Combining long- and short-term probabilistic volcanic hazard assessment with cost-benefit analysis to support decision making in a volcanic crisis from the Auckland Volcanic Field,New Zealand

By using BET_VH, we propose a quantitative probabilistic hazard assessment for base surge impact in Auckland, New Zealand. Base surges resulting from phreatomagmatic eruptions are among the most dangerous phenomena likely to be associated with the initial phase of a future eruption in the Auckland Volcanic Field. The assessment is done both in the long-term and in a specific short-term case study, i.e. the simulated pre-eruptive unrest episode during Exercise Ruaumoko, a national civil defence exercise. The most important factors to account for are the uncertainties in the vent location (expected for a volcanic field) and in the run-out distance of base surges. Here, we propose a statistical model of base surge run-out distance based on deposits from past eruptions in Auckland and in analogous volcanoes. We then combine our hazard assessment with an analysis of the costs and benefits of evacuating people (on a 1 × 1-km cell grid). In addition to stressing the practical importance of a cost-benefit analysis in creating a bridge between volcanologists and decision makers, our study highlights some important points. First, in the Exercise Ruaumoko application, the evacuation call seems to be required as soon as the unrest phase is clear; additionally, the evacuation area is much larger than what is recommended in the current contingency plan. Secondly, the evacuation area changes in size with time, due to a reduction in the uncertainty in the vent location and increase in the probability of eruption. It is the tradeoff between these two factors that dictates which cells must be evacuated, and when, thus determining the ultimate size and shape of the area to be evacuated.     

BET_VH: exploring the influence of natural uncertainties on long-term hazard from tephra fallout at Campi Flegrei (Italy)

In this paper, we explore the effects of the intrinsic uncertainties upon long-term volcanic hazard by analyzing tephra fall hazard at Campi Flegrei, Italy, using the BET_VH model described in Marzocchi et al. (Bull Volcanol, 2010). The results obtained show that volcanic hazard based on the weighted average of all possible eruptive settings (i.e. size classes and vent locations) is significantly different from an analysis based on a single reference setting, as commonly used in volcanic hazard practice. The long-term hazard map for tephra fall at Campi Flegrei obtained here accounts for a wide spectrum of uncertainties which are usually neglected, largely reducing the bias intrinsically introduced by the choice of a specific reference setting. We formally develop and apply a general method to recursively integrate simulations from different models which have different characteristics in terms of spatial coverage, resolution and physical details. This outcome of simulations will be eventually merged with field data through the use of the BET_VH model.     

A Bayesian procedure for Probabilistic Tsunami Hazard Assessment

In this paper, a Bayesian procedure is implemented for the Probability Tsunami Hazard Assessment (PTHA). The approach is general and modular incorporating all significant information relevant for the hazard assessment, such as theoretical and empirical background, analytical or numerical models, instrumental and historical data. The procedure provides the posterior probability distribution that integrates the prior probability distribution based on the physical knowledge of the process and the likelihood based on the historical data. Also, the method deals with aleatory and epistemic uncertainties incorporating in a formal way all sources of relevant uncertainty, from the tsunami generation process to the wave propagation and impact on the coasts. The modular structure of the procedure is flexible and easy to modify and/or update as long as new models and/or information are available. Finally, the procedure is applied to an hypothetical region, Neverland, to clarify the PTHA evaluation in a realistic case.     

Probabilistic tsunami hazard assessment for Messina Strait Area (Sicily, Italy)

The general modular Bayesian procedure is applied to provide a probabilistic tsunami hazard assessment (PTHA) for the Messina Strait Area (MSA), Italy. This is the first study in an Italian area where the potential tsunamigenic events caused by both submarine seismic sources (SSSs) and submarine mass failures (SMFs) are examined in a probabilistic assessment. The SSSs are localized on active faults in MSA as indicated by the instrumental data of the catalogue of the Italian seismicity; the SMFs are spatially identified using their propensity to failure in the Ionian and Tyrrhenian Seas on the basis of mean slope and mean depth, and using marine geology background knowledge. In both cases the associated probability of occurrence is provided. The run-ups were calculated at key sites that are main cities and/or important sites along the Eastern Sicily and the Southern Calabria coasts where tsunami events were recorded in the past. The posterior probability distribution combines the prior probability and the likelihood calculated in the MSA. The prior probability is based on the physical model of the tsunami process, and the likelihood is based on the historical data collected by the historical catalogues, background knowledge, and marine geological information. The posterior SSSs and SMFs tsunami probabilities are comparable and are combined to produce a final probability for a full PTHA in MSA.     

