A GIS-based methodology for the estimation of potential volcanic damage and its application to Tenerife Island, Spain

Scaini, Chiara; Felpeto, A.; Martı́, Joan; Carniel, Roberto

doi:10.1016/j.jvolgeores.2014.04.005

Cited by 17 publications

(30 citation statements)

References 75 publications

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“…With growing use, KDE was expanded to include spatio-temporal models of volcanism (Bebbington & Cronin, 2011) and coupled to other hazard models, particularly lava flows hazards (e.g., Favalli et al, 2012;Connor et al, 2012;Cappello et al, 2012;Runge et al, 2014), and to include uncertainty quantification (Jaquet et al, 2008;Bevilacqua et al, 2017). Spatial density analysis has been incorporated into commonly used hazard applications including QVAST (Bartolini et al, 2013), VORIS (Felpeto et al, 2007;Scainia et al, 2014), and MatHaz (Bertin et al, 2019), although in some of these applications the term spatial density has been replaced by spatial susceptibility or spatial vulnerability. KDE played a major role for a Yucca Mountain probabilistic volcanic hazard analysis update (PVHA-U), to further inform a panel of experts during the formal expert elicitation process (Coppersmith et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

How to use kernel density estimation as a diagnostic and forecasting tool for distributed volcanic vents

Connor

Germa

et al. 2019

SIV

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2019) How to use kernel density estimation as a diagnostic and forecasting tool for distributed volcanic vents, Statistics in Volcanology 4.3 : 1 − 25. AbstractVolcanic activity often results in the formation of new volcanic vents. These new vents can create hazards in unexpected areas. Therefore, the probability of new vent formation should be assessed as part of volcanic hazard assessments. This paper describes our use of kernel density estimation (KDE) as a way to estimate the spatial density of future volcanic vents. The bivariate Gaussian kernel function is described step-by-step using pseudocode. Our computer code, written in PERL, is used to calculate the spatial density of existing vents and then create a contour map using GMT (Generic Mapping Tools). Application of this method and code relies on several assumptions about the definition of volcanic events, independence of events, the type of kernel function used, and the selection of kernel bandwidth. Three examples using the code are provided: (1) for volcanic vents located west of the city of Managua (Nicaragua), (2) for volcanic vents distributed within the Arsia Mons caldera (Mars), weighted by volume, and (3) for vents of the Lassen volcanic system (northern California), sub-divided by geochemistry.

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Section: Introductionmentioning

confidence: 99%

How to use kernel density estimation as a diagnostic and forecasting tool for distributed volcanic vents

Connor

Germa

et al. 2019

SIV

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“…In order to build a social vulnerability assessment system, social-economic statistical data were required to retrieve indicators. Based on previous studies [1,12] and the availability of data, we collected a variety of social-economic statistical data on infrastructure, economics, administration and population (Table 2) for extracting indicators required for social vulnerability analysis (see Section 3.2.1). Because it was challenging to obtain data all acquired in 2017, data acquired in neighboring years were replaced instead.…”

Section: Socio-economic Statisticsmentioning

confidence: 99%

“…The eruption is weaker (eruptive column 3 km high) than that at the central edifice. Basaltic lava flows downstream from high-susceptibility vents on the two ridges [12].…”

Section: Eruptive Scenariosmentioning

confidence: 99%

“…In addition to hazard analysis, vulnerability analysis (aka vulnerability assessment) is the other component of risk assessment and refers to evaluating the vulnerability of elements (e.g., communities, systems and assets) exposed to volcanic hazards [1,11]. Volcanic risk assessment requires comprehensive consideration of volcanic hazards and vulnerability [11,12]. Risk assessment is critical for volcanic islands, as it can provide knowledge of the impact of potential volcanic hazards and identify vulnerable populations and areas.…”

