Anthropogenic noise in the sea is now classed as a pollutant alongside chemical pollution and marine litter in accordance with the Marine Strategy Framework Directive. Noise from shipping is a major contributor to the ambient noise levels in the ocean, particularly at low (<300Hz) frequencies. The properties of sound propagation in shallow waters are highly influenced by the marine physical environment. Ocean modelling plays an important role in underwater noise studies since it can provide high resolution water column parameters over large geographic areas. This study investigates the noise patterns and their temporal variations in the Celtic Sea by using a coupled ocean model (POLCOMS) and an acoustic model (HARCAM). A method to predict noise exposure experienced by marine animals is then developed, following an application for diving seals. The ocean model is applied in the Celtic Sea to provide high-resolution 3D hourly temperature and salinity fields for the acoustic model. The model is validated against in-situ and satellite observations, giving high skills to simulate the water column structures. Sensitivity studies of modelled results to different atmospheric forcing are carried out in order to improve the accuracy of the model. The results show that the modelled sea surface temperature, stratification and water column structures are highly sensitive to the choice of surface forcing, especially in the summer time. The increase in resolution of surface forcing does not necessarily lead to more accurate results. The tidally frontal position is, however, insensitive to the forcing. The variability of noise propagation is studied using the coupled model, demonstrating high dependence on oceanographic conditions, geographic location of sound source and its depth. In summer, when the source of sound is on the inshore side of the bottom front, the sound energy is mostly concentrated in the near-bottom layer. In winter, the sound from the same source is distributed more evenly in the vertical. When the source is on the seaward side of the front, the sound level from a shallow source is nearly uniform in the vertical and the transmission loss is significantly greater (~16dB at 40km distance) in summer than in winter. In contrast, sound energy from a deep source is trapped in the bottom cold water, leading to a much lower transmission loss (~20dB) in summer than in winter. Note that ~10dB fluctuation of sound energy is found during the deterioration of the thermocline in late autumn. Shallow sources (e.g. ships) are sensitive to the surface heat flux as it changes significantly the vertical temperature gradient, while tides play an important role in determining the TL variability of deeper sources (e.g. pile driving) since they cause adjustments of positions of subsurface fronts. The seasonal noise patterns radiated by a large cargo ship are modelled by relating the AIS ship track data and the coupled model, showing a clear influence of the seasonal thermocline and associated bottom fronts on shipping noise distribution. The noise propagates much further (tens of kilometres) in winter than in summer. The predicted shipping noise exposure perceived by grey seals shows strong step changes in the sound level during their descent/ascent through the water column. Since grey seals tend to be benthic foragers, a hypothesis that the step change in sound exposure may have negative impacts on their foraging behaviour is proposed for biological specialists.

Given a known signal and perfect knowledge of the environment there exist few detection and estimation problems that cannot be solved. Detection performance is limited by uncertainty in the signal, an imperfect model, uncertainty in environmental parameters, or noise. Complex environments such as the ocean acoustic waveguide and the human anatomy are difficult to model exactly as they can differ, change with time, or are difficult to measure. We address the uncertainty in the model or parameters by incorporating their possibilities in our detection algorithm. Noise in the signal is not so easily dismissed and we set out to provide cases in which what is frequently termed a nuisance parameter might increase detection performance. If the signal and the noise component originate from the same system then it might be reasonable to assume that the noise contains information about the system as well. Because of the negative effects of ionizing radiation it is of interest to maximize the amount of diagnostic information obtained from a single exposure. Scattered radiation is typically considered image degrading noise. However it is also dependent on the structure of the medium and can be estimated using stochastic simulation. We describe a novel Bayesian approach to signal detection that increases performance by including some of the characteristics of the scattered signal. This dissertation examines medical imaging problems specific to mammography. In order to model environmental uncertainty we have written software to produce realistic voxel phantoms of the breast. The software includes a novel algorithm for producing three dimensional distributions of fat and glandular tissue as well as a stochastic ductal branching model. The image produced by a radiographic system cannot be determined analytically since the interactions of particles are a random process. We have developed a particle transport software package to model a complete radiographic system including a realistic x-ray spectrum model, an arbitrary voxel-based medium, and an accurate material library. Novel features include an efficient voxel ray tracing algorithm that reflects the true statistics of the system as well as the ability to produce separable images of scattered and direct radiation. Similarly, the ocean environment includes a high degree of uncertainty. A pressure wave propagating through a channel produces a measurable collection of multipath arrivals. By modeling changes in the pressure wave front we can estimate the expected pattern that appears at a given location. For this purpose we have created an ocean acoustic ray tracing code that produces time-domain multipath arrival patterns for arbitrary 3-dimensional environments. This iterative algorithm is based on a generalized recursive ray acoustics algorithm. To produce a significant gain in computation speed we model the ocean channel as a linear, time invariant system. It differs from other ocean propagation codes in that it uses time as the dependent variable and can compute sound pressure levels along a ray path effectively measuring the spatial impulse response of the ocean medium. This dissertation also investigates Bayesian approaches to source localization in a 3-D uncertain ocean environment. A time-domain-based optimal a posteriori probability bistatic source localization method is presented. This algorithm uses a collection of acoustic time arrival patterns that have been propagated through a 3-D acoustic model as the observable data. These replica patterns are collected for a possible range of unknown environmental parameters. Receiver operating characteristics for a bistatic detection problem are presented using both simulated and measured data. / Dissertation

