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 Classification: | 05. 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 | Size | Format | Existing users please Login |
---|---|---|---|---|
Bilotta_EM&S_2012.pdf | 609.93 kB | Adobe PDF |
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