Development of 2D models to estimate nearshore bathymetry and sediment transport

We examine the interactions and feedbacks between bathymetry, waves, currents, and sediment transport. The first two pro jects focus on the use of remote sensing techniques to expand our knowledge of the nearshore. Due to the plethora of snap-shot data that is available from satellites and their distribution via Google Earth, having a method that can determine bathymetry from spatial wave patterns would be very valuable. Utilizing remotely-sensed wave refraction patterns of nearshore waves, we estimate bathymetry gradients in the nearshore through the 2D irrotationality of the wave number equation. The model, discussed in Chapter 2, uses an augmented form of the refraction equation that relates gradients in bathymetry to gradients in wavenumber and wave angle through the chain rule. The equations are cast in a form that is independent of wave period, so can be solved using wavenumber and direction data from a single snapshot rather than the normally-required time series of images. Synthetic testing of the model using monochromatic waves on three bathymetries of increasing complexity, showed that the model accurately estimated 2D bathymetry gradients, hence bathymetry, with a mean bias of 0.01 m and mean root mean square error over the three beaches of 0.17 m for depths less than 5 m. While the model is not useful for cases of complex seas or small refraction signals, the simplified data requirement of only a single snapshot is attractive. The model is perhaps best suited for shorter period swell conditions (wave periods of 8-10 seconds), for example, where strong refraction patterns are visible and wave number, k, and wave angle, θ, are easily extracted from a single frame image. Secondly, remotely sensed images of wave breaking over complex bathymetry are used to study the nonlinear feedbacks between two-dimensional (horizontal), 2DH, morphol- ogy and cross-shore migration rates of the alongshore averaged bar. We first test a linear model on a subset of 4 years of data at Palm Beach, Australia. The results are discussed in Chapter 3. The model requires eight free parameters, solved for using linear regression of the data to model the relationship between alongshore averaged bar position, x, along- shore sinuosity of the bar, a, and wave forcing, F = H 2 o . The linear model suggests that 2DH bathymetry is linked to cross-shore bar migration rates. Nevertheless, the primary limitation is that variations in bar position and variability are required to be temporally uncorrelated with forcing in order to achieve meaningful results. For large storms, this is indeed the case. However, many smaller storms seen at Palm Beach show that changes in bar position and variability are correlated with forcing and bar interaction dynamics are not separable from bar - forcing dynamics. In Chapter 4 a nonlinear model is subsequently developed and tested on the same data set. Initial equations for cross-shore sediment transport are formulated from commonly accepted theory using energetics-type equations. Cross-shore transport is based on the deviations around an equilibrium amount of roller contribution with the nonlinearity of the model forcing sediment transport to zero in the absence of wave breaking. The extension to 2DH is based on parameterizations of bar variability and the associated 2DH circulation. The model has five free parameters used to describe the relation between alongshore averaged bar position, x, 2DH bar variability, a, and wave characteristics (wave height, H , wave period, T , and wave angle, θ). The model is able to span multiple storms, accurately predicting bar migration for both onshore and offshore events. The longest individual data set tested is approximately 6 months. Using manually determined values for the coefficients, bar position is predicted with an R2 value of 0.42 over this time period. The effect of including a 2D dependency both increased rates of onshore migration and prevented highly 2D systems from migrating offshore under moderate wave heights. The model is also compared against a 1DH version by setting the 2D dependency term to unity and using the same values for the five free parameters. The 1DH model showed limited skill at predicting onshore migration rates, suggesting again that the inclusion of 2DH terms is important. The last pro ject (Chapter 5) explored the utilization of changes in bathymetry, ∆h/∆t, to gain further understanding of the feedbacks between 2D sediment transport patterns, Qx and Qy , with respect to existing bathymetry in the nearshore. The model is based on the 2D continuity equation that relates changes in bathymetry to gradients in the cross-shore, ∂ Qx /∂ x, and the alongshore, ∂ Qy /∂ y, directions. The problem is under-determined, having two unknowns (Qy and Qx) and only one known (∆h/∆t) such that a series of constraints must be applied in order to solve for transport. We as- sume that that the cross-shore integral of Qx is closed, such that no sand enters or exits the system in this direction. By conservation of mass, this requires changes in volume of the cross-shore transect to be due to longshore gradients in Qy . We test six rules for distributing Qy : three rules describing the initial longshore transport (Qr y ) and three describing the cross-shore distribution of the excess volume component (Qe y ). Initial re- sults suggest that requiring sediment to travel down slope (Qry = f (βy )) is an intuitive choice for describing transport of distinct perturbations. However, in one example field test this method did not perform well and the approach may need further refinements. Alternatively, having Qrx and Qry depend on spatial correlation lags between two sur- veys showed good results for identifying transport associated with alongshore migrating features. This method, however, did not do well under strict onshore migration of 2D features, where alongshore transport was not predicted. A hybrid approach, using both the down-slope constraint and spatial correlation lags may provide more robust predic- tions of sediment transport patterns in complex environments. Due to the lack of closed boundaries in the alongshore, knowledge of Qy (x, y0 ) is required to obtain sensible net sediment transport patterns. Alternatively, spatial patterns of the transport gradients (∂ Qy /∂ y, ∂ Qx /∂ x), which ultimately determine bar migrations provide useful insight into the system behavior without requiring Qy (x, y0 )

