Thesis (M.S. in Physics) Naval Postgraduate School, Dec. 1996. / Thesis advisors, Richard Christopher Olsen, Newell Garfield. AD-A329 389. Includes bibliographical references (p. 73-75). Also available online.

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Idealized bathymetries were subjected to idealized cyclones in order to measure the storm surge response to a range of bathymetry features, under various storm conditions. Ten bathymetries were considered, including eight shoals, one pit, and a featureless reference domain. Six storms (two different sizes/intensities and three different landfall directions) were used as meteorological forcing. The bathymetry features influenced local surge response during pre- and post-peak surge conditions. However, peak surge and surge at the coast were not meaningfully affected by the presence of the bathymetry features considered. The effect of three bathymetry feature parameters on surge response was analyzed (i.e. depth below mean sea level, cross-shore width, and distance from shore). Of these parameters, feature depth below mean sea level was the most influential on surge generation.

Beaches and barrier islands are vulnerable to extreme storm events, such as hurricanes, that can cause severe erosion and overwash to the system. Having dunes and a wide beach in front of coastal infrastructure can provide protection during a storm, but the influence that nearshore bathymetric features have in protecting the beach and barrier island system is not completely understood. The spatial variation in nearshore features, such as sand bars and beach cusps, can alter nearshore hydrodynamics, including wave setup and runup. The influence of bathymetric features on long-wave runup can be used in evaluating the vulnerability of coastal regions to erosion and dune overtopping, evaluating the changing morphology, and implementing plans to protect infrastructure. In this thesis, long-wave runup variation due to changing bathymetric features as determined with the numerical model XBeach is quantified (eXtreme Beach behavior model). Wave heights are analyzed to determine the energy through the surfzone. XBeach assumes that coastal erosion at the land-sea interface is dominated by bound long-wave processes. Several hydrodynamic conditions are used to force the numerical model. The XBeach simulation results suggest that bathymetric irregularity induces significant changes in the extreme long-wave runup at the beach and the energy indicator through the surfzone.

This study proposes and demonstrates a through-water photogrammetry approach for Satellite Derived Bathymetry (SDB), which may be used to map nearshore bathymetry in the Canadian Arctic. A four step process is used: First, a standard photogrammetric extraction is performed on 2 m resolution WorldView stereo imagery, then apparent depths are calculated by referencing submerged points to the extracted elevation of the water level seen in the image. Due to the effects of refraction, these apparent depths are underestimates, and a refraction correction factor is applied to convert to actual depths. Finally, tidal stage at the time of image acquisition is used to bring depths to chart datum. A post processing step may be applied to remove erroneous depths caused by water surface objects such as boats, debris, or large waves. This was demonstrated in six study areas across Nunavut, Canada to test its robustness under a variety of environmental conditions, including different seafloor types, and under varying sea states. The six study sites were (with vertical accuracy given in Root Mean Square Error/and vertical bias, both in meters): eastern Coral Harbour (1.18/0.03), western Coral Harbour (0.78/-0.32), Cambridge Bay (1.16/0.08), Queen Maud Gulf (0.97/0.13), Arviat (1.02/0.13), and Frobisher Bay, where bathymetry extraction largely failed due to unfavourable sea surface conditions. These findings show that the proposed method has similar or better vertical accuracy as currently established SDB approaches; however, it has several benefits over the established methods which make it better suited for the Arctic. Namely, not requiring the precise atmospheric correction necessary for physics-based models, which is difficult at high latitudes; as well as being able to function in heterogeneous seafloor environments and not needing in-situ calibration data like the empirical spectral ratio approach, better suiting it to remote Arctic waters which often lack existing bathymetric survey data.