Section: Introductionmentioning

confidence: 99%

“…Marrero et al [18] assessed the number of potential fatalities caused by pyroclastic density currents (PDCs, mixtures of fragmented volcanic particles, hot gases and ash that spread from a volcano at high speeds [19,20]) from the central volcanic complex, but this assessment exclusively investigated the impact of one hazard, PDCs, on population. A comprehensive recent volcanic risk assessment was performed by Scaini et al [12], but again was limited to a small area consisting of Icod de los Vinos, San Juan de la Rambla and La Guancha. While all these studies provide important data, no comprehensive volcanic hazard risk assessment identifying vulnerable and high-risk areas has been undertaken for the whole volcanic island to date.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Testing a Comprehensive Volcanic Risk Assessment of Tenerife by Volcanic Hazard Simulations and Social Vulnerability Analysis

Liu

Chen

et al. 2020

IJGI

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Volcanic activity remains highly detrimental to populations, property and activities in the range of its products. In order to reduce the impact of volcanic processes and products, it is critically important to conduct comprehensive volcanic risk assessments on volcanically active areas. This study tests a volcanic risk assessment methodology based on numerical simulations of volcanic hazards and quantitative analysis of social vulnerability in the Spanish island of Tenerife, a well-known tourist destination. We first simulated the most likely volcanic hazards in the two eruptive scenarios using the Volcanic Risk Information System (VORIS) tool and then evaluated the vulnerability using a total of 19 socio-economic indicators within the Vulnerability Scoping Diagram (VSD) framework by combining the analytic hierarchy process (AHP) and the entropy method. Our results show good agreement with previous assessments. In two eruptive scenarios, the north and northwest of the island were more exposed to volcanic hazards, and the east registered the highest vulnerability. Overall, the northern municipalities showed the highest volcanic risk in two scenarios. Our test indicates that disaster risk varies greatly across the island, and that risk reduction strategies should be prioritized on the north areas. While refinements to the model will produce more accurate results, the outputs will still be beneficial to the local authorities when designing policies for volcanic risk reduction policies in Tenerife. This study tests a comprehensive volcanic risk assessment for Tenerife, but it also provides a framework that is applicable to other regions threatened by volcanic hazards.

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Probabilistic E-tools for Hazard Assessment and Risk Management

Bartolini

Martı́

Sobradelo

et al. 2017

Advances in Volcanology

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The impact of a natural event can significantly affect human life and the environment. Although fascinating, a volcanic eruption creates similar or even greater problems than more frequent natural events due to its multi-hazard nature and the intensity and extent of its potential impact. It is possible to live near a volcanic area and take advantage of the benefits that volcanoes offer, but it is also important to be aware of the existing threats and to know how to minimise risks. In this chapter, we present an integrated approach using e-tools for assessing volcanic hazard and risk management. These tools have been especially designed to assess and manage volcanic risk, to evaluate longand short-term volcanic hazards, to conduct vulnerability analysis, and to assist decision-makers during the management of a volcanic crisis. The methodology proposed here can be implemented before an emergency in order to identify optimum mitigating actions and how these may have to be adapted as new information is obtained. These tools also allow us identifying the most appropriate probabilistic and statistical techniques for volcanological data analysis and treatment in the context of quantitative hazard and risk assessments. Understanding volcanic unrest, forecasting volcanic eruptions, and predicting the most probable scenarios, all imply a high degree of inherent uncertainty, which needs to be quantified and clearly explained when transmitting scientific information to decision-makers. Resumen El impacto de un evento natural puede afectar significativamente la vida humana y el medio ambiente. Aunque fascinante, una erupción volcánica

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A GIS-based methodology for the estimation of potential volcanic damage and its application to Tenerife Island, Spain

Cited by 17 publications

References 75 publications

How to use kernel density estimation as a diagnostic and forecasting tool for distributed volcanic vents

How to use kernel density estimation as a diagnostic and forecasting tool for distributed volcanic vents

Testing a Comprehensive Volcanic Risk Assessment of Tenerife by Volcanic Hazard Simulations and Social Vulnerability Analysis

Probabilistic E-tools for Hazard Assessment and Risk Management

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