A novel model to predict a slap avalanche configuration using m:n-CAk cellular automata

Abstract

The paper introduces a novel method to represent slap avalanche phenomena. The model is based on a cellular automaton generalization named m:n-$CA^k$. This generalization allows the use of different layers in a single cellular automaton. Each one of these layers represents the GIS data needed to perform the calculations. The model is represented using Specification and Description Language, and is implemented in C++. The clear separation between the model representation and implementation simplifies the understanding of the behavior that rules the model. We determine experimentally two parameters that generate more accurate results in all the tested scenarios, namely the Penalization Coefficient ($K_p$) and the Inertial Coefficient ($K_i$). All the models have been validated using data from the Catalan Pyrenees.