A behavior‐oriented dynamic model for sandbar migration and 2DH evolution

A nonlinear model is developed to study the time‐dependent relationship between the alongshore variability of a sandbar, a(t), and alongshore‐averaged sandbar position, xc(t). Sediment transport equations are derived from energetics‐based formulations. A link between this continuous physical representation and a parametric form describing the migration of sandbars of constant shape is established through a simple transformation of variables. The model is driven by offshore wave conditions. The parametric equations are dynamically coupled such that changes in one term (i.e., xc) drive changes in the other (i.e., a(t)). The model is tested on 566 days of data from Palm Beach, New South Wales, Australia. Using weighted nonlinear least squares to estimate best fit model coefficients, the model explained 49% and 41% of the variance in measured xc and a(t), respectively. Comparisons against a 1‐D horizontal (1DH) version of the model showed significant improvements when the 2DH terms were included (1DH and 2DH Brier skill scores were −0.12 and 0.42, respectively). Onshore bar migration was not predicted in the 1DH model, while the 2DH model correctly predicted onshore migration in the presence of 2DH morphology and allowed the bar to remain closer to shore for a given amount of breaking, providing an important hysteresis to the system. The model is consistent with observations that active bar migration occurs under breaking waves with onshore migration occurring at timescales of days to weeks and increasing 2DH morphology, while offshore migration occurs rapidly under high waves and coincides with a reduction in 2DH morphology.Keywords: 2DH evolution, Sandbar migratio

Coastal shoreline change assessments at global scales

During the present era of rapid climate change and sea-level rise, coastal change science is needed at global, regional, and local scales. Essential elements of this science, regardless of scale, include that the methods are defendable and that the results are independently verifiable. The recent contribution by Almar et al.1 does not achieve either of these measures as shown by: (i) the use of an error-prone proxy for coastal shoreline and (ii) analyses that are circular and explain little of the data variance

Coastal vulnerability across the Pacific dominated by El Niño/Southern Oscillation

