Defence Research and Development Canada External Literature (N) DRDC-RDDC-2020-N162 October 2020

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Modelling of Seafloor Reverberation in Northern Gulf of Mexico Sandy Sediment

Shannon Steele Sean Pecknold DRDC – Atlantic Research Centre Acoustics Week in Canada 2015 Halifax, Nova Scotia Canada 6–9 October 2015 2 Pages Date of Publication from Ext Publisher: October 2015

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MODELLING OF SEAFLOOR REVERBERATION IN NORTHERN GULF OF MEXICOSANDY SEDIMENT

Shannon Steele ∗1 and Sean Pecknold †21Dalhousie University and Defence Research Development Canada-Atlantic

2Defence Research Development Canada-Atlanticc

1 IntroductionUnderwater acoustics is an important tool for detecting andclassifying targets such as submarines, mines, and fauna.Backscatter from the seafloor degrades the acoustic signalreceived from targets and thus modelling seafloor backscat-ter is an important component of active sonar. In this paperseabed roughness and cone pentrometer data taken duringthe TREX2013 sea trial will be used to produce a model ofbackscatter from sediment. The TREX sea trial was conduc-ted in the Northern Gulf of Mexico, just off the coast of Pa-nama City, Florida. The data was collected along two dif-ferent tracks known as the main track(Figure 1) and the clut-ter track, which runs approximately perpendicular to the tothe main track. The study area is composed of fine to mediumgrained quartz sand with a low carbonate content and patchesof fine-grained sediment(mud and silt) [1,2]. The bathymetryof the TREX study area is characterized by large-scale north-south-trending sand ripples with amplitudes ranging from 1–3 m and wavelengths between 0.1 to 0.5 km [1, 3]. At highresolutions the acoustic scattering is considered nearly iso-tropic, however, on a broad scale it appears to show both gra-dual and abrupt changes in backscatter strength [4]. At highfrequencies backscatter in the study area is mainly controlledby roughness spectra, however, at low and medium frequen-cies it is expected that volume scattering will also play a rolein sediment backscatter. The most prominent volume scatte-rers in the study area are likely to be shell hash, hard packedsand, and other carbonate scatterers [5].

2 Methods2.1 Roughness SpectraThe one dimensional roughness spectra for the multiple dif-ferent sources of bathymetry collected during TREX werecalculated in both the along track and across track directions.For each line a peridogram was calculated and then in eachdirection the peridograms were averaged. To test for isotropya 2D FFT was also calculated.Two important parameters forinputs into backscattering models are spectral strength(ω2)and spectral slope(−γ2).This can be modelled by the powerlaw, which can be expressed as W (~k) = ω2k

−γ2 [6]. Since,in this study, the roughness was found to be roughly isotro-pic the spectral strength and slope can be determined fromthe 1D spectra, which is modelled as a power law of spec-tral strength (ω1) and slope(−γ1). It was assumed that themeasured roughness scaling continued to scales that affect thescattering.

Figure 1: Image of main track bathymetry at 1m resolution

2.2 Scattering ModelThe two-dimensional roughness spectra and geoacoustic pa-rameters measured by the cone pentrometer were used tomodel acoustic backscatter as a function of Grazing Angle.Methods described in [7] were used to empirically estimatesound speed ratio(υ), density ratio(ρ), loss parameter(δ), andvolume scattering parameter(σ2) based on the grain sizes de-termined by the cone penetrometer. A composite roughnessapproximation (CRA) model [6,7] was used to determine thebackscattering strength. In the CRA backscattering strengthis defined as the product of roughness scattering and volumescattering.

3 Results3.1 Roughness SpectraFor all sources of bathymetry the 2D FFTs show roughlyisotropic spectral characteristics at the scale of 75m or less,and thus in terms of high to mid frequency acoustics the se-diment can be considered isotropic. Shown in Figure 2 isthe average one dimensional spectra across the north/southlines, east/west lines, and across all lines. The power law fitobtained from the 1D spectra is ω1 = 5.716−8m3−γ1 andγ1 = 1.454. The 2D spectral parameters were calculated tobe ω2 = 4.464−7m4−γ2 and γ2 = 2.454.

