The “Mera” lahar deposit in the upper Amazon basin: Transformation of a late Pleistocene collapse at Huisla volcano, central Ecuador

Bedón, P.A. Espín; Mothes, Patricia; Hall, Minard L.; Arcos, Viviana Valverde; Keen, Hayley Frances

doi:10.1016/j.jvolgeores.2018.10.008

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…3) The LaharFlow 5 model for syn-eruptive or 'hot' lahars generated by snow cap melting (Woodhouse et al, 2016;Tierz et al, 2017;Espín Bedón et al, 2019). 4) The Decreasing Probability model within the Q-LavHA framework (v. 3.0) 6 for blocky lava flows (Felpeto et al, 2001;Bonne et al, 2008;Mossoux et al, 2016).…”

Section: Selection Of Computational Modelsmentioning

confidence: 99%

“…The parameters of LaharFlow were calibrated by using data from the 1985 Nevado del Ruiz lahar (Pierson et al, 1990). Even though LaharFlow is a relatively recent model, it has already been tested to model lahars in the literature (Tierz et al, 2017;Espín Bedón et al, 2019). The first-order parameters in LaharFlow are the DEM resolution and the volume.…”

Section: Selection Of Computational Modelsmentioning

confidence: 99%

“…LaharFlow occupies the Shuttle Radar Topography Mission (SRTM) 30-m global DEM (Farr et al, 2007), which can be extrapolated to create lower-resolution DEMs, with the intent to decrease computational time costs. Other important parameters of the model are the erosion rate, the erosion depth, and the granular friction, although no published works have produced sensitivity analyses to identify the variability of results from the use of different values in these parameters (Tierz et al, 2017;Espín Bedón et al, 2019). We have selected LaharFlow because it is a real-time model that has an initial volume parameter, which can be used to co-parameterize the volume of different phenomena in the same intra-scenario.…”

Section: Selection Of Computational Modelsmentioning

confidence: 99%

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A GIS-based multi-hazard assessment at the San Pedro volcano, Central Andes, northern Chile

et al. 2022

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Recent advances in the modeling of volcanic phenomena have allowed scientists to better understand the stochastic behavior of volcanic systems. Eruptions can produce various types of volcanic phenomena of different sizes. The size of a given volcanic phenomenon dominates its spatial distribution and is commonly represented by volume/mass parameters in the models that reproduce their behavior. Multi-hazard assessments depend on first-order parameters to forecast hazards at a given geographic location. However, few multi-hazard assessments consider the size of the eruption (e.g., tephra fallout) to co-parameterize the size of the accompanying phenomena (e.g., mass flows) in a given eruptive scenario. Furthermore, few studies simulate multi-phenomenon eruptive scenarios with semi-continuous variations in their size, something that allows a better quantification of the aleatoric variability of the system. Here, we present a multi-hazard assessment of the San Pedro volcano, a high-threat volcano from northern Chile, that produced two large-size Plinian eruptions (VEI 5 and 6) in the last 16 ka, and ten Strombolian eruptions (VEI 2) between 1870 and 2021 CE, with the latest occurring on 2 December 1960 CE. We use intra-scenarios (i.e., subdivisions of eruptive scenarios) to explore the size variability of explosive volcanic phenomena. The size of intra-scenarios is extrapolated from the largest-size deposits of each type of phenomenon from the geologic record of the San Pedro volcano. We simulate explosive intra-scenarios for tephra fallout, concentrated PDCs, and lahars, and effusive scenarios for blocky lava flows. On the local scale, mass flows are likely (66–100%) to affect transport and energy infrastructure within a 14 km radius of the volcano. On the regional scale, large-size eruptions (VEI 5) in the rainy season are about as likely as not (33–66%) to accumulate 1 cm of tephra on energy, transport, and mining infrastructure over a 50 km radius, and these same eruptions are unlikely (10–33%) to accumulate 1 cm of tephra on the city of Calama. This work shows how multi-phenomenon intra-scenarios can be applied to better quantify the aleatoric variability of the type and size of volcanic phenomena in hazard assessments.

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