To predict future coastal hazards, it is important to quantify any links between climate drivers and spatial patterns of coastal change. However, most studies of future coastal vulnerability do not account for the dynamic components of coastal water levels during storms, notably wave-driven processes, storm surges and seasonal water level anomalies, although these components can add metres to water levels during extreme events. Here we synthesize multi-decadal, co-located data assimilated between 1979 and 2012 that describe wave climate, local water levels and coastal change for 48 beaches throughout the Pacific Ocean basin. We find that observed coastal erosion across the Pacific varies most closely with El Niño/Southern Oscillation, with a smaller influence from the Southern Annular Mode and the Pacific North American pattern. In the northern and southern Pacific Ocean, regional wave and water level anomalies are significantly correlated to a suite of climate indices, particularly during boreal winter; conditions in the northeast Pacific Ocean are often opposite to those in the western and southern Pacific. We conclude that, if projections for an increasing frequency of extreme El Niño and La Niña events over the twenty-first century are confirmed, then populated regions on opposite sides of the Pacific Ocean basin could be alternately exposed to extreme coastal erosion and flooding, independent of sea-level rise.The published article is copyrighted by the author(s) and published by Nature Publishing Group. The published article can be found at: http://www.nature.com/ngeo/index.htm

LIDAR Scanning as an Advanced Technology in Physical Hydraulic Modelling: The Stilling Basin Example

In hydraulic engineering, stilling basin design is traditionally carried out using physical models, conducting visual flow observations as well as point-source measurements of pressure, flow depth, and velocity at locations of design relevance. Point measurements often fail to capture the strongly varying three-dimensionality of the flows within the stilling basin that are important for the best possible design of the structure. This study introduced fixed scanning 2D LIDAR technology for laboratory-scale physical hydraulic modelling of stilling basins. The free-surface motions were successfully captured along both longitudinal and transverse directions, providing a detailed free-surface map. LIDAR-derived free-surface elevations were compared with typical point-source measurements using air–water conductivity probes, showing that the elevations measured with LIDAR consistently corresponded to locations of strongest air–water flow interactions at local void fractions of approximately 50%. The comparison of LIDAR-derived free-surface elevations with static and dynamic pressure sensors confirmed differences between the two measurement devices in the most energetic parts of the jump roller. The present study demonstrates that LIDAR technology can play an important role in physical hydraulic modelling, enabling design improvement through detailed free-surface characterization of complex air–water flow motions beyond the current practice of point measurements and visual flow observations

Remote Sensing Is Changing Our View of the Coast: Insights from 40 Years of Monitoring at Narrabeen-Collaroy, Australia

Narrabeen-Collaroy Beach, located on the Northern Beaches of Sydney along the Pacific coast of southeast Australia, is one of the longest continuously monitored beaches in the world. This paper provides an overview of the evolution and international scientific impact of this long-term beach monitoring program, from its humble beginnings over 40 years ago using the rod and tape measure Emery field survey method; to today, where the application of remote sensing data collection including drones, satellites and crowd-sourced smartphone images, are now core aspects of this continuing and much expanded monitoring effort. Commenced in 1976, surveying at this beach for the first 30 years focused on in-situ methods, whereby the growing database of monthly beach profile surveys informed the coastal science community about fundamental processes such as beach state evolution and the role of cross-shore and alongshore sediment transport in embayment morphodynamics. In the mid-2000s, continuous (hourly) video-based monitoring was the first application of routine remote sensing at the site, providing much greater spatial and temporal resolution over the traditional monthly surveys. This implementation of video as the first of a now rapidly expanding range of remote sensing tools and techniques also facilitated much wider access by the international research community to the continuing data collection program at Narrabeen-Collaroy. In the past decade the video-based data streams have formed the basis of deeper understanding into storm to multi-year response of the shoreline to changing wave conditions and also contributed to progress in the understanding of estuary entrance dynamics. More recently, ‘opportunistic’ remote sensing platforms such as surf cameras and smartphones have also been used for image-based shoreline data collection. Commencing in 2011, a significant new focus for the Narrabeen-Collaroy monitoring program shifted to include airborne lidar (and later Unmanned Aerial Vehicles (UAVs)), in an enhanced effort to quantify the morphological impacts of individual storm events, understand key drivers of erosion, and the placing of these observations within their broader regional context. A fixed continuous scanning lidar installed in 2014 again improved the spatial and temporal resolution of the remote-sensed data collection, providing new insight into swash dynamics and the often-overlooked processes of post-storm beach recovery. The use of satellite data that is now readily available to all coastal researchers via Google Earth Engine continues to expand the routine data collection program and provide key insight into multi-decadal shoreline variability. As new and expanding remote sensing technologies continue to emerge, a key lesson from the long-term monitoring at Narrabeen-Collaroy is the importance of a regular re-evaluation of what data is most needed to progress the science

