Using a genetic algorithm to estimate source term parameters of volcanic ash clouds
A method is presented that applies a genetic algorithm (GA) to observation data in order to back-calculate the source parameters governing the eruption. The GA is an optimization technique where trial source terms, in this case emission rates, are created and evolved through mating and mutation operators. The GA continually evolves the population of trial solutions until it converges on the most likely source term. Observed concentration data are derived from satellite data to determine the observed ash concentrations. A case study is made of the March 2009 eruption of Mt. Redoubt in Alaska.