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

Coastal erosion is a growing phenomenon that is increasingly causing difficulties both from environmental land management and social and economic point of views. 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 complex macroscopic fluid-dynamical phenomena, difficult to be modelled in other CA frames. Macroscopic CA can need a large amount of states that describe properties of the cells (e.g., altitude, depth of bottom sea, ..) called substates. The third dimension may be enclosed in substates for surface phenomena. In the past, the erosion problem by CA approach was described and modelled by: (D'AMBROSIO et alii, 2001) soil erosion by rain (SCAVATU model); (CHOPARD et alii, 2000) transport, deposit and erosion by sand and snow; (CHOPARD et alii, 2000; KUBO et alii, 2005) subaerial-subaqueous flow-like landslides (AVOLIO et alii, 2012). In this contribution, we aim 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 very preliminar CA model RUSICA (RUdimental SImulation of Coastal erosion by cellular Automata) is sketched and then experimental results are described (CALIDONNA et alii). Finally, some conclusions and perspectives of this work are outlined.