A quantitative uncertainty assessment of eruptive parameters derived from tephra deposits: the example of two large eruptions of Cotopaxi volcano, Ecuador

Physical parameters of explosive eruptions are typically derived from tephra deposits. However, the characterization of a given eruption relies strongly on the quality of the dataset used, the strategy chosen to obtain and process field data and the particular model considered to derive eruptive parameters. As a result, eruptive parameters are typically affected by a certain level of uncertainty and should not be considered as absolute values. Unfortunately, such uncertainty is difficult to assess because it depends on several factors and propagates from field sampling to the application and interpretation of dispersal models. Characterization of explosive eruptions is made even more difficult when tephra deposits are poorly exposed and only medial data are available. In this paper, we present a quantitative assessment of the uncertainty associated with the characterization of tephra deposits generated by the two largest eruptions of the last 2,000years of Cotopaxi volcano, Ecuador. In particular, we have investigated the effects of the determination of the maximum clast on the compilation of isopleth maps, and, therefore, on the characterization of plume height. We have also compared the results obtained from the application of different models for the determination of both plume height and erupted volume and for the eruption classification. Finally, we have investigated the uncertainty propagation into the calculation of mass eruption rate and eruption duration. We have found that for our case study, the determination of plume height from isopleth maps is more sensitive to the averaging techniques used to define the maximum clast than to the choice of dispersal models used (i.e. models of Carey and Sparks 1986; Pyle 1989) and that even the application of the same dispersal model can result in plume height discrepancies if different isopleth lines are used (i.e. model of Carey and Sparks 1986). However, the uncertainties associated with the determination of erupted mass, and, as a result, of the eruption duration, are larger than the uncertainties associated with the determination of plume height. Mass eruption rate is also associated with larger uncertainties than the determination of plume height because it is related to the fourth power of plume height. Eruption classification is also affected by data processing. In particular, uncertainties associated with the compilation of isopleth maps affect the eruption classification proposed by Pyle (1989), whereas the VEI classification is affected by the uncertainties resulting from the determination of erupted mass. Finally, we have found that analytical and empirical models should be used together for a more reliable characterization of explosive eruptions. In fact, explosive eruptions would be characterized better by a range of parameters instead of absolute values for erupted mass, plume height, mass eruption rate and eruption duration. A standardization of field sampling would also reduce the uncertainties associated with eruption characterizatio

Temporal evolution of roof collapse from tephra fallout during the 2021-Tajogaite eruption (La Palma, Spain)

Although dominantly effusive, the 2021 Tajogaite eruption from Cumbre Vieja volcano (La Palma, Spain) produced a wide tephra blanket over 85 days of activity. About one month after the eruption onset, clean-up operations were implemented to mitigate the impact of tephra load on primary buildings. Here, we present a post-event impact assessment of 764 primary buildings, which expands our empirical knowledge of building vulnerability to tephra fallout to include impacts from long-lasting eruptions. Field observations are analyzed in the perspective of existing fragility curves, high-resolution satellite imagery and a reconstruction of the spatio-temporal evolution of the tephra blanket to characterize the evolution of roof collapse due to static loads over time. Thanks to a chronological correlation between the temporal evolution of tephra sedimentation and the timing of clean-up operations, we quantified their effectiveness in mitigating roof collapse. If no clean-up measures had been taken 11% of the surveyed buildings would have exceeded a 75% probability of roof collapse, while only 10 roof collapses have been observed (1.3% of the analysed buildings). This work provides key insights for further development of emergency plans for the management of long-lasting eruptions characterised by the sustained emission of tephra over weeks to months

Mapa regional y ranking de riesgos volcánicos de la zona volcánica central de los Andes

La Zona Volcánica Central de los Andes (ZVCA) es una de las zonas volcánicas más activas de América del Sur y es una de las áreas en las que la mayoría de los volcanes se encuentran dentro de los 25 km de una frontera internacional comprendiendo Argentina, Chile, Bolivia y Perú, con importantes desafíos transfronterizos (Donovan & Oppenheimer, 2019). En esta región, los volcanes se ubican en el Altiplano-Puna (sobre los 4000 m de altitud) y, por lo tanto, varios volcanes superan los 6000 m s.n.m., entre ellos el Ojos del Salado que es la cumbre volcánica más alta del mundo. Durante décadas, la ZVCA ha sido un sitio importante para entender una gran cantidad de procesos geológicos (e.g, evolución geológica, tectónica, espesor de la corteza, erosión y geometría por subducción, segmentación del arco volcánico y génesis del magma), pero debido al difícil acceso, los registros de erupciones eran bastante escasos, hasta hace muy poco. Durante los últimos 20 años, la agitación volcánica en varias partes de la ZVCA ha permitido la implementación de nuevas capacidades de monitoreo e inversiones en investigación (Aguilera et al., 2022) y como consecuencia, se ha puesto a disposición nueva información detallada. La priorización de estrategias de reducción de riesgos es especialmente importante para la ZVCA debido a su gran cantidad de volcanes. Además, el número de personas expuestas a la actividad volcánica en la ZVCA depende de la dinámica eruptiva y la magnitud de las erupciones potenciales

New Insights Into the Relationship Between Mass Eruption Rate and Volcanic Column Height Based On the IVESPA Data Set

Rapid and simple estimation of the mass eruption rate (MER) from column height is essential for real-time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we explore empirical MER-height relationships for four measures of column height: spreading level, sulfur dioxide height, and top height from direct observations and as reconstructed from deposits. These relationships show significant differences and highlight limitations of empirical models currently used in operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding highlights challenges in constraining the MER-height relation using heterogeneous observations and empirical models, which reinforces the need for improved eruption source parameter data sets and physics-based models

