Applying genetic algorithms for calibrating a hexagonal cellular automata model for the simulation of debris flows characterised by strong inertial effects G. Iovine a,b, * , D. D’Ambrosio c , S. Di Gregorio c a CNR-IRPI, via Cavour, 6/8-87030 Rende (CS), Italy b Department of Earth Sciences and High-Performance Computing Center, University of Calabria, Arcavacata di Rende-87036 (CS), Italy c Department of Mathematics and High-Performance Computing Center, University of Calabria, Arcavacata di Rende-87036 (CS), Italy Received 15 January 2003; received in revised form 12 December 2003; accepted 15 September 2004 Available online 23 November 2004 Abstract In modelling complex a-centric phenomena which evolve through local interactions within a discrete time-space, cellular automata (CA) represent a valid alternative to standard solution methods based on differential equations. Flow-type phenomena (such as lava flows, pyroclastic flows, earth flows, and debris flows) can be viewed as a-centric dynamical systems, and they can therefore be properly investigated in CA terms. SCIDDICA S 4a is the last release of a two-dimensional hexagonal CA model for simulating debris flows characterised by strong inertial effects. S 4a has been obtained by progressively enriching an initial simplified model, originally derived for simulating very simple cases of slow-moving flow-type landslides. Using an empirical strategy, in S 4a , the inertial character of the flowing mass is translated into CA terms by means of local rules. In particular, in the transition function of the model, the distribution of landslide debris among the cells is obtained through a double cycle of computation. In the first phase, the inertial character of the landslide debris is taken into account by considering indicators of momentum. In the second phase, any remaining debris in the central cell is distributed among the adjacent cells, according to the principle of maximum possible equilibrium. The complexities of the model and of the phenomena to be simulated suggested the need for an automated technique of evaluation for the determination of the best set of global parameters. Accordingly, the model is calibrated using a genetic algorithm and by considering the May 1998 Curti–Sarno (Southern Italy) debris flow. The boundaries of the area affected by the debris flow are simulated well with the model. Errors computed by comparing the simulations with the mapped areal extent of the actual landslide are smaller than those previously obtained without genetic algorithms. As the experiments have been realised in a sequential computing environment, they could be improved by adopting a parallel environment, which allows the performance of a great number of tests in reasonable times. D 2004 Elsevier B.V. All rights reserved. Keywords: Debris flow; Inertial effects; Simulation; Cellular automata; Genetic algorithms 0169-555X/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.geomorph.2004.09.017 * Corresponding author. Tel.: +39 0984 835521; fax: +39 0984 835319. E-mail address: iovine@irpi.cnr.it (G. Iovine). Geomorphology 66 (2005) 287 – 303 www.elsevier.com/locate/geomorph