Application of the Acoustic Integration Model (AIM) to predict and minimize environmental impacts

Abstract

Minimizing and mitigating the potential effect of sound upon the environment is an increasing concern for many activities. Naval operations, seismic exploration, vessel and aircraft operations, and scientific investigations now need to consider the potential effect of underwater acoustic sources. Marine mammals are usually the primary concern, due to their widespread distribution and excellent hearing. Predicting the exposure of marine mammals is complicated by their diving behavior, which causes them to 'sample' many depth strata within the water column. Acoustic propagation and sound received levels are a function of depth as well as range. The Acoustic Integration Model (AIM) addresses this specific complication. A principal component of the central engine of AIM is a movement simulator. Both sound sources and animals, collectively addressed as 'ANIMATS', are programmed to move in location and depth over time in a realistic function. Animal movement is based on documented regional and seasonal behavioral data for each species generated. Acoustic sources and receivers are programmed to move through a virtual acoustic environment based on external environmental databases and radiated sound fields created from a choice of several propagation models. The integration component of the AIM engine then predicts the exposure level of each simulated animal at successive operator-selected time steps. Furthermore, each animat can evaluate its environment at each time step, and can be programmed to alter direction or diving behavior in response to any variable, such as sound level or sea depth. The model therefore allows the user to predict the effects of different operational scenarios and animal response levels, thereby allowing the selection of the alternative that produces the least impact and still meets operation requirements.