Probability hazard map for future vent opening at the Campi Flegrei caldera,Italy

The Campi Flegrei caldera is a restless structure affected by general subsidence and ongoing resurgence of its central part. The persistent activity of the system and the explosive character of the volcanism lead to a very high volcanic hazard that, combined with intense urbanization, corresponds to a very high volcanic risk. One of the largest sources of uncertainty in volcanic hazard/risk assessment for Campi Flegrei is the spatial location of the future volcanic activity. This paper presents and discusses a long-term probability hazard map for vent opening in case of renewal of volcanism at the Campi Flegrei caldera, which shows the spatial conditional probability for the next vent opening, given that an eruption occurs. The map has been constructed by building a Bayesian inference scheme merging prior information and past data. The method allows both aleatory and epistemic uncertainties to be evaluated. The probability map of vent opening shows that two areas of relatively high probability are present within the active portion of the caldera, with a probability approximately doubled with respect to the rest of the caldera. The map has an immediate use in evaluating the areas of the caldera prone to the highest volcanic hazard. Furthermore, it represents an important ingredient in addressing the more general problem of quantitative volcanic hazards assessment at the Campi Flegrei caldera.     

Long-term multi-hazard assessment for El Misti volcano (Peru)

We propose a long-term probabilistic multi-hazard assessment for El Misti Volcano, a composite cone located <20 km from Arequipa. The second largest Peruvian city is a rapidly expanding economic centre and is classified by UNESCO as World Heritage. We apply the Bayesian Event Tree code for Volcanic Hazard (BET_VH) to produce probabilistic hazard maps for the predominant volcanic phenomena that may affect c.900,000 people living around the volcano. The methodology accounts for the natural variability displayed by volcanoes in their eruptive behaviour, such as different types/sizes of eruptions and possible vent locations. For this purpose, we treat probabilistically several model runs for some of the main hazardous phenomena (lahars, pyroclastic density currents (PDCs), tephra fall and ballistic ejecta) and data from past eruptions at El Misti (tephra fall, PDCs and lahars) and at other volcanoes (PDCs). The hazard maps, although neglecting possible interactions among phenomena or cascade effects, have been produced with a homogeneous method and refer to a common time window of 1 year. The probability maps reveal that only the north and east suburbs of Arequipa are exposed to all volcanic threats except for ballistic ejecta, which are limited to the uninhabited but touristic summit cone. The probability for pyroclastic density currents reaching recently expanding urban areas and the city along ravines is around 0.05 %/year, similar to the probability obtained for roof-critical tephra loading during the rainy season. Lahars represent by far the most probable threat (around 10 %/year) because at least four radial drainage channels can convey them approximately 20 km away from the volcano across the entire city area in heavy rain episodes, even without eruption. The Río Chili Valley represents the major concern to city safety owing to the probable cascading effect of combined threats: PDCs and rockslides, dammed lake break-outs and subsequent lahars or floods. Although this study does not intend to replace the current El Misti hazard map, the quantitative results of this probabilistic multi-hazard assessment can be incorporated into a multi-risk analysis, to support decision makers in any future improvement of the current hazard evaluation, such as further land-use planning and possible emergency management.     

Quantifying risk to agriculture from volcanic ashfall: a case study from the Bay of Plenty,New Zealand

Natural Hazards - Quantitatively assessing long-term volcanic risk can be challenging due to the many variables associated with volcanic hazard and vulnerability. This study presents a structured...     

Bayesian event tree for eruption forecasting (BET_EF) at Vesuvius,Italy: a retrospective forward application to the 1631 eruption

Reliable forecasting of the next eruption at Vesuvius is the main scientific factor in defining effective strategies to reduce volcanic risk in one of the most dangerous volcanic areas of the world. In this paper, we apply a recently developed probabilistic code for eruption forecasting to new and independent historical data related to the pre-eruptive phase of the 1631 eruption. The results obtained point out three main issues: (1) the importance of “cold” historical data (according to Guidoboni 2008) related to pre-eruptive phases for evaluating forecasting tools and possibly refining them; (2) the BET_EF code implemented for Vesuvius would have forecasted the 1631 eruption satisfactorily, marking different stages of the pre-eruptive phase; (3) the code shows that pre-eruptive signals that significantly increase the probability of eruption were likely detected more than 2 months before the event.