Estimating Sampling Areas for Passive Acoustic Recorders

Tetyana Margolina, Naval Postgraduate School, Department of Oceanography, Monterey, CA, United States, John Joseph, Naval Postgraduate School, Oceanography, Monterey, United States, Simone Baumann-Pickering, University of California San Diego, Scripps Institution of Oceanography, La Jolla, United States, Brandon Southall, Southall Environmental Associates, Inc., CA, United States and Leila Hatch, NOAA Office of National Marine Sanctuaries, Scituate, United States
Passive acoustic monitoring is a unique approach that can provide continuous, long-term measurements of biotic and abiotic sources and quantify underwater soundscapes. However, the interpretation of passive acoustic data and detector output can be ambiguous because of uncertainty in sampling parameters. A primary source of this uncertainty is the highly variable sampling area, which depends on the sound source characteristics, environmental parameters, and background noise. We apply advanced acoustic propagation modeling and noise estimates to reduce the uncertainty and visualize sampling area variability. Sound propagation at various frequencies is estimated using a parabolic equation (PE) acoustic propagation model and available environmental databases. Range-dependent ocean sound speed structure is calculated using daily outputs of temperature and salinity from the HYCOM model. We specifically focus on frequencies below 1 kHz primarily dominated by wind-induced noise. To estimate frequency-specific signal-to-noise ratio (SNR) thresholds, wind-induced noise is estimated using surface wind stress from the Regional Navy Coastal Ocean Model (RNCOM) and wind speed measured by NOAA moored buoys. We apply this approach to passive acoustic datasets collected within the Navy/NOAA Sanctuary Soundscape Monitoring Project (SanctSound) and other previously recorded PAM datasets. Passive acoustic data collected between December 2012 and March 2015 at Thirtymile Bank, 25 nm west of Point Loma CA, serve as a benchmark for the developed approach. These data are used to evaluate the modeled wind-induced noise and introduce the correction for low wind speed conditions when shipping-induced noise dominates the noise field. The resulting sampling area is defined as the area within which the received level is expected to exceed the estimated SNR threshold. We present time series of frequency and location specific sampling areas to assist with interpretation of passive acoustic data collected among diverse marine environments.