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Authors: Tarquini, S.* 
Favalli, M.* 
Title: Mapping and DOWNFLOW simulation of recent lava flow fields at Mount Etna
Issue Date: 1-Jul-2011
Series/Report no.: 1-4/204(2011)
DOI: 10.1016/j.jvolgeores.2011.05.001
Keywords: LIDAR
lava flow field
lava flow simulation
Digital elevation model
Mount Etna
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring 
04. Solid Earth::04.08. Volcanology::04.08.07. Instruments and techniques 
04. Solid Earth::04.08. Volcanology::04.08.08. Volcanic risk 
Abstract: In recent years, progress in geographic information systems (GIS) and remote sensing techniques have allowed the mapping and studying of lava flows in unprecedented detail. A composite GIS technique is introduced to obtain high resolution boundaries of lava flow fields. This technique is mainly based on the processing of LIDAR-derived maps and digital elevation models (DEMs). The probabilistic code DOWNFLOW is then used to simulate eight large flow fields formed at Mount Etna in the last 25 years. Thanks to the collection of 6 DEMs representing Mount Etna at different times from 1986 to 2007, simulated outputs are obtained by running the DOWNFLOW code over pre-emplacement topographies. Simulation outputs are compared with the boundaries of the actual flow fields obtained here or derived from the existing literature. Although the selected fields formed in accordance with different emplacement mechanisms, flowed on different zones of the volcano over different topographies and were fed by different lava supplies of different durations, DOWNFLOW yields results close to the actual flow fields in all the cases considered. This outcome is noteworthy because DOWNFLOW has been applied by adopting a default calibration, without any specific tuning for the new cases considered here. This extensive testing proves that, if the pre-emplacement topography is available, DOWNFLOW yields a realistic simulation of a future lava flow based solely on a knowledge of the vent position. In comparison with deterministic codes, which require accurate knowledge of a large number of input parameters, DOWNFLOW turns out to be simple, fast and undemanding, proving to be ideal for systematic hazard and risk analyses.
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