Interface roughness can have a significant effect on the scattering of sound energy, and therefore an understanding of the effects of roughness is essential to making predictions of sound propagation and transmission underwater. Many models of roughness scattering currently in use are two dimensional (2D) in nature; three dimensional (3D) modeling requires significantly more time and computational resources. In this work, an effort is made to quantify the effects of 3D scattering in order to assess whether or under what conditions 3D modeling is necessary. To that end, an exact 3D roughness scattering model is developed based on a commercially available finite element package. The finite element results are compared with two approximate scattering models (the Kirchhoff approximation and first order perturbation theory) to establish the validity and regimes of applicability of each. The rough surfaces are realizations generated from power spectra measured from the sea floor. However, the surfaces are assumed to be pressure release (as on an air-water interface). Such a formulation is nonphysical, but allows the assessment of the validity of the various modeling techniques which is the focus of this work. The comparison between the models is made by calculating the ensemble average of the scattering from realizations of randomly rough surfaces. It is shown that a combination of the Kirchhoff approximation and perturbation theory models recovers the 3D finite element solution. / text

Single-beam echosounders are an inexpensive, practical and non-invasive means of remote sensing the seabed. Ideally, the common single-beam echosounder should be able to tell fishers, navigators, engineers and scientists what the seabed consists of in addition to water depth. Low-frequency underwater acoustic systems (<10 kHz) can do this in some circumstances, but are expensive, offer limited resolution and potentially hazardous to marine mammals. High-frequency systems, such as single and multibeam echosounders, are very effective at mapping bathymetry, but do not characterize the seabed directly. Instead, these systems divide the seabed into self-similar segments or classes, and then rely on ground-truth data (usually sediment grab samples) to assign seabed-type labels such as sand, etc., to the classes. However, inadequate and inaccurate ground-truth is a major problem. Single-beam seabed classification methods also suffer from a lack of discriminatory power and from artefacts such as water depth and seabed slope. The cause of these problems is that the methods lack a basis in physics and are mainly statistical. Then, the central objective in this dissertation is to develop physics-based methods to improve classification and to address the problem of ground-truth by inferring seabed characteristics directly from the acoustics. An overview of current methods is presented along with case studies of single-beam surveys to introduce the current seabed classification method called QTC VIEW™ and to identify specific problems. A physical basis is established in scattering and geometrical theories and observations of field and model data. This leads to new classification and characterization methods that overcome the shortcomings of current seabed classification methods. Advancements also include new physical models of echosounding. The new methods are presented, implemented and evaluated. Highlights of experimental results include a new testbed located in Patricia Bay, British Columbia. The testbed consists of exhaustive ground-truth, surveys and novel controlled experiments with various single-beam echosounders, ranging in frequency from 12 to 200 kHz. Simulated echo time series data from the numerical BORIS model and a new analytic model are used to augment the testbed. Evaluation of experimental results shows the new physics-based methodology improves seabed classification significantly and enables seabed characterization by an uncalibrated single-beam echosounder. / Graduate