3.2 Backscatter ModelThe following geoacoustic parameters were obtained fromthe cone penetrometer data, and used as inputs into the scat-tering model : υ=1.23, ρ=1.46, σ2=0.002, and δ=0.016. TheCRA backscatter model has been plotted as a function of gra-zing angle along with Lambert’s Law and a Lambert’s Law

fit for sandy sediment (µ=-20.2) for comparison. Between30◦ and 90◦ the model appears to be most predominantlycontrolled by volume scattering. At grazing angles below ap-proximately 18◦ roughness scattering is the dominant controlon scattering strength. In between 18◦ and 30◦ both typesof scattering appear to contribute equally to the scatteringstrength. Near the critical angle (35.7◦) the CRA demons-trates a steep slope, causing the backscattering strength to bemuch lower than what is predicted by Lambert’s Law. Below15◦ the CRA plot has a much smaller slope than predicted byLambert’s Law. The CRA predicts significantly lower backs-catter than the sandy sediment value fit with µ=-20.2 measu-red previously at other sites.

Figure 2: Average spectra and Power-Law fitted spectrum to ave-rage Spectra from both directions

4 DiscussionIn the CRA the volume scattering coefficient is determined ei-ther empirically based on measured backscattering data or byestimation based on mean grain size. In this study, the volumeparameter was determined based on mean grain size, howeverin many cases sediment grain size is not an accurate predictorof volume scattering [6, 7].In addition to this, the model alsofails to consider volume scattering due to heterogeneity withdepth as well as the presence of discrete scatterers [7]. The-refore it is possible that the CRA model predicts significantlylower backscattering strength than expected because volumescattering is not being fully accounted for.

5 ConclusionsThe CRA model predicts that the sediment in the study areais not an ideal diffusely reflecting surface. Below the criticalangle the CRA model predicts grazing angle dependency thatis far different than what would be predicted by Lambert’sLaw. The significant difference in scattering strength predic-ted by the CRA model and the Lambert’s law fit to sandysediment indicates that predicting volume scattering with se-diment grain size may not always be an effective way to mo-

Figure 3: Plot comparing scattering strength as function of grazingangle for : the CRA model of TREX study area, Lambert’s Law(µ=-27) and Lambert’s Law fit for sandy sediment(µ=-20.2). Also shownis the seabed roughness scattering strength computed for the CRAand the volume scattering strength computed for the CRA

del backscattering. Thus more research needs to be conductedto test and further develop models that account for volumeheterogeneity (both at and below the sediment water inter-face) and discreet scatterers. In future work sub-bottom pro-filer data collected during TREX2013 will be used in order toquantify volume scattering.

References[1] Peter. Fleischer, William B. Sawyer, Hannelore Fiedler, and

Ingo H. Stender. Spatial and temporal variability of a coarse-sand anomaly on a sandy inner shelf, northeastern gulf ofmexico. Geo-Marine Letters, 16(3) :266–272, 1996.

[2] Larry J. Doyle and Thomas N. Sparks. Sediments of the Missis-sippi, Alabama, and Florida (MAFLA) continental shelf. Jour-nal of Sedimentary Petrology, 50(3) :905–915, 1980.

[3] Steven J. Parker, Albert W. Shultz, and William W. Schroeder.Sediment Characteristics and Seafloor Topography of a Palimp-sest Shelf, Mississippi-Alabama Continental Shelf. SEPM, 48,1992.

[4] Kenneth S. Davis, Niall C. Slowey, Ingo H. Stender, Hanne-lore Fiedler, William R. Bryant, and Gunther Fechner. Acous-tic backscatter and sediment textural properties of inner shelfsands, northeastern gulf of mexico. Geo-Marine Letters,16(3) :273–278, 1996.

[5] John A. Goff. Reconnaissance marine geophysical survey forthe shallow water acoustics program. 2013.

[6] D. Jackson and M. Richardson. High-Frequency SeafloorAcoustics. The Underwater Acoustics Series. Springer NewYork, 2007.

[7] APL-UW High-Frequency Ocean Environmental Acoustic Mo-dels Handbook,. Technical report, Dod, Defense Technical In-formation Center, 1995.

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Modelling of Seafloor Reverberation in Northern Gulf of Mexico Sandy Sediment

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Steele, S.; Pecknold, S.

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