Maria Vittoria Avolio

Predicting the impact of lava flows at Mount Etna, Italy

This work was sponsored by the Italian Ministry for Education, University and Research, FIRB project n° RBAU01RMZ4 “Lava flow simulations by Cellular Automata”, and by the National Civil Defence Department and INGV (National Institute of Geophysics and Volcanology), project V3_6/09 “V3_6 – Etna”.

Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios

Abstract Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.

SCIARA γ2: An improved cellular automata model for lava flows and applications to the 2002 Etnean crisis

Abstract Cellular automata are widely utilized for modelling and simulating complex dynamical systems whose evolution depends on the local interactions of their constituent parts. Simulation by Cellular Interactive Automata of the Rheology of Aetnean lava flows (SCIARA) is a Cellular Automata model for simulating lava flows; its release γ 2 introduces innovations to the empirical method for modelling macroscopic phenomena that was utilized in the previous releases. The lava flows are described as “blocks”, individuated by their barycentre co-ordinates and velocities. This approach is different from the previous releases of SCIARA and from cellular automata derived models for fluid-dynamical phenomena such as lattice-gas and lattice-Boltzmann models. Block specifications permit to obtain a more physical description of the phenomenon and a more accurate control of its development. SCIARA γ 2 was applied to the 2002 Etnean lava flows with satisfying results, obtaining better simulations in comparison with the previous releases.

The latest release of the lava flows simulation model SCIARA: first application to Mt Etna (Italy) and solution of the anisotropic flow direction problem on an ideal surface

Abstract This paper presents the latest developments of the deterministic Macroscopic Cellular Automata model SCIARA for simulating lava flows. A Bingham-like rheology has been introduced for the first time as part of the Minimization Algorithm of the Differences, which is applied for computing lava outflows from the generic cell towards its neighbours. The hexagonal cellular space adopted in the previous releases of the model for mitigating the anisotropic flow direction problem has been replaced by a–Moore neighbourhood–square one, nevertheless by producing an even better solution for the anisotropic effect. Furthermore, many improvements have been introduced concerning the important modelling aspect of lava cooling. The model has been tested with encouraging results by considering both a real case of study, the 2006 lava flows at Mt Etna (Italy), and an ideal surface, namely a 5°inclined plane, in order to evaluate the magnitude of the anisotropic effect. As a matter of fact, notwithstanding a preliminary calibration, the model demonstrated to be more accurate than its predecessors, providing the best results ever obtained on the simulation of the considered real case of study. Eventually, experiments performed on the inclined plane have pointed out how this release of SCIARA does not present the typical anisotropic problem of deterministic Cellular Automata models for fluids on ideal surfaces.

Pyroclastic flows modelling using cellular automata

Cellular automata (CA) and derived computational paradigms represent an alternative approach to differential equations to model and simulating complex fluid dynamical systems, whose evolution depends on the local interactions of their constituent parts. A new notion of CA was developed according to an empirical method for modelling macroscopic phenomena; its application to PYR, a CA model for simulating pyroclastic flows, generated PYR2, which permitted an improvement of the model and a more efficient implementation. PYR2 was utilised for the 1991 eruption of Mt. Pinatubo in the Philippines islands and for the 1996 eruption of the Soufriere Hills in the Montserrat Island. Results of the simulations are satisfactory if the comparison between real and simulated event is performed, considering the area involved by the event and the variations of thickness of the deposit, as generated by collapsing volcanic columns.

SCIDDICA-SS3: a new version of cellular automata model for simulating fast moving landslides

Cellular Automata (CA) are discrete and parallel computational models useful for simulating dynamic systems that evolve on the basis on local interactions. Some natural events, such as some types of landslides, fall into this type of phenomena and lend themselves well to be simulated with this approach. This paper describes the latest version of the SCIDDICA CA family models, specifically developed to simulate debris-flows type landslides. The latest model of the family, named SCIDDICA-SS3, inherits all the features of its predecessor, SCIDDICA-SS2, with the addition of a particular strategy to manage momentum. The introduction of the latter permits a better approximation of inertial effects that characterize some rapid debris flows. First simulations attempts of real landslides with SCIDDICA-SS3 have produced quite satisfactory results, comparable with the previous model.

Modelling Combined Subaerial-Subaqueous Flow-Like Landslides by Cellular Automata

Macroscopic Cellular Automata characterize a methodological approach for modelling large scale (extended for kilometres) complex acentric phenomena, e.g. surface flows as lava flows, debris flows etc.. This paper concerns the extension of such a method in order to simulate combined subaerial-subaqueous flow-like landslides. The occurrence of heterogeneous interacting processes requires a more physical description of the energy balance and an explicit velocity management. The model SCIDDICA-SS2 proposes some empirical solutions, such as the computation at each step and inside each cell, of departing flows which are characterized by their mass centre position and velocity. An application to combined subaerial-subaqueous landslide is exhibited together with simulation results of the 1997 Albano lake (Rome, Italy) debris flow.

A Theorem about the Algorithm of Minimization of Differences for Multicomponent Cellular Automata

Multicomponent Cellular Automata, also known as Macroscopic Cellular Automata, characterize a methodological approach for modeling complex systems, that need many components both for the states (substates) to account for different properties of the cell and for the transition function (elementary processes) in order to account for various different dynamics. Many applications were developed for modeling complex natural phenomena, particularly macroscopic ones, e.g., large scale surface flows. Minimizing the differences of a certain quantity in the cell neighborhood, by distribution from the cell to the other neighboring cells, is a basic component of many transition functions in this context. The Algorithm for the Minimization of Differences (AMD) was applied in different ways to many models. A fundamental theorem about AMD is proved in this paper; it shows that AMD properties are more extended than the previous demonstrated theorem.

Lava invasion susceptibility hazard mapping through cellular automata

This work deals with a new methodology for the definition of volcanic susceptibly hazard maps through Cellular Automata and Genetic Algorithms Specifically, the paper describes the proposed approach and presents the first results to the South-Eastern flank of Mt Etna (Sicily, Italy) In particular, resulting hazard maps are characterized by a high degree of detail and allow for a punctual and accurate evaluation of the risk related to lava invasion.

Development and calibration of a preliminary cellular automata model for snow avalanches

Numerical modelling is a major challenge in the prevention of risks related to the occurrence of catastrophic phenomena. A Cellular Automata methodology was developed for modelling large scale (extended for kilometres) dangerous surface flows of different nature such as lava flows, pyroclastic flows, debris flows, rock avalanches, etc. This paper presents VALANCA, a first version of a Cellular Automata model, developed for the simulations of dense snow avalanches. VALANCA is largely based on SCIDDICA-SS2, the most advanced model of the SCIDDICA family developed for flow-like landslides. VALANCA adopts several of its innovations: outflows characterized by their mass centre position and explicit velocity. First simulations of real past snow avalanches occurred in Switzerland in 2006 show a satisfying agreement, concerning avalanche path, snow cover erosion depth and deposit thickness and areal distribution.