding of volcanic eruptions include conduit processes and dynamics, abrupt transitions in eruption regime, unsteadiness, eruption energy and energy balance

From anecdotes to quantification: advances in characterizing volcanic eruption impacts on the built environment

Over the past 20 years, our understanding of volcanic eruption impacts on the built environment has transformed from being primarily observational with small datasets to one grounded in field investigations, laboratory experiments, and quantitative modeling, with an emphasis on stakeholder collaboration and co-creation. Here, we summarize key advances and knowledge gaps of impacts across volcanic hazards and built environment types from the past 20 + years. Studies have concentrated on impacts from tephra fall (ash) and to buildings, with less examination of other hazards’ impacts to critical infrastructure. As we look to the next decade, we speculate on likely research directions, including the increasing role of new technologies, higher resolution modeling, transdisciplinary collaborations, and evidence-based mitigative solutions

Identification, structural and pharmacological characterization of τ-CnVA, a conopeptide that selectively interacts with somatostatin sst3 receptor

International audienc

Integrating hazard, exposure, vulnerability and resilience for risk and emergency management in a volcanic context: the ADVISE model

Risk assessments in volcanic contexts are complicated by the multi-hazard nature of both unrest and eruption phases, which frequently occur over a wide range of spatial and temporal scales. As an attempt to capture the multi-dimensional and dynamic nature of volcanic risk, we developed an integrAteD VolcanIc risk asSEssment (ADVISE) model that focuses on two temporal dimensions that authorities have to address in a volcanic context: short-term emergency management and long-term risk management. The output of risk assessment in the ADVISE model is expressed in terms of potential physical, functional, and systemic damage, determined by combining the available information on hazard, exposed systems and vulnerability. The ADVISE model permits qualitative, semi-quantitative and quantitative risk assessment depending on the final objective and on the available information. The proposed approach has evolved over a decade of study on the volcanic island of Vulcano (Italy), where recent signs of unrest combined with uncontrolled urban development and significant seasonal variations of exposed population result in highly dynamic volcanic risk. For the sake of illustration of all the steps of the ADVISE model, we focus here on the risk assessment of the transport system in relation to the tephra fallout associated with a long-lasting Vulcanian cycle

Dynamic Probabilistic Hazard Mapping in the Long Valley Volcanic Region CA: Integrating Vent Opening Maps and Statistical Surrogates of Physical Models of Pyroclastic Density Currents

Ideally, probabilistic hazard assessments combine available knowledge about physical mechanisms of the hazard, data on past hazards, and any precursor information. Systematically assessing the probability of rare, yet catastrophic hazards adds a layer of difficulty due to limited observation data. Via computer models, one can exercise potentially dangerous scenarios that may not have happened in the past but are probabilistically consistent with the aleatoric nature of previous volcanic behavior in the record. Traditional Monte Carlo-based methods to calculate such hazard probabilities suffer from two issues: they are computationally expensive, and they are static. In light of new information, newly available data, signs of unrest, and new probabilistic analysis describing uncertainty about scenarios the Monte Carlo calculation would need to be redone under the same computational constraints. Here we present an alternative approach utilizing statistical emulators that provide an efficient way to overcome the computational bottleneck of typical Monte Carlo approaches. Moreover, this approach is independent of an aleatoric scenario model and yet can be applied rapidly to any scenario model making it dynamic.We present and apply this emulator-based approach to create multiple probabilistic hazard maps for inundation of pyroclastic density currents in the Long Valley Volcanic Region. Further, we illustrate how this approach enables an exploration of the impact of epistemic uncertainties on these probabilistic hazard forecasts. Particularly, we focus on the uncertainty of vent opening models and how that uncertainty both aleatoric and epistemic impacts the resulting probabilistic hazard maps of pyroclastic density current inundation.Published9600-96216V. Pericolosità vulcanica e contributi alla stima del rischioJCR Journa