Using Multibeam Backscatter Data to Investigate Sediment-Acoustic Relationships

Sediment properties are known to influence acoustic backscatter intensity. This sediment-acoustic relationship has been investigated previously through using physical geoacoustic models and empirical methods and found to be complex and non-linear. Here we employ a robust machine-learning statistical model (random forest decision tree) to investigate the most likely non-linear sediment-backscatter relationships. The analysis uses co-located sediment and acoustic backscatter data for 564 locations in four different areas on the Australian margin. Seven sediment grain size properties (%gravel, %sand, %mud, mean grain size, sorting, skewness and kurtosis) were used to predict the acoustic backscatter responses at individual incidence angles. The sample size and consistency of sediment textural analysis ensure the adequacy of the statistical power for the modelling and is the fundamental strength of this study. The modelling results demonstrate the effectiveness of the cause-to-effect approach for the investigation of sediment-acoustic interactions. Thus, we find that for incidence angles between 1o and 41o, the sediment variables explain around 70% of variance in the backscatter intensity. Sediment mud content was found to be the most important sediment variable in the model, and has a significant negative relationship with backscatter intensity. Mean grain size was the second ranked sediment variable and found to have a positive relationship with backscatter intensity. The results also show that sediment mud content plays a key role in sorting-backscatter and sand-backscatter relationships. The combined influence of sediment mud content and mean grain size was able to largely explain the sediment-acoustic interaction. The strongest backscatter return occurred with medium sediment mud content and large mean grain sizes (or muddy coarse sand). However, the sediment-acoustic interaction beyond the critical angle could not been reliably resolved in this study. Overall, these results further demonstrate the utility of acoustic backscatter in seabed habitat mapping and provide important insights into those sediment parameters that warrant further investigation. Citation: Huang, Z., Siwabessy, J., Cheng, H., & Nichol, S. (2018). Using multibeam backscatter data to investigate sediment-acoustic relationships. Journal of Geophysical Research: Oceans, 123, 4649–4665. https://doi.org/10.1029/2017JC013638