ORCID Profile
0000-0002-0082-8444
Current Organisation
UNSW Sydney
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Natural Hazards | Physical Oceanography | Geomorphology and earth surface processes | Maritime engineering | Geology | Physical Geography and Environmental Geoscience | Environmental Engineering Modelling | Maritime Engineering | Ocean Engineering | Marine Geoscience | Ocean engineering
Natural Hazards in Coastal and Estuarine Environments | Coastal and Estuarine Land Management | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Tourism Infrastructure Development |
Publisher: Cambridge University Press (CUP)
Date: 2023
DOI: 10.1017/CFT.2023.22
Abstract: Although coasts are frequently seen as at the frontline of near-future environmental risk, there is more to the understanding of the future of coastal environments than a simple interaction between increasing hazards (particularly related to global sea level rise) and increasing exposure and vulnerability of coastal populations. The environment is both multi-hazard and regionally differentiated, and coastal populations, in what should be seen as a coupled social–ecological–physical system, are both affected by, and themselves modify, the impact of coastal dynamics. As the coupled dance between human decisions and coastal environmental change unfolds over the coming decades, transdisciplinary approaches will be required to come to better decisions on identifying and following sustainable coastal management pathways, including the promotion of innovative restoration activities. Inputs from indigenous knowledge systems and local communities will be particularly important as these stakeholders are crucial actors in the implementation of ecosystem-based mitigation and adaptation strategies.
Publisher: MDPI AG
Date: 27-05-2021
DOI: 10.3390/JMSE9060582
Abstract: In this paper, a new approach to model wave-driven, cross-shore shoreline change incorporating multiple timescales is introduced. As a base, we use the equilibrium shoreline prediction model ShoreFor that accounts for a single timescale only. High-resolution shoreline data collected at three distinctly different study sites is used to train the new data-driven model. In addition to the direct forcing approach used in most models, here two additional terms are introduced: a time-upscaling and a time-downscaling term. The upscaling term accounts for the persistent effect of short-term events, such as storms, on the shoreline position. The downscaling term accounts for the effect of long-term shoreline modulations, caused by, for ex le, climate variability, on shorter event impacts. The multi-timescale model shows improvement compared to the original ShoreFor model (a normalized mean square error improvement during validation of 18 to 59%) at the three contrasted sandy beaches. Moreover, it gains insight in the various timescales (storms to inter-annual) and reveals their interactions that cause shoreline change. We find that extreme forcing events have a persistent shoreline impact and cause 57–73% of the shoreline variability at the three sites. Moreover, long-term shoreline trends affect short-term forcing event impacts and determine 20–27% of the shoreline variability.
Publisher: American Meteorological Society
Date: 04-2020
Abstract: The Australian marine research, industry, and stakeholder community has recently undertaken an extensive collaborative process to identify the highest national priorities for wind-waves research. This was undertaken under the auspices of the Forum for Operational Oceanography Surface Waves Working Group. The main steps in the process were first, soliciting possible research questions from the community via an online survey second, reviewing the questions at a face-to-face workshop and third, online ranking of the research questions by in iduals. This process resulted in 15 identified priorities, covering research activities and the development of infrastructure. The top five priorities are 1) enhanced and updated nearshore and coastal bathymetry 2) improved understanding of extreme sea states 3) maintain and enhance the in situ buoy network 4) improved data access and sharing and 5) ensemble and probabilistic wave modeling and forecasting. In this paper, each of the 15 priorities is discussed in detail, providing insight into why each priority is important, and the current state of the art, both nationally and internationally, where relevant. While this process has been driven by Australian needs, it is likely that the results will be relevant to other marine-focused nations.
Publisher: MDPI AG
Date: 09-09-2021
DOI: 10.3390/RS13183599
Abstract: 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.
Publisher: The Oceanography Society
Date: 09-2017
Publisher: Coastal Engineering Research Council
Date: 14-12-2012
DOI: 10.9753/ICCE.V33.MANAGEMENT.21
Abstract: In coastal management under climatic pressures, the final aim of vulnerability assessments, system thinking or scenario planning exercises is to inform the identification of the most appropriate adaptation options for communities under risk of coastal hazards and climate change. In this paper we show how we combined these techniques for coastal settlements adaptation in South East Queensland, one of the most populated Australian regions, including: (i) the use of suburb-level mapping and numerical modelling to identify and assess vulnerability hotspots (ii) the development and testing of systems thinking and bayesian modelling techniques to explore adaptation pathways and the adaptive capacity of coastal communities and (iii) the use of scenario planning techniques to test adaptation options in an uncertain future. We show how these outcomes were used to develop a range of research-based adaptation policies, programs and actions and to inform the preparation of practical guidance for councils across Queensland.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Springer Science and Business Media LLC
Date: 29-09-2023
Publisher: Elsevier BV
Date: 07-2017
Publisher: Coastal Engineering Research Council
Date: 28-10-2014
Publisher: Cambridge University Press (CUP)
Date: 23-12-2023
DOI: 10.1017/CFT.2022.12
Abstract: Whilst there is little argument that coasts are on the frontline when it comes to the impacts of near-future global environmental change, is there a need for yet another coastal journal? Emphatically ‘yes’. There is an unfilled niche here for a forum that promotes and presents cross-disciplinary research, from fundamental science to impact-orientated approaches. We wish to see a journal that informs pathways away from unsustainable practices towards more socially just and equitable futures for the world’s coastlines and their communities. We set out below some of the questions that arise when articulating this pathway, using the high-level categories in the journal’s topic map as some of the stepping stones that will be encountered along the way.
