Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/15743
Authors: Tadini, Alessandro* 
Aravena, Álvaro* 
Bevilacqua, Andrea* 
Samaniego, Pablo* 
Bernard, Benjamin* 
Hidalgo, Silvana* 
Azzaoui, Nourddine* 
Roche, Olivier* 
Title: Pyroclastic density currents and tephra fallout hazard assessment at Tungurahua volcano, Ecuador: hazard maps with uncertainty quantification
Issue Date: 2022
Keywords: multihazard
Tungurahua
Abstract: Pyroclastic currents (PCs) and tephra fallout are among the major volcanic hazards at explosive volcanoes and have been widely studied over the past decades in order to model the physical processes controlling them. The aim of such efforts is using numerical models for producing probabilistic hazard maps, and complementing such maps with a quantification of the major sources of uncertainty. In this contribution we chose Tungurahua volcano (Ecuador) as a case-study for producing hazard maps for both PCs and tephra fallout for two eruption types (VEI 3 and 4). Concerning PCs we adopt the models ECMapProb 2.0 and BoxMapProb 2.0; the first model is based on the energy cone assumption, while the second is a “box model” integral model. Both follow a tree-branching approach to enhance the channeled features of the flows. We implement structured and reproducible strategies to calibrate input parameters on the data of past eruptions, by considering well-documented benchmark PC-forming events. We compare the hazard maps derived from the application of different calibration metrics and models. Concerning tephra fallout, we perform Monte Carlo simulations coupling the plume model PLUME-MoM and the tephra dispersal model HYSPLIT. First, we quantify the average under/overestimation of the thickness outputs in a particular scenario. Then we sample the uncertainty distributions of the input parameters in various eruptive scenarios (total fallout mass, eruption duration, average plume height). We compare the results based on different sampling strategies, in which we sample two of the inputs and infer the third from them. This enables the replication of input correlation structures. Finally, we describe the hazard maps of the two phenomena separately and then we discuss them in terms of the implications of their combination. Our results provide the quantitative basis for a multi-hazard assessment that may enable better operative decisions to face future eruptive crises.
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