Quantifying uncertainties in the measurement of tephra fall thickness

Engwell, Samantha; Sparks, R. S. J.; Aspinall, Willy

doi:10.1186/2191-5040-2-5

Cited by 81 publications

(99 citation statements)

References 24 publications

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“…Tephra thickness is influenced by eruption dynamics, topographic variations, compaction, erosion and deposition, and bioturbation (Engwell et al 2013). While the relative importance of these influences is rarely examined numerous observations attest to the rapid erosion from hillslopes of recently emplaced tephra.…”

Section: Introductionmentioning

confidence: 99%

Preservation of thin tephra

Blong

Enright

Grasso³

2017

J Appl. Volcanol.

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The preservation of thin (<300 mm thick) tephra falls was investigated at four sites in Papua New Guinea (PNG), Alaska and Washington, USA. Measurements of the variations in the thickness of: (i) Tibito Tephra 150 km downwind from the source, Long Island (PNG) erupted mid-seventeenth century; (ii) St Helens W tephra (erupted 1479-80 A.D.) on the slopes of the adjacent Mt. Rainier in Washington State; (iii) Novarupta (1912) tephra preserved on Kodiak Island (Alaska, USA); and (iv) an experimentally placed tephra at a site near Mt. Hagen (PNG) allow tentative conclusions to be drawn about the relative importance to tephra preservation of slope gradients, vegetation cover and soil faunal activity. Results for the experimental tephra suggest that compaction occurs rapidly post-deposition and that estimates of tephra thickness and bulk density need to indicate how long after deposition thickness measurements were made. These studies show that erosional reworking of thin tephra is not rapid even on steeper slopes in high rainfall environments. In Papua New Guinea a 350-year old tephra is rarely present under forest but is well-preserved under alpine grasslands. On Mt. Rainier 500-year old tephra is readily preserved under forest but absent under grasslands as a result of gopher activity. Despite the poor relationship between tephra thickness and slope steepness the thickness of thin tephras is highly variable. On Kodiak Island thickness variability across a few metres is similar to that observed across the whole northeast of the island. The measured variability reported here indicates large sample sizes are necessary to adequately estimate the mean thickness of these thin tephra. These results have implications for the preparation of isopach maps, estimation of tephra volumes and elaboration of the potential consequences of tephra falls.

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Section: Introductionmentioning

confidence: 99%

Preservation of thin tephra

Blong

Enright

Grasso³

2017

J Appl. Volcanol.

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“…Typical field-based input parameters used to derive ESPs relate to the compilation of isopleth and isopach maps (i.e., crosswind and downwind ranges of isopleth maps, diameter of maximum clasts, deposit thickness, and area of isopach contours). We do not aim to quantify the typical ranges of errors associated with field-based input parameters but strongly encourage systematic studies of the uncertainty related to the variability of deposits, measurement techniques and subjective interpretations following the works of Barberi et al (1995), Biass & Bonadonna (2011), Cioni et al (2011, Engwell et al (2013), Klawonn et al (2014a) and Klawonn et al (2014b). Four additional key input parameters are considered in the TError package (empirical constants of Wilson & Walker (1987) and Mastin et al (2009), distal integration limit of Bonadonna & Houghton (2005) and wind speed at the tropopause) in order to assess the sensitivity related to the choice of given values.…”

Section: Discussionmentioning

confidence: 99%

“…If recent studies suggest mainly lognormal distribution of errors related to measurement and deposit uncertainties (Engwell et al, 2013;Klawonn et al, 2014b), these systematic investigations are focused on the calculation of the erupted volume only. In TError, in the absence of more detailed studies on the possible shape of the uncertainty related to input parameters, we implemented Gaussian and uniform distributions of uncertainty mainly for simplicity.…”

Section: Propagation Of Errormentioning

confidence: 99%

“…For example, volume estimates published in the Icelandic literature are traditionally reported as freshly fallen since the work of Thorarinsson (1967), where the volume obtained from field measurements is expanded by a factor of 40% to account for compaction processes. Similarly, the fraction of ash (< 2 mm) can undergo compaction leading to an increase of density and a decrease of thickness up to 50% in a couple of years (Engwell et al, 2013). The second kind of uncertainty relates to measurements.…”

Section: Introductionmentioning

confidence: 99%

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TError: towards a better quantification of the uncertainty propagated during the characterization of tephra deposits

