Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/8506
Authors: Bilotta, G.* 
Cappello, A.* 
Herault, A.* 
Vicari, A.* 
Russo, G.* 
Del Negro, C.* 
Title: Sensitivity analysis of the MAGFLOW Cellular Automaton model
Journal: Environmental Modelling & Software 
Series/Report no.: /35 (2012)
Issue Date: Jul-2012
DOI: 10.1016/j.envsoft.2012.02.015
URL: http://www.sciencedirect.com/science/article/pii/S1364815212000631
Keywords: Sensitivity analysis; MAGFLOW model; Forecasting; Hazard; Lava flow simulation; Polynomial chaos; Sobol' indices; ANOVA
Subject Classification05. General::05.01. Computational geophysics::05.01.99. General or miscellaneous 
Abstract: MAGFLOW is a physics-based numerical model for lava flow simulations based on the Cellular Automaton approach that has been successfully used to predict the lava flow paths during the recent eruptions on Mt Etna. We carried out an extensive sensitivity analysis of the physical and rheological parameters that control the evolution function of the automaton and which are measured during eruptive events, in an effort to verify the reliability of the model and improve its applicability to scenario forecasting. The results obtained, which include Sobol' sensitivity indices computed using polynomial chaos expansion, confirm the consistency of MAGFLOW with the underlying physical model and identify water content and solidus temperature as critical parameters for the automaton. Additional tests also indicate that flux rates can have a strong influence on the emplacement of lava flows, and that to obtain more accurate simulations it is better to have continuous monitoring of the effusion rates, even if with moderate errors, rather than sparse accurate measurements.
Appears in Collections:Article published / in press

Files in This Item:
File Description SizeFormat Existing users please Login
Bilotta_EM&S_2012.pdf609.93 kBAdobe PDF
Show full item record

WEB OF SCIENCETM
Citations

33
checked on Feb 10, 2021

Page view(s)

243
checked on Apr 24, 2024

Download(s)

28
checked on Apr 24, 2024

Google ScholarTM

Check

Altmetric