Integration of an empirical cellular model for sand coastal erosion and an experimental contrast method

Coastal erosion is a growing phenomenon that is causing ever more difficulties both from an environmental land management but also from a social and economic point of view. Three processes are considered, over time scales consistent with natural hazard analysis: sea level rise, changes in storm climate, human interference. Such global causes are differently evaluated by scientific communities. Generally such phenomena are addressed by PDE, with classical approaches, only since recent times alternative approaches had been used such as Cellular Automata (CA) methodology. In dealing with macroscopic complex systems an extension of classical CA, i.e. macroscopic CA [DI GREGORIO S., SERRA R] were developed in order to model many complex macroscopic fluid-dynamical phenomena, that seem difficult to be modeled in other CA frames (e.g. the lattice Boltzmann method, as macroscopic CA can need a large amount of states that describe properties of the cells (e.g. temperature, of bottom sea, thickness of sand cover,...). called substates. In the past the erosion problem by CA approach was described and modeled by: [D'AMBROSIO D. ET AL.] soil erosion by rain (SCAVATU model); [CHOPARD B. et al.] transport, deposit and erosion by sand and snow; [CHOPARD B. ET AL., KUBO Y. ET AL.], subaerial-subaqueous flow-like landslides [AVOLIO M.V. ET AL.]. In this contribution we want to show, adopting CA, how it is possible to model and simulate dynamics of the coastal erosion complex phenomenon integrating empirical observation. After geomorphological considerations of the experimental site and a brief description of empirical observation and considerations, the CA RUSICA (RUdimental SImulation of Coastal erosion by cellular Automata) model is introduced and then experimental results are described. Finally some conclusions and perspectives of this work are outlined.