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We present a Bayesian statistical approach to estimate volumes for a series of eruptions from an assemblage of sparse proximal and distal tephra (volcanic ash) deposits. Most volume estimates are of widespread tephra deposits from large events using isopach maps constructed from observations at exposed locations. Instead, we incorporate raw thickness measurements, focussing on tephra thickness data...
Detailed tephrochronologies are built to underpin probabilistic volcanic hazard forecasting, and to understand the dynamics and history of diverse geomorphic, climatic, soil-forming and environmental processes. Complicating factors include highly variable tephra distribution over time; difficulty in correlating tephras from site to site based on physical and chemical properties; and uncertain age...
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