The overall goal of this thesis is to develop non-linear Bayesian methods for three-dimensional tracking of a moving acoustic source in shallow water despite environmental uncertainty, with application to data from a horizontal line array (HLA) of hydrophones. As a precursor, Bayesian geoacoustic inversion is applied to estimate seabed model parameters and their uncertainties. A simulation study examines the effect of source and array factors on geoacoustic information content in matched-field inversion of HLA data, as quantified in terms of model parameter uncertainties. Bayesian geoacoustic inversion is applied to both controlled-source and ship-noise data from a HLA deployed on the seafloor in a shallow-water experiment conducted in the Barents Sea. A new approach is introduced to account for data error reduction due to averaging data over time-series subsegments (snapshots), based on empirically apportioning measurement and theory error, with effects on inversion results compared to those of existing approaches. It is further demonstrated that combining data from multiple, independent time-series segments (for a moving source) in the inversion can significantly reduce geoacoustic parameter uncertainties. Geoacoustic uncertainties are also shown to depend on ship range and orientation, with lowest uncertainties for short ranges and for the ship stern/propeller oriented toward the array. Sediment sound-speed profile and density estimates from controlled-source and ship-noise data inversions are found to be in good agreement with values from geophysical measurements. Two non-linear Bayesian matched-field inversion approaches are developed for three-dimensional source tracking despite environmental uncertainty. Focalization-tracking maximizes the posterior probability density (PPD) over track and environmental parameters. Synthetic test cases show that the algorithm substantially outperforms tracking with poor environmental estimates and generally obtains results close to those achieved with exact environmental knowledge. Marginalization-tracking integrates the PPD over environmental parameters to obtain joint marginal distributions over source coordinates, from which track uncertainty estimates and the most probable track are extracted. Both approaches are applied to data from the Barents Sea experiment. Focalization-tracking successfully estimates the tracks of the towed source and a surface ship in cases where simpler tracking algorithms fail. Marginalization-tracking generally outperforms focalization-tracking and gives uncertainty estimates that encompass the true tracks.

Multi-frequency backscatter acoustic profilers (echosounders) are used to measure biological and physical phenomena in the ocean in ways that are not possible with optical methods. Echosounders are commonly used on ocean observatories and by commercial fisheries but require significant manual effort to classify species of interest within the collected echograms. The work presented in this thesis tackles the challenging task of automating the identification of fish and other phenomena in echosounder data, with specific application to aggregations of juvenile salmon, schools of herring, and bubbles of air that have been mixed into the water. U-Net convolutional neural networks (CNNs) are used to accomplish this task by identifying classes at the pixel level. The data considered here were collected in Okisollo Channel on the coast of British Columbia, Canada, using an Acoustic Zooplankton and Fish Profiler at four frequencies (67.5, 125, 200, and 455 kHz). The entrainment of air bubbles and the behaviour of fish are both governed by the surrounding physical environment. To improve the classification, simulated channels for water depth and solar elevation angle (a proxy for sunlight) are used to encode the CNNs with information related to the environment providing spatial and temporal context. The manual annotation of echograms at the pixel level is a challenging process, and a custom application was developed to aid in this process. A relatively small set of annotations were created and are used to train the CNNs. During training, the echogram data are divided into randomly-spaced square tiles to encode the models with robust features, and into overlapping tiles for added redundancy during classification. This is done without removing noise in the data, thus ensuring broad applicability. This approach is proven highly successful, as evidenced by the best-performing U-Net model producing F1 scores of 93.0%, 87.3% and 86.5% for herring, salmon, and bubble classes, respectively. These models also achieve promising results when applied to echogram data with coarser resolution. One goal in fisheries acoustics is to detect distinct schools of fish. Following the initial pixel level classification, the results from the best performing U-Net model are fed through a heuristic module, inspired by traditional fisheries methods, that links connected components of identified fish (school candidates) into distinct school objects. The results are compared to the outputs from a recent study that relied on a Mask R-CNN architecture to apply instance segmentation for classifying fish schools. It is demonstrated that the U-Net/heuristic hybrid technique improves on the Mask R-CNN approach by a small amount for the classification of herring schools, and by a large amount for aggregations of juvenile salmon (improvement in mean average precision from 24.7% to 56.1%). / Graduate

