Understanding Degassing Pathways Along the 1886 Tarawera (New Zealand) Volcanic Fissure by Combining Soil and Lake CO₂ Fluxes

CO₂ flux measurements are often used to monitor volcanic systems, understand the cause of volcanic unrest, and map sub-surface structures. Currently, such measurements are incomplete at Tarawera (New Zealand), which erupted with little warning in 1886 and produced a ∼17 km long fissure. We combine new soil CO₂ flux and C isotope measurements of Tarawera with previous data from Rotomahana and Waimangu (regions also along the 1886 fissure) to fingerprint the CO₂ source, understand the current pathways for degassing, quantify the CO₂ released along the entire fissure, and provide a baseline survey. The total CO₂ emissions from the fissure are 1227 t⋅d⁻¹ (742–3398 t⋅d⁻¹ 90 % confidence interval), similar to other regions in the Taupō Volcanic Zone. The CO₂ flux from Waimangu and Rotomahana is far higher than from Tarawera (>549 vs. ∼4 t⋅d⁻¹ CO₂), likely influenced by a shallow silicic body at depth and Okataina caldera rim faults increasing permeability at the southern end of the fissure. Highly localized regions of elevated CO2 flux occur along the fissure and are likely caused by cross-cutting faults that focus the flow. One of these areas occurs on Tarawera, which is emitting ∼1 t⋅d⁻¹ CO₂ with a δ¹³CO₂ of −5.5 ± 0.5 ‰, and comparison with previous observations shows that activity is declining over time. This region highlights the spatial and temporal complexity of degassing pathways at volcanoes and that sub-surface structures exert a primary control on the magnitude of CO₂ flux in comparison to the surface mechanism (i.e., CO₂ released through the soil or lake surface)

Bayesian Network Modeling and Expert Elicitation for Probabilistic Eruption Forecasting: Pilot Study for Whakaari/White Island, New Zealand

Bayesian Networks (BNs) are probabilistic graphical models that provide a robust and flexible framework for understanding complex systems. Limited case studies have demonstrated the potential of BNs in modeling multiple data streams for eruption forecasting and volcanic hazard assessment. Nevertheless, BNs are not widely employed in volcano observatories. Motivated by their need to determine eruption-related fieldwork risks, we have worked closely with the New Zealand volcano monitoring team to appraise BNs for eruption forecasting with the purpose, at this stage, of assessing the utility of the concept rather than develop a full operational framework. We adapted a previously published BN for a pilot study to forecast volcanic eruption on Whakaari/White Island. Developing the model structure provided a useful framework for the members of the volcano monitoring team to share their knowledge and interpretation of the volcanic system. We aimed to capture the conceptual understanding of the volcanic processes and represent all observables that are regularly monitored. The pilot model has a total of 30 variables, four of them describing the volcanic processes that can lead to three different types of eruptions: phreatic, magmatic explosive and magmatic effusive. The remaining 23 variables are grouped into observations related to seismicity, fluid geochemistry and surface manifestations. To estimate the model parameters, we held a workshop with 11 experts, including two from outside the monitoring team. To reduce the number of conditional probabilities that the experts needed to estimate, each variable is described by only two states. However, experts were concerned about this limitation, in particular for continuous data. Therefore, they were reluctant to define thresholds to distinguish between states. We conclude that volcano monitoring requires BN modeling techniques that can accommodate continuous variables. More work is required to link unobservable (latent) processes with observables and with eruptive patterns, and to model dynamic processes. A provisional application of the pilot model revealed several key insights. Refining the BN modeling techniques will help advance understanding of volcanoes and improve capabilities for forecasting volcanic eruptions. We consider that BNs will become essential for handling ever-burgeoning observations, and for assessing data's evidential meaning for operational eruption forecasting

Geophysical signature of unrest episodes at active volcanic systems : insights into the hydrothermal system fingerprint.

