Dynamics and Modelling of the 2015 Calbuco eruption Volcanic Debris Flows (Chile). From field evidence to a primary lahar model

  • Felipe A Flores

Student thesis: Master's ThesisMaster of Science by Research (MScR)


The Calbuco volcanic eruption of 2015, was characterized by two explosive phases with partial
and major column collapses that triggered lahars in many of the flanks of the volcano. Large lahar flows descended to the southern flank where highly fractured ice bodies were emplaced on steep slopes.
In this study, we present a chronology of the volcanic flows based on a multi parameter
data set that includes social media, reports of authoritative institutions, instrumental monitoring
data and published research literature on the eruption. Our review established that
lahars in the Amarillo river began during the first phase of the eruption due to the sustained emplacement of pyroclastic flows in its catchment. In contrast, we propose that the lahars in the
Blanco – Correntoso river system and the Este river were likely to have been triggered by a
sudden mechanical collapse of the glacier that triggered mixed avalanches which transitioned
into lahars downstream.
Our observations include inundation cross-sections, estimates of flow speeds, and characterization of the morphology, grain sizes, and componentry of deposits.
Field measurements are used together with instrumental data for calibrating a dynamic, physics-based model of lahar, Laharflow. We model flows in the Blanco – Correntoso river system and explore the influence of the model parameters on flow predictions in an ensemble of simulations. We develop a calibration that accounts for the substantial epistemic uncertainties in our observations and the model formulation, that seeks to determine plausible ranges for the model parameters, including those representing the lahar source. Our approach highlights the parameters in the model that have a dominant effect on the ability of the model to match observations, indicating where further development and additional observations could improve model predictions. The simulations in our ensemble that provide plausible matches to the observations are combined to produce flow inundation maps.
Date of Award23 Jan 2024
Original languageEnglish
Awarding Institution
  • University of Bristol
SupervisorM J Woodhouse (Supervisor) & Jeremy C Phillips (Supervisor)

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