The Tonga-Kermadec arc in the SW Pacific comprises a chain of more than 90 volcanic complexes. A continuous 400-km long chain of volcanic activity along the central portion of the Tonga arc has become the focus of intensive research, extending previous studies that have focused on the southern Kermadec chain. Earlier interpretations of the Tonga arc have focused on a perceived lack of volcanism between ~21°S and ~27°S, adjacent to a bend in the trench caused by the collision of the subducting Louisville Seamount Chain (LSC). During swath mapping in 2002, it was revealed that this portion of the arc, including the Louisville and Monowai segments, is in fact one of the most volcanically active parts of the Tonga-Kermadec system. At this location, a combination of oblique convergence of the Pacific Plate and southward compression due to the collision of the LSC has resulted in left-lateral strike-slip faulting and rifting of the arc crust. This has produced a series of left-stepping arc transverse graben and horst structures that localize the voluminous volcanic activity. For this study, a new 1:250,000 scale geological map of the Louisville and Monowai segments has been constructed as a framework for a quantitative analysis of arc volcanism and the eruptive history of these segments. Two types of volcanoes dominate the arc front: deep caldera systems (collapse structures formed due to the evacuation of magma) within the arc rifts, and smaller volcanic cones between the rifts. The cone volcanoes tend to have small summit craters (<10 km3) whereas the large caldera volcanoes have major depressions of up to 50 km3. The cones are relatively undeformed, whereas the larger calderas are affected by multiple stages of collapse, asymmetric subsidence, and distortion caused by regional stresses. Surveys of the crater walls of the cone volcanoes show a predominance of volcaniclastic deposits, whereas the caldera volcanoes contain a high proportion of coherent lava flows. The caldera volcanoes also show a prevalence of basaltic melts compared to the more andesitic and dacitic cones. The largest caldera volcano is the Monowai volcanic complex (25°53’S) occupying a deep depression (Monowai Rift Graben) that crosses the arc front. The volcanic complex consists of a large caldera (12 km wide, 1600 m deep) and an adjacent stratovolcano (Monowai Cone) rising nearly to sea level. We suggest that the different types of volcanoes along the Louisville and Monowai segments reflect the influence of deep structures within the arc crust that have localized strikeslip and normal faulting.

No / Submerged palaeolandscapes can contain pristine underwater heritage. Regular monitoring of these areas is essential to assess and mitigate threats from development including construction, mining, and commercial trawling. While bathymetry alone may be insufficient to detect submerged palaeolandscape features, it can nonetheless recognize previously mapped structures that have a topographic expression. The Sentinel-1 constellation will provide unprecedented access to freely available, high-resolution Synthetic Aperture Radar (SAR) data, acquired systematically and with long-term continuity, and may constitute a cost-effective solution for the monitoring of submerged palaeolandscapes. The article shows the application of a recently developed bathymetric algorithm to Sentinel-1 SAR data over a region of the southern North Sea. Results show general agreement with water depth data obtained from the European Marine Observation and Data Network portal for bathymetry (EMODnet). To assess the support that SAR bathymetry can provide to the analysis of submerged palaeolandscapes, the Sentinel-1-derived water depths were compared to a palaeolandscape map of the same area produced by the North Sea Palaeolandscapes Project (NSPP). Results show a clear correspondence between certain topographic structures identified in the Sentinel-1 water depth map and features interpreted by the NSPP as early Holocene lakes, rivers, and landscape topography.

Nearshore bathymetry in the Canadian Arctic is poorly surveyed, but is vital knowledge for coastal communities that rely on marine transportation for resources and development. Nautical charts currently available are often outdated and surveying by traditional methods is both time consuming and expensive. Satellite-derived bathymetry (SDB) offers a significantly cheaper and faster option to provide information on nearshore bathymetry. The two most common approaches to SDB are empirical and physics-based. The empirical approach is simple and typically does well when calibrated with high-quality in-situ data, whereas the physics-based approach is more difficult to implement and requires precise atmospheric correction. This project tests the practical use of five methods within the empirical and physics-based approaches to SDB, using Landsat 8 and Sentinel-2 satellite imagery, at seven sites across Nunavut. Methods tested include: the Ratio-Transform, Multiband, and Random Forest Regression methods (empirical) and radiative transfer modeling (physics-based) using two atmospheric correction models: ACOLITE and Deep Water Correction. All methods typically use geolocated water depth data for validation, as well as calibration for the empirical methods. Spectral reflectance for model inputs were collected in Cambridge Bay, NU. Water depth data were acquired from the Canadian Hydrographic Service. All processing was conducted within the framework of plugins developed for the open-source GIS software, QGIS. Results from the empirical methods were typically poor due to poor calibration data, though Random Forest Regression performed well when good calibration data were available. Due to poor quality validation data, error for the physics-based results cannot be adequately quantified in most places. Additionally, atmospheric correction remains a challenge for the physics-based methods. Overall, results indicate that where large, high-quality calibration datasets are available, Random Forest Regression performs best of all methods tested, with little bias and low mean absolute error in water less than 10 m deep. As such datasets are rare in the Arctic, the physics-based method is often the only option for SDB and is an excellent qualitative tool for informing communities of shallow bathymetry features and assessing navigation risk.

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques.