Hazard area and probability of volcanic disruption of the proposed high-level radioactive waste repository at Yucca Mountain, Nevada, USA

Ho, Chih-Hsiang; Smith, Eugene I.; Keenan, Deborah L.

doi:10.1007/s00445-006-0058-5

Cited by 13 publications

(13 citation statements)

References 25 publications

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“…Some of the earliest, (Wickman, 1965(Wickman, , 1976Reyment, 1969;Klein, 1982) employed stochastic principles to analyze eruption patterns. Further studies included transition probabilities of Markov chains (Carta et al, 1981;Aspinall et al, 2006;Bebbington, 2007), Bayesian analysis of volcanic activity (Ho, 1990;Solow, 2001;Newhall and Hoblitt, 2002;Ho et al, 2006;Marzocchi et al, 2008), homogeneous and non-homogeneous Poisson process applied to volcanic series (De la Cruz-Reyna, 1991;426 A. T. Mendoza-Rosas and S. De la Cruz-Reyna: A simple and precise assessment of the volcanic hazard 1996a, b), geostatistical hazard-estimation methods (Jaquet et al, 2000;Jaquet and Carniel, 2006), a mixture of Weibull distributions (Turner et al, 2008) and non-homogeneous statistics to link geological and historical eruption time series (Mendoza-Rosas and De la ). An exhaustive list of the available literature on this subject is beyond the scope of this paper, and the above references only attempt to illustrate the diversity of methods that have been applied to the volcanic eruption sequences.…”

Section: Introductionmentioning

confidence: 99%

A mixture of exponentials distribution for a simple and precise assessment of the volcanic hazard

Mendoza-Rosas¹,

Cruz‐Reyna²

2009

Nat. Hazards Earth Syst. Sci.

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Abstract. The assessment of volcanic hazard is the first step for disaster mitigation. The distribution of repose periods between eruptions provides important information about the probability of new eruptions occurring within given time intervals. The quality of the probability estimate, i.e., of the hazard assessment, depends on the capacity of the chosen statistical model to describe the actual distribution of the repose times. In this work, we use a mixture of exponentials distribution, namely the sum of exponential distributions characterized by the different eruption occurrence rates that may be recognized inspecting the cumulative number of eruptions with time in specific VEI (Volcanic Explosivity Index) categories. The most striking property of an exponential mixture density is that the shape of the density function is flexible in a way similar to the frequently used Weibull distribution, matching long-tailed distributions and allowing clustering and time dependence of the eruption sequence, with distribution parameters that can be readily obtained from the observed occurrence rates. Thus, the mixture of exponentials turns out to be more precise and much easier to apply than the Weibull distribution. We recommended the use of a mixture of exponentials distribution when regimes with well-defined eruption rates can be identified in the cumulative series of events. As an example, we apply the mixture of exponential distributions to the repose-time sequences between explosive eruptions of the Colima and Popocatépetl volcanoes, México, and compare the results obtained with the Weibull and other distributions.

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Section: Introductionmentioning

confidence: 99%

A mixture of exponentials distribution for a simple and precise assessment of the volcanic hazard

Mendoza-Rosas¹,

Cruz‐Reyna²

2009

Nat. Hazards Earth Syst. Sci.

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“…Bebbington and Lai (1996a) applied a Weibull renewal model to describe the patterns of New Zealand volcanoes. Other studies used transition probabilities of Markov chains (Carta et al, 1981;Aspinall et al, 2006;Bebbington, 2007), change-point detection techniques (Mulargia et al, 1987;Burt et al, 1994), Rank-order statistics (Pyle, 1998), Bayesian analysis of volcanic activity (Ho, 1990;Solow, 2001;Newhall and Hoblitt, 2002;Ho et al, 2006;Marzocchi et al, 2008;Sobradelo and Martí, 2010), non-homogeneous models (Ho, 1991;Bebbington and Lai, 1996b), a mixture of Weibull distributions (Turner et al, 2007), geostatistical hazard-estimation methods (Jaquet et al, 2000;, and a mixture of exponential distributions (Mendoza-Rosas and De la Cruz-Reyna, 2009Dzierma and Wehrmann, 2010a,b). Extreme-value methods have been applied to geological and historical eruption time series combined (Mendoza-Rosas and De la Cruz-Reyna, 2008 and historical series of large volcanic magnitudes (Coles and Sparks, 2006).…”

Section: Introductionmentioning

confidence: 99%

Volcanic hazard assessment for the Canary Islands (Spain) using extreme value theory

Sobradelo

Martı́

Mendoza-Rosas³

et al. 2011

Nat. Hazards Earth Syst. Sci.

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Abstract. The Canary Islands are an active volcanic region densely populated and visited by several millions of tourists every year. Nearly twenty eruptions have been reported through written chronicles in the last 600 yr, suggesting that the probability of a new eruption in the near future is far from zero. This shows the importance of assessing and monitoring the volcanic hazard of the region in order to reduce and manage its potential volcanic risk, and ultimately contribute to the design of appropriate preparedness plans. Hence, the probabilistic analysis of the volcanic eruption time series for the Canary Islands is an essential step for the assessment of volcanic hazard and risk in the area. Such a series describes complex processes involving different types of eruptions over different time scales. Here we propose a statistical method for calculating the probabilities of future eruptions which is most appropriate given the nature of the documented historical eruptive data. We first characterize the eruptions by their magnitudes, and then carry out a preliminary analysis of the data to establish the requirements for the statistical method. Past studies in eruptive time series used conventional statistics and treated the series as an homogeneous process. In this paper, we will use a method that accounts for the time-dependence of the series and includes rare or extreme events, in the form of few data of large eruptions, since these data require special methods of analysis. Hence, we will use a statistical method from extreme value theory. In particular, we will apply a non-homogeneous Correspondence to: R. Sobradelo (rsobradelo@ija.csic.es) Poisson process to the historical eruptive data of the Canary Islands to estimate the probability of having at least one volcanic event of a magnitude greater than one in the upcoming years. This is done in three steps: First, we analyze the historical eruptive series to assess independence and homogeneity of the process. Second, we perform a Weibull analysis of the distribution of repose time between successive eruptions. Third, we analyze the non-homogeneous Poisson process with a generalized Pareto distribution as the intensity function.

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“…That being said, we note that full PVHA is still quite rare (Magill et al 2006;Ho et al 2006;Neri et al 2008;Marti et al 2008 are among the few exceptions).…”

Section: Introductionmentioning

confidence: 75%

BET_VH: a probabilistic tool for long-term volcanic hazard assessment

2010

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In this paper, we illustrate a Bayesian Event Tree to estimate Volcanic Hazard (BET_VH). The procedure enables us to calculate the probability of any kind of long-term hazardous event for which we are interested, accounting for the intrinsic stochastic nature of volcanic eruptions and our limited knowledge regarding related processes. For the input, the code incorporates results from numerical models simulating the impact of hazardous volcanic phenomena on an area and data from the eruptive history. For the output, the code provides a wide and exhaustive set of spatiotemporal probabilities of different events; these probabilities are estimated by means of a Bayesian approach that allows all uncertainties to be properly accounted for. The code is able to deal with many eruptive settings simultaneously, weighting each with its own probability of occurrence. In a companion paper, we give a detailed example of application of this tool to the Campi Flegrei caldera, in order to estimate the hazard from tephra fall.

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Hazard area and probability of volcanic disruption of the proposed high-level radioactive waste repository at Yucca Mountain, Nevada, USA

Cited by 13 publications

References 25 publications

A mixture of exponentials distribution for a simple and precise assessment of the volcanic hazard

A mixture of exponentials distribution for a simple and precise assessment of the volcanic hazard

Volcanic hazard assessment for the Canary Islands (Spain) using extreme value theory

BET_VH: a probabilistic tool for long-term volcanic hazard assessment

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