Valeria Lupiano

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”.

First simulations of the Sarno debris flows through Cellular Automata modelling

Abstract Cellular Automata (CA) can be efficiently applied in the simulation of complex natural processes. They represent an alternative approach to classical methods based on the resolution of differential equations. In this paper, the general frame and the latest developments of the Cellular Automata model SCIDDICA (Simulation through Computational Innovative methods for the Detection of Debris flow path using Interactive Cellular Automata) for simulating debris-flow phenomena are presented. Landslides characterised by a dominant flow-type (e.g. earth flows, debris flows, debris avalanches) can be considered as dynamical systems, subdivided into elementary parts that evolve, exclusively, as a consequence of local interactions. In SCIDDICA, space and time are discrete: in particular, the space in which the phenomenon evolves is represented by square cells, whose states describe the considered physical characteristics; time is implicit in the steps of model computation. The peculiarities of the structure permitted to extend SCIDDICA first release, in order to progressively account for more complex phenomenological aspects of the considered landslides. In this paper, examples of application of SCIDDICA to three real landslide events are presented. After briefly describing earlier simulations of the 1992 Tessina (Italy) earth flow and of the 1984 Mt. Ontake (Japan) debris avalanche, first attempts at modelling a debris flow that occurred in 1998 at Sarno (Italy) are discussed. The model has been validated through the reconstruction of the initial topographic and geomorphological conditions of a selected, typical phenomenon (which occurred at Chiappe di Sarno–Curti, on May 1998), and by successively comparing the simulation results with the actually observed debris-flow path. Even though improvements to the algorithms are still needed, and further testing of parameters on a more representative sample of phenomena desirable, first simulations of the Curti landslide have demonstrated the reliability of SCIDDICA in the assessment of debris-flow susceptibility.

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.

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.

Simulating the Curti–Sarno debris flow through cellular automata: the model SCIDDICA (release S2)

Cellular automata (CA) are based on a regular division of the space in cells. Each cell embeds an identical finite automaton, whose input is given by the states of neighbouring cells. The transition function r of the CA is made of a set of rules, simultaneously applied, step by step, to each cell of the cellular space. Rules are derived by subdividing, in computational terms, the physical phenomenon into a set of independent, elementary processes. By properly combining each elementary result, the behaviour of the phenomenon can be simulated. Debris flows are dense mixtures of sediment and water, which surge down the slopes and along the drainage system, characterised by severe destructive potential. They can be described in terms of local interactions among their elementary portions, and can thus be efficiently modelled through CA. Debris-flows rheologic equations cannot be easily solved without making substantial simplifications. By applying CA, a phenomenological description––able to overcome resource computational limits––can be obtained. On May 1998, hundreds of soil slip-debris flows were triggered by exceptional rains in Campania (Italy), mostly on the slopes of Pizzo dAlvano. Aiming at modelling purposes, the Curti debris flow was selected as a case study, among the whole population of landslides triggered by the event. The general frame of SCIDDICAS2 is inherited from previous releases, recently applied for the simulation of the 1992 Tessina (Italy) earth flow and of the 1984 Mt. Ontake (Japan) debris avalanche. Since its S1 release, the model satisfactorily simulated the Curti–Sarno debris flow. Latest improvements to the transition function led to the S2 release, and to better simulations (presented here). SCIDDICA exhibits a notable flexibility in modelling and simulating flow-like landslides. It could be usefully applied in hazard mapping (also through a statistical approach), and in evaluating the effects of either human works or ‘‘accidents’’ along the path of the flow. � 2002 Elsevier Science Ltd. All rights reserved.

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.

Simulation of Wildfire Spread Using Cellular Automata with Randomized Local Sources

The accuracy of Cellular Automata (CA) methods for simulating wildfires is limited by the fact that spread directions are constrained to the few angles imposed by the regular lattice of cells. To mitigate such problem, this paper proposes a new CA in which a local randomization of the spread directions is explicitly introduced over the lattice. The suggested technique, inspired by a method already used for simulating lava flows, is empirically investigated under homogeneous conditions and by comparison with the vector-based simulator FARSITE. According to the presented results, the adopted randomization seems to be able to significantly improve the accuracy of CA based on a standard center-to-center ignition scheme.

A cellular model for secondary lahars and simulation of cases in the Vascún Valley, Ecuador

Abstract Cellular Automata (CA) represent a computational paradigm for simulating complex fluid-dynamical phenomena, that evolve on the basis of local interactions. Secondary lahars are highly destructive surface flows that originate from the mobilization of pyroclastic deposits by exceptionally heavy rainfalls. CA modelling of rain-induced lahars could be an important tool for risk management in threatened regions. LLUNPIY is a CA model, developed and partially applied on two real events: the 2005 and 2008 secondary lahars of Vascun Valley, Ecuador. Simulations are satisfying: a comparison of 2005 event was performed with the two-dimensional model Titan2D and field data, while results of 2008 event were confronted only with field data.