Hot mudflow prediction area model and simulation based on Cellular Automata for LUSI mud plume at Sidoarjo in East Java

Abstract

We propose a new hot mudflow prediction model based on Cellular Automata (CA). Using our CA prediction model, we present simulations of the LUSI hot mudflow in the Sidoarjo disaster area. Our CA method to predict mudflow is based on a fluid dynamic model, because hot mudflow characteristics are similar to fluid. The CA model also takes into consideration landscape data, including features such as dikes and buildings. The Moore neighborhood model is adopted for CA to take into account the relationship between the cell of interest and the surrounding cells. A Gaussian interpolation is used to approximate the behavior of the hot mudflow over landscape features. We evaluated the prediction accuracy of our CA model, by comparing results from the CA model with remote sensing satellite data from the disaster areas and measurements of the mudflow disaster area. Simulation results of the LUSI hot mudflow show relatively good prediction accuracy in comparison with conventional models. Therefore, we conclude that the CA model will be valuable for predictions pertaining to hot mudflow in future disasters of a similar nature.