The characterisation of unrest signals and eruption precursors is one of the main challenges in volcano research because of the complexity of volcanic systems (e.g., the interplay between magmatic and hydrothermal fluids). This thesis addresses the issue for White Island volcano (New Zealand), and presents a comprehensive analysis of geophysical changes associated with the recent unrest/eruptive episode (2011-2013). A modelling strategy was used to 1. Characterise the source of the magnetic and gravity changes during this unrest/eruptive episode, 2. describe the effect of an inclined fumarole on hydrothermal circulation and gravity changes, 3. assess whether volcanic tremor can be used for eruption forecasting at White Island. The observed magnetic changes were inverted for a dipole, and can be explained by temperature changes at shallow depth below the active crater. The lack of signi_cant gravity changes was then used to constrain the heat source responsible for the magnetic changes. The geophysical changes are consistent with a model involving an episode of increased degassing from a possible shallow magmatic intrusion. The effect of a period of increased degassing on hydrothermal circulation and gravity changes in the fumarole area was then investigated. Previous studies inferred an inclined conduit for the main fumarole at White Island (fumarole zero). I therefore investigated the effect of such an inclined conduit on hydrothermal circulation and gravity changes at steady state and associated with an unrest episode, using a numerical modelling approach (TOUGH2). The model was constrained using parameters consistent for fumarole zero (small conduit one order of magnitude more permeable than the surrounding medium). The effect of the fumarole inclination is to shift the hydrothermal plume and the gravity anomaly towards the injection area instead of the fumarole outlet. Such a model implies that regular microgravity measurements can inform on the location of the feeding source of the fumarole. Finally, I calibrated an algorithm implementing the material Failure Forecast Method to issue eruption forecasts from volcanic tremor at White Island. Volcanic tremor increases preceding four out of the five eruptions of August 2011-January 2014 period are well explained by a model where an eruption is a case of material failure due to magma pressurisation. These tremor increases were therefore likely precursory to the eruptions. The good fit between the model and data allowed the issue of reliable eruption forecasts so that four eruptions (out of the five eruptions of the episode) occurred during forecast eruption windows. The probability of having an eruption during a forecast eruption window is 0.21 for the whole period, 37 times higher than the probability of having an eruption on any day, demonstrating that eruption forecasting capabilities can be enhanced using our procedure. We conclude that, at White Island, magnetic and gravity measurements are valuable to characterise the unrest source, and that the evolution of volcanic tremor can be used for eruption forecasting. Magnetic measurements can help characterise unrest because of their sensitivity to temperature changes. Additional gravity measurements allow constraining the source of the magnetic changes, and they could also inform on location of the source of the fluid injection in the fumarole area. The evolution of volcanic tremor can be precursory to eruptions and allow an estimate of the timing of the eruptions onset. This study therefore brings insights into unrest sources and eruption precursors at White Island, while providing methods that could be applied at other volcanoes. It also highlights the importance of continuous measurements to constrain volcanic processes

Towards Improved Forecasting of Volcanic Eruptions

info:eu-repo/semantics/publishe

Understanding degassing pathways along the 1886 Tarawera (New Zealand) volcanic fissure by combining soil and lake CO2 fluxes

CO2 flux measurements are often used to monitor volcanic systems, understand the cause of volcanic unrest, and map sub-surface structures. Currently, such measurements are incomplete at Tarawera (New Zealand), which erupted with little warning in 1886 and produced a ∼17 km long fissure. We combine new soil CO2 flux and C isotope measurements of Tarawera with previous data from Rotomahana and Waimangu (regions also along the 1886 fissure) to fingerprint the CO2 source, understand the current pathways for degassing, quantify the CO2 released along the entire fissure, and provide a baseline survey. The total CO2 emissions from the fissure are 1227 t⋅d–1 (742–3398 t⋅d–1 90 % confidence interval), similar to other regions in the Taupō Volcanic Zone. The CO2 flux from Waimangu and Rotomahana is far higher than from Tarawera (>549 vs. ∼4 t⋅d–1 CO2), likely influenced by a shallow silicic body at depth and Okataina caldera rim faults increasing permeability at the southern end of the fissure. Highly localized regions of elevated CO2 flux occur along the fissure and are likely caused by cross-cutting faults that focus the flow. One of these areas occurs on Tarawera, which is emitting ∼1 t⋅d–1 CO2 with a δ13CO2 of −5.5 ± 0.5 ‰, and comparison with previous observations shows that activity is declining over time. This region highlights the spatial and temporal complexity of degassing pathways at volcanoes and that sub-surface structures exert a primary control on the magnitude of CO2 flux in comparison to the surface mechanism (i.e., CO2 released through the soil or lake surface).Published versio

Adaptation and Resilience in ASEAN: Managing Disaster Risks from Natural Hazards

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