Recruitment of Glycosyl Hydrolase Proteins in a Cone Snail Venomous Arsenal: Further Insights into Biomolecular Features of Conus Venoms

Cone snail venoms are considered an untapped reservoir of extremely diverse peptides, named conopeptides, displaying a wide array of pharmacological activities. We report here for the first time, the presence of high molecular weight compounds that participate in the envenomation cocktail used by these marine snails. Using a combination of proteomic and transcriptomic approaches, we identified glycosyl hydrolase proteins, of the hyaluronidase type (Hyal), from the dissected and injectable venoms (“injectable venom” stands for the venom variety obtained by milking of the snails. This is in contrast to the “dissected venom”, which was obtained from dissected snails by extraction of the venom glands) of a fish-hunting cone snail, Conus consors (Pionoconus clade). The major Hyal isoform, Conohyal-Cn1, is expressed as a mixture of numerous glycosylated proteins in the 50 kDa molecular mass range, as observed in 2D gel and mass spectrometry analyses. Further proteomic analysis and venom duct mRNA sequencing allowed full sequence determination. Additionally, unambiguous segment location of at least three glycosylation sites could be determined, with glycans corresponding to multiple hexose (Hex) and N-acetylhexosamine (HexNAc) moieties. With respect to other known Hyals, Conohyal-Cn1 clearly belongs to the hydrolase-type of Hyals, with strictly conserved consensus catalytic donor and positioning residues. Potent biological activity of the native Conohyals could be confirmed in degrading hyaluronic acid. A similar Hyal sequence was also found in the venom duct transcriptome of C. adamsonii (Textilia clade), implying a possible widespread recruitment of this enzyme family in fish-hunting cone snail venoms. These results provide the first detailed Hyal sequence characterized from a cone snail venom, and to a larger extent in the Mollusca phylum, thus extending our knowledge on this protein family and its evolutionary selection in marine snail venoms

TephraProb: A Matlab Package for Probabilistic Hazard Assessments of Tephra Fallout

TephraProb is a toolbox of Matlab functions designed to produce scenario–based probabilistic hazard assessments for ground tephra accumulation based on the Tephra2 model. The toolbox includes a series of graphical user interfaces that collect, analyze and pre–process input data, create distributions of eruption source parameters based on a wide range of probabilistic eruption scenarios, run Tephra2 using the generated input scenarios and provide results as exceedence probability maps, probabilistic isomass maps and hazard curves. We illustrate the functionality of TephraProb using the 2011 eruption of Cordón Caulle volcano (Chile) and selected eruptions of La Fossa volcano (Vulcano Island, Italy). The range of eruption styles captured by these two events highlights the potential of TephraProb as an operative tool when rapid hazard assessments are required during volcanic crises

Grain size modulates volcanic ash retention on crop foliage and potential yield loss

Ashfall from volcanic eruptions endangers crop production and food security while jeopardising agricultural livelihoods. As populations in the vicinity of volcanoes continue to grow, strategies to reduce volcanic risks to and impacts on crops are increasingly needed. Current models of crop vulnerability to ash are limited. They also rely solely on ash thickness (or loading) as the hazard intensity metric and fail to reproduce the complex interplay of other volcanic and non-volcanic factors that drive impact. Amongst these, ash retention on crop leaves affects photosynthesis and is ultimately responsible for widespread damage to crops. In this context, we carried out greenhouse experiments to assess how ash grain size, leaf pubescence, and humidity conditions at leaf surfaces influence the retention of ash (defined as the percentage of foliar cover coated with ash) in tomato and chilli pepper plants, two crop types commonly grown in volcanic regions. For a fixed ash mass load (∼570 g m−2), we found that ash retention decreases exponentially with increasing grain size and is enhanced when leaves are pubescent (such as in tomato plants) or when their surfaces are wet. Assuming that leaf area index (LAI) diminishes with ash retention in tomato and chilli pepper plants, we derived a new expression for predicting potential crop yield loss after an ashfall event. We suggest that the measurement of crop LAI in ash-affected areas may serve as an impact metric. Our study demonstrates that quantitative insights into crop vulnerability can be gained rapidly from controlled experiments. We advocate this approach to broaden our understanding of ash–plant interactions and to validate the use of remote sensing methods for assessing crop damage and recovery at various spatial and time scales after an eruption

Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data

Although the generally high fertility of volcanic soils is often seen as an opportunity, short-term consequences of eruptions on natural and cultivated vegetation are likely to be negative. The empirical knowledge obtained from post-event impact assessments provides crucial insights into the range of parameters controlling impact and recovery of vegetation, but their limited coverage in time and space offers a limited sample of all possible eruptive and environmental conditions. Consequently, vegetation vulnerability remains largely unconstrained, thus impeding quantitative risk analyses. Here, we explore how cloud-based big Earth observation data, remote sensing and interpretable machine learning (ML) can provide a large-scale alternative to identify the nature of, and infer relationships between, drivers controlling vegetation impact and recovery. We present a methodology developed using Google Earth Engine to systematically revisit the impact of past eruptions and constrain critical hazard and vulnerability parameters. Its application to the impact associated with the tephra fallout from the 2011 eruption of Cordón Caulle volcano (Chile) reveals its ability to capture different impact states as a function of hazard and environmental parameters and highlights feedbacks and thresholds controlling impact and recovery of both natural and cultivated vegetation. We therefore conclude that big Earth observation (EO) data and machine learning complement existing impact datasets and open the way to a new type of dynamic and large-scale vulnerability models.ISSN:1561-8633ISSN:1684-998