Probabilistic Methodology for Long-Term Assessment of Volcanic Hazards

Jaquet, Olivier; Connor, Charles B.; Connor, L.

doi:10.13182/nt08-a3980

Cited by 33 publications

(28 citation statements)

References 11 publications

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“…However, some examples exist: Cox processes have been applied to the assessment of long-term volcanic hazards (e.g., Jaquet et al, 2000Jaquet et al, , 2008Jaquet and Carniel, 2006); self-exciting processes have been introduced for modeling the temporal eruptive pattern of volcanic fields (e.g., Bebbington and Cronin, 2011); a complete long-term PDC hazard assessment procedure has been developed at the Montserrat volcano, combining probability estimates of time, size and direction of the flows (Bayarri et al, 2009(Bayarri et al, , 2015. A detailed review also including other approaches has been described in Bebbington (2013).…”

Section: Temporal Model For Explosive Eruptionsmentioning

confidence: 99%

The Effects of Vent Location, Event Scale, and Time Forecasts on Pyroclastic Density Current Hazard Maps at Campi Flegrei Caldera (Italy)

et al. 2017

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This study presents a new method for producing long-term hazard maps for pyroclastic density currents (PDC) originating at Campi Flegrei caldera. Such method is based on a doubly stochastic approach and is able to combine the uncertainty assessments on the spatial location of the volcanic vent, the size of the flow and the expected time of such an event. The results are obtained by using a Monte Carlo approach and adopting a simplified invasion model based on the box model integral approximation. Temporal assessments are modeled through a Cox-type process including self-excitement effects, based on the eruptive record of the last 15 kyr. Mean and percentile maps of PDC invasion probability are produced, exploring their sensitivity to some sources of uncertainty and to the effects of the dependence between PDC scales and the caldera sector where they originated. Conditional maps representative of PDC originating inside limited zones of the caldera, or of PDC with a limited range of scales are also produced. Finally, the effect of assuming different time windows for the hazard estimates is explored, also including the potential occurrence of a sequence of multiple events. Assuming that the last eruption of Monte Nuovo (A.D. 1538) marked the beginning of a new epoch of activity similar to the previous ones, results of the statistical analysis indicate a mean probability of PDC invasion above 5% in the next 50 years on almost the entire caldera (with a probability peak of ∼25% in the central part of the caldera). In contrast, probability values reduce by a factor of about 3 if the entire eruptive record is considered over the last 15 kyr, i.e., including both eruptive epochs and quiescent periods.

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Section: Temporal Model For Explosive Eruptionsmentioning

confidence: 99%

The Effects of Vent Location, Event Scale, and Time Forecasts on Pyroclastic Density Current Hazard Maps at Campi Flegrei Caldera (Italy)

et al. 2017

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“…Published works in this field (Connor and Hill, 1995;Felpeto et al, 2007;Jaquet et al, 2008;Martí and Felpeto, 2010;Favalli et al, 2011;Connor et al, 2012;Cappello et al, 2012Cappello et al, , 2013 report the use of kernel density functions to evaluate susceptibility. However, this technique is based mainly on the assumption that new vents will not form far from existing ones (Martin et al, 2004;Jaquet et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…However, this technique is based mainly on the assumption that new vents will not form far from existing ones (Martin et al, 2004;Jaquet et al, 2008). This is an a priori hypothesis for long-term hazard assessment, in which the use of volcano structural alignments (eruptive fissures, fractures, dykes) and the location of past centers of emission assumes implicitly that the general stress field has not changed significantly since the formation of these structures.…”

Section: Introductionmentioning

confidence: 99%

QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

Bartolini

Cappello

Martı́

et al. 2013

Nat. Hazards Earth Syst. Sci.

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Abstract. One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps (i.e., the spatial probability of a future vent opening given the past eruptive activity of a volcano). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source geographic information system Quantum GIS, which is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows the selection of an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

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“…For this reason the models are constructed, implicitly, as doubly stochastic (e.g., Cox & Isham, 1980;Daley & Vere-Jones, 2005, 2008Jaquet et al, 2008Jaquet et al, , 2012. This means that the statistical distribution of the location of the next eruptive vent is represented using illconstrained parameters.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2017

SIV

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The Long Valley volcanic region is an active volcanic area situated at the eastern base of the Sierra Nevada escarpment and dominated by a 32 km wide resurgent caldera created~760 ka. Eruptions after 180 ka have been localized at Mammoth Mountain on the western rim of the caldera and along the Mono-Inyo Craters volcanic chain stretching about 45 km northward. Three different probability models have been developed and then combined in a logic tree to estimate the long-term spatial probability of vent opening. These models include (i) an anisotropic kernel density estimator based on past vent locations, (ii) a new Bayesian model for coupling new vents with pre-existing faults, and (iii) a uniformly distributed probability map. The model combination procedure relies on Bayesian model averaging. Using a doubly stochastic framework enables us to incorporate some of the main sources of epistemic uncertainty about the interpretation of the volcanic system, thereby exploring their effect. Our vent-opening probability maps show two higher likelihood regions for new vent opening, one around Mammoth Mountain to the south, and the other along the Mono-Inyo Craters to the north. The spatial vent opening probability, conditional on an eruption, is estimated as~64% in the northern region and~36% in the southern region, with an uncertainty of about ±20%. These findings provide a rational basis for the hazard mapping of a potential eruption in the Long Valley volcanic region, suggesting that the hazard associated with Mammoth Mountain volcanism should be fully evaluated.

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Probabilistic Methodology for Long-Term Assessment of Volcanic Hazards

Cited by 33 publications

References 11 publications

The Effects of Vent Location, Event Scale, and Time Forecasts on Pyroclastic Density Current Hazard Maps at Campi Flegrei Caldera (Italy)

The Effects of Vent Location, Event Scale, and Time Forecasts on Pyroclastic Density Current Hazard Maps at Campi Flegrei Caldera (Italy)

QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

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