Biass¹,

Bagheri²,

Aeberhard³

et al. 2013

SIV

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We present TError, a Matlab package designed to quantify systematically the uncertainty associated with the characterization of tephra deposits, in which the most commonly used methods to quantify eruption source parameters are implemented. Inputs of the code are a range of field-based, model-based and empirical parameters (i.e., clast diameter, crosswind and downwind ranges, thickness measurement, area of isopach contours, bulk deposit density, empirical constants and wind speed), for which the user defines an uncertainty and an associated distribution. The TError package contains two main functions. The first function deterministically varies one input parameter at a time and quantifies the sensitivity of each Eruption Source Parameter (ESP; i.e., plume height, erupted volume, mass eruption rate) to the variability of input parameters. The second function propagates input parameters as stochastic distributions of noise through all ESPs. The resulting distributions can then be used to express the uncertainty of physical parameters of explosive eruptions in a systematic way. For both functions, comprehensive reports and sets of figures assist the user in the interpretation of the results. As an example, the TError package was applied to Layer 5 of Cotopaxi volcano. Using the median, the 2 nd percentile and the 98 th percentile as central value, lower bound and upper bound respectively, a new quantification of the ESP suggests a plume height of 30 ± 1 km a.s.l, a mass eruption rate of 1.8 citation:Biass, S., G. Bagheri, W. H. Aeberhard, C. Bonadonna (2014) TError: towards a better quantification of the uncertainty propagated during the characterization of tephra deposits, Statistics in Volcanology 1.2 : 1 − 27.

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“…For example, it is difficult to measure dynamic pressures of PDCs due to their potential to cause injury and destroy measurement equipment; therefore, the dynamic pressure is typically estimated from deposits or resulting asset damage (e.g., Jenkins et al 2013). This can lead to large uncertainties in the measurement of volcanic hazard intensity (e.g., Engwell et al 2013). Large sources of uncertainty within volcanic impact data arise from the classification of impacts into ISs and the often small sample size.…”

Section: Uncertainty Analysismentioning

confidence: 99%

Framework for developing volcanic fragility and vulnerability functions for critical infrastructure

Wilson

Deligne

et al. 2017

J Appl. Volcanol.

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Volcanic risk assessment using probabilistic models is increasingly desired for risk management, particularly for loss forecasting, critical infrastructure management, land-use planning and evacuation planning. Over the past decades this has motivated the development of comprehensive probabilistic hazard models. However, volcanic vulnerability models of equivalent sophistication have lagged behind hazard modelling because of the lack of evidence, data and, until recently, minimal demand. There is an increasingly urgent need for development of quantitative volcanic vulnerability models, including vulnerability and fragility functions, which provide robust quantitative relationships between volcanic impact (damage and disruption) and hazard intensity. The functions available to date predominantly quantify tephra fall impacts to buildings, driven by life safety concerns. We present a framework for establishing quantitative relationships between volcanic impact and hazard intensity, specifically through the derivation of vulnerability and fragility functions. We use tephra thickness and impacts to key infrastructure sectors as examples to demonstrate our framework. Our framework incorporates impact data sources, different impact intensity scales, preparation and fitting of data, uncertainty analysis and documentation. The primary data sources are post-eruption impact assessments, supplemented by laboratory experiments and expert judgment, with the latter drawing upon a wealth of semi-quantitative and qualitative studies. Different data processing and function fitting techniques can be used to derive functions; however, due to the small datasets currently available, simplified approaches are discussed. We stress that documentation of data processing, assumptions and limitations is the most important aspect of function derivation; documentation provides transparency and allows others to update functions more easily. Following our standardised approach, a volcanic risk scientist can derive a fragility or vulnerability function, which then can be easily compared to existing functions and updated as new data become available. To demonstrate how to apply our framework, we derive fragility and vulnerability functions for discrete tephra fall impacts to electricity supply, water supply, wastewater and transport networks. These functions present the probability of an infrastructure site or network component equalling or exceeding one of four impact states as a function of tephra thickness.

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Quantifying uncertainties in the measurement of tephra fall thickness

Cited by 81 publications

References 24 publications

Preservation of thin tephra

Preservation of thin tephra

TError: towards a better quantification of the uncertainty propagated during the characterization of tephra deposits

Framework for developing volcanic fragility and vulnerability functions for critical infrastructure

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