In this thesis, acoustic inversion methods are employed to estimate array element locations and the geoacoustic properties of the seabed using measured acoustic data consisting of noise from a surface ship in the Gulf of Mexico. The array element localization utilizes relative travel-time information obtained by cross-correlating the recorded time series of ship noise received at spatially separated hydrophones. The relative travel-time data are used in an inversion, based on the regularized least-squares method and the acoustic ray tracing equations, to obtain improved estimates of the receiver and source positions and their uncertainties. Optimization and Bayesian matched-field inversion methods are employed to estimate seabed geoacoustic properties and their uncertainties in the vicinity of a bottom-moored vertical line array using the recorded surface ship noise. This study is used to test the feasibility of matched-field methods to detect temporal changes in the geoacoustic properties of the seabed near a known gas hydrate mound in the Gulf of Mexico. Finally, a synthetic study is performed that demonstrates how ignoring environmental range dependence of seabed sound speed and water depth in matched-field inversion can lead to biases in the estimated geoacoustic parameters. The study considers the distributions of optimal parameter estimates obtained from a large number of range-independent inversions of synthetic data generated for random range-dependent environments. Range-independent Bayesian inversions are also performed on selected data sets and the marginal parameter distributions are examined. Both hard- and soft-bottom environments are examined at a number of scales of variability in sound speed and water depth.

Cette thèse mêle observations, simulations et développement d'outils numériques haute performance dans le domaine de l’acoustique sous-marine, et notamment pour l’étude des ondes T. Après une revue de la littérature sur les ondes T, nous avons analysé des données réelles enregistrées en Italie. Afin de modéliser le phénomène nous avons développé un solveur éléments spectraux axisymétriques dans le domaine temporel, que nous présentons et validons. Nous présentons également une étude paramétrique de l'influence de la pente du plancher océanique dans un scénario typique de génération/conversion d'une onde T. L'énergie et la durée de ces ondes s’avère être particulièrement sensible à l'environnement. En particulier nous avons vu que les pentes et les caractéristiques du fond marin jouaient un rôle capital. Nos études confirment qu’aux distances régionales le profil de vitesse dans l'océan s'avère n'être qu'un paramètre de deuxième ordre. Pour en évaluer l’impact nous avons développé une procédure pour le calcul de cartes de perte de transmission et de dispersion à partir de simulations numériques en forme d'onde complète dans le domaine temporel. Dans un second temps nous montrons qu'un bateau commercial de taille moyenne peut créer par diffraction des ondes T d'une d'amplitude conséquente et de faible dispersion. Ce mode de génération d'onde T, encore non documenté, doit être particulièrement fréquent dans les zones où le trafic maritime est important et pourrait expliquer certaines ondes T abyssales encore incomprises. Pour finir, nous présentons des outils numériques pour calculer le champ acoustique créé par une source en mouvement / This thesis combines observations, simulations and development of high performance numerical tools in the field of underwater acoustics, and in particular for the study of T-waves. After a literature review on T-waves, we analysed real data recorded in Italy. In order to model the phenomenon we have developed an axisymmetric spectral element solver in the time domain, which we present and validate. We also present a parametric study of the influence of seafloor slope in a typical scenario of generation / conversion of a T-wave. The energy and duration of these waves is particularly sensitive to the environment. In particular, we have seen that the slopes and characteristics of the seabed are of crucial importance. Our studies confirm that at regional distances the ocean speed profile is only a second order parameter. To evaluate its impact we have developed a procedure for the calculation of transmission and dispersion loss maps from full waveform numerical simulations in the time domain. In a second step we show that a medium-sized commercial boat can create T-waves of a significant amplitude and of low dispersion by diffraction. This T-wave generation mode, still undocumented, must be particularly frequent in areas where maritime traffic is dense and could explain some abyssal T-waves still misunderstood. Finally, we present numerical tools for calculating the acoustic field created by a moving source

In this report, we study how finite differences can be used to simulate acoustic wave propagation originating from a point source in the ocean using the Helmholtz equation. How to model sediment layers and the vast size of the ocean is studied in particular. The finite differences are implemented with summation by parts operators with boundary conditions enforced with simultaneous approximation terms and projection. The numerical solver is combined with the WaveHoltz method to improve the performance. Sediment layers are handled with interface conditions and the domain is artificially expanded using absorbing layers. The absorbing layer is implemented with an alternative approach to the super-grid method where the domain expansion is accomplished by altering the wave speed rather than with coordinate transformations. To isolate these issues, other parameters such as variations in the ocean floor are neglected. With this simplification, cylindrical coordinates are used and the angular variation is assumed to be zero. This reduces the problem to a quasi-three-dimensional system. We study how the parameters of the alternative absorbing layer approach affect its quality. The numerical solver is verified on several test cases and appears to work according to theory. Finally, a semi-realistic simulation is carried out and the solution seems correct in this setting.