How do the grain size characteristics of a tephra deposit change over time?

Financial support was provided by the National Science Foundation of America through grant 1202692 ‘Comparative Island Ecodynamics in the North Atlantic’ and grant 1249313 ‘Tephra layers and early warning signals for critical transitions’ (both to AJD).Volcanologists frequently use grain size distributions (GSDs) in tephra layers to infer eruption parameters. However, for long-past eruptions, the accuracy of the reconstruction depends upon the correspondence between the initial tephra deposit and preserved tephra layer on which inferences are based. We ask: how closely does the GSD of a decades-old tephra layer resemble the deposit from which it originated? We addressed this question with a study of the tephra layer produced by the eruption of Mount St Helens, USA, in May 1980. We compared grain size distributions from the fresh, undisturbed tephra with grain size measurements from the surviving tephra layer. We found that the overall grain size characteristics of the tephra layer were similar to the original deposit, and that distinctive features identified by earlier authors had been preserved. However, detailed analysis of our samples showed qualitative differences, specifically a loss of fine material (which we attributed to ‘winnowing’). Understanding how tephra deposits are transformed over time is critical to efforts to reconstruct past eruptions, but inherently difficult to study. We propose long-term, tephra application experiments as a potential way forward.Publisher PDFPeer reviewe

Methodology of determining the uncertainity in the accessible geothermal-resource base of identified hydrothermal convection systems

In order to quantify the uncertainty of estimates of the geothermal-resource base in identified hydrothermal convection systems, a methodology is presented for combining estimates with uncertainties for temperature, area, and thickness of a geothermal reservoir into an estimate of the stored energy with uncertainty. Probability density functions for temperature, area, and thickness are assumed to be triangular in form. In order to calculate the probability distribution function for the stored energy in a single system or in many systems, a computer program for aggregating the input distribution functions using the Monte-Carlo method has been developed. To calculate the probability distribution of stored energy in a single system, an analytical expression is also obtained that is useful for calibrating the Monte Carlo approximation. For the probability distributions of stored energy in a single and in many systems, the central limit approximation is shown to give results ranging from good to poor

Chemistry of spring and well waters on Kilauea Volcano, Hawaii, and vicinity

Published and new data for chemical and isotopic samples from wells and springs on Kilauea Volcano and vicinity are presented. These data are used to understand processes that determine the chemistry of dilute meteoric water, mixtures with sea water, and thermal water. Data for well and spring samples of non-thermal water indicate that mixing with sea water and dissolution of rock from weathering are the major processes that determine the composition of dissolved constituents in water. Data from coastal springs demonstrate that there is a large thermal system south of the lower east rift of Kilauea. Samples of thermal water from shallow wells in the lower east rift and vicinity have rather variable chemistry indicating that a number of processes operate in the near surface. Water sampled from the available deep wells is different in composition from the shallow thermal water, indicating that generally there is not a significant component of deep water in the shallow wells. Data for samples from available deep wells show significant gradients in chemistry and steam content of the reservoir fluid. These gradients are interpreted to indicate that the reservoir tapped by the existing wells is an evolving vapor-dominated system