Rapid adjustment of shoreline behavior to changing seasonality of storms : Observations and modelling at an open-coast beach

An 8-year time series of weekly shoreline data collected at the Gold Coast, Australia, is used to examine the temporal evolution of a beach, focusing on the frequency response of the shoreline to time-varying wave height and period. Intriguingly, during 2005 the movement of the shoreline at this site changed from a seasonally-dominated mode (annual cycle) to a storm-dominated (~monthly) mode. This unexpected observation provides the opportunity to explore the drivers of the observed shoreline response. Utilizing the calibration of an equilibrium shoreline model to explore the time-scales of underlying beach behavior, the best-fit frequency response (days-1) is shown to be an order of magnitude higher post-2004, suggesting that a relatively subtle change in wave forcing can drive a significant change in shoreline response. Analysis of available wave data reveals a statistically significant change in the seasonality of storms, from predominantly occurring at the start of the year pre-2005 to being relatively consistent throughout the year after this time. The observed change from one mode of shoreline variability to another suggests that beaches can adapt relatively quickly to subtle changes in the intra-annual distribution of wave energy

Rapid adjustment of shoreline behavior to changing seasonality of storms : Observations and modelling at an open-coast beach

An 8-year time series of weekly shoreline data collected at the Gold Coast, Australia, is used to examine the temporal evolution of a beach, focusing on the frequency response of the shoreline to time-varying wave height and period. Intriguingly, during 2005 the movement of the shoreline at this site changed from a seasonally-dominated mode (annual cycle) to a storm-dominated (~monthly) mode. This unexpected observation provides the opportunity to explore the drivers of the observed shoreline response. Utilizing the calibration of an equilibrium shoreline model to explore the time-scales of underlying beach behavior, the best-fit frequency response (days-1) is shown to be an order of magnitude higher post-2004, suggesting that a relatively subtle change in wave forcing can drive a significant change in shoreline response. Analysis of available wave data reveals a statistically significant change in the seasonality of storms, from predominantly occurring at the start of the year pre-2005 to being relatively consistent throughout the year after this time. The observed change from one mode of shoreline variability to another suggests that beaches can adapt relatively quickly to subtle changes in the intra-annual distribution of wave energy

Dynamic Motions of Piled Floating Pontoons Due to Boat Wake and Their Impact on Postural Stability and Safety

Piled floating pontoons are public access structures that provide a link between land and sea. Despite floating pontoons being frequented by the public, there is limited data available to coastal or maritime engineers detailing the dynamic motions (acceleration and rotation) of these structures under wave action and the impact of these motions on public comfort and safety to inform their design. This contribution summarises results from a set of laboratory-scale physical model experiments of two varying beam width piled floating pontoons subjected to boat wake conditions. Observed accelerations and roll angles were dependent on beam-to-wavelength ratio (B/L), with the most adverse motion response observed for B/L ~0.5. Internal mass of the pontoon played a secondary role, with larger mass structures experiencing lower accelerations for similar B/L ratios. Importantly, these new experimental results reveal the complex interaction between the piles and pontoon that result in peak accelerations more than six times the nominated operational safe motion limit of 0.1g. Root mean square (RMS) accelerations were more than three times the nominated comfort limit (0.02g) and angles of rotation more than double what would be perceived as safe (6 degrees) for the boat wake conditions tested. The frequency of acceleration also suggests patrons standing on these platforms are likely to experience discomfort and instability. Laboratory results are compared against a series of field-scale experiments of pontoon motion response and patron feedback. The dynamic motion response of pontoons tested in both field-scale and laboratory experiments compared well