Publisher: Elsevier BV
Date: 08-2019
Publisher: Springer Science and Business Media LLC
Date: 07-02-2020
DOI: 10.1038/S41598-020-59018-Y
Abstract: Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than in idual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.
Publisher: MDPI AG
Date: 06-11-2018
DOI: 10.3390/RS10111744
Abstract: 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 in idual 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.
Publisher: California Digital Library (CDL)
Date: 12-07-2023
DOI: 10.31223/X58W98
Abstract: Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline (SDS) mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established SDS algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for SDS algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.
Publisher: American Geophysical Union (AGU)
Date: 09-11-2020
DOI: 10.1029/2020GL090724
Abstract: A novel approach to improve seasonal to interannual sandy shoreline predictions is presented, whereby model‐free parameters can vary in time, adjusting to potential nonstationarity in the underlying model forcing. This is achieved by adopting a suitable data assimilation technique (dual state‐parameter ensemble Kalman filter) within the established shoreline evolution model ShoreFor. The method is first tested and evaluated using synthetic scenarios, specifically designed to emulate a broad range of natural sandy shoreline behavior. This approach is then applied to a real‐world shoreline data set, revealing that time‐varying model‐free parameters are linked through physical processes to changing characteristics of the wave forcing. Greater accuracy of shoreline predictions is achieved, compared to existing stationary modeling approaches. It is anticipated that the wider application of this method can improve our understanding and prediction of future beach erosion patterns and trends in a changing wave climate.
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 2014
Publisher: Wiley
Date: 23-07-2020
Publisher: American Geophysical Union (AGU)
Date: 07-2023
DOI: 10.1029/2022JF006936
Abstract: Satellite‐derived shoreline observations combined with dynamic shoreline models enable fine‐scale predictions of coastal change across large spatiotemporal scales. Here, we present a satellite‐data‐assimilated, “littoral‐cell”‐based, ensemble Kalman‐filter shoreline model to predict coastal change and uncertainty due to waves, sea‐level rise (SLR), and other natural and anthropogenic processes. We apply the developed ensemble model to the entire California coastline (approximately 1,760 km), much of which is sparsely monitored with traditional survey methods (e.g., Lidar/GPS). Water‐level‐corrected, satellite‐derived shoreline observations (obtained from the CoastSat toolbox) offer a nearly unbiased representation of in situ surveyed shorelines (e.g., mean sea‐level elevation contours) at Ocean Beach, San Francisco. We demonstrate that model calibration with satellite observations during a 20‐year hindcast period (1995–2015) provides nearly equivalent model forecast accuracy during a validation period (2015–2020) compared to model calibration with monthly in situ observations at Ocean Beach. When comparing model‐predicted shoreline positions to satellite‐derived observations, the model achieves an accuracy of m RMSE for nearly half of the entire California coastline for the validation period. The calibrated/validated model is then applied for multi‐decadal simulations of shoreline change due to projected wave and sea‐level conditions, while holding the model parameters fixed. By 2100, the model estimates that 24%–75% of California's beaches may become completely eroded due to SLR scenarios of 1.0–3.0 m, respectively. The satellite‐data‐assimilated modeling system presented here is generally applicable to a variety of coastal settings around the world owing to the global coverage of satellite imagery.
Publisher: Wiley
Date: 23-04-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2011
Publisher: World Scientific Publishing Company
Date: 04-2007
Publisher: American Geophysical Union (AGU)
Date: 20-01-2023
DOI: 10.1029/2022GL100498
Abstract: Accurately mapping the evolving bathymetry under energetic wave breaking is challenging, yet critical for improving our understanding of sandy beach morphodynamics. Though remote sensing is one of the most promising opportunities for reaching this goal, existing depth‐inversion algorithms using linear approaches face major theoretical and/or technical issues in the surf zone, limiting their accuracy over this region. Here, we present a new depth‐inversion approach relying on Boussinesq theory for quantifying nonlinear dispersion effects in nearshore waves. Using high‐resolution datasets collected in the laboratory under erse wave conditions and beach morphologies, we demonstrate that this approach results in enhanced levels of accuracy in the surf zone (errors typically within 10%) and presents a major improvement over linear methods. The new nonlinear depth‐inversion approach provides significant prospects for future practical applications in the field using existing remote sensing technologies, including continuous lidar scanners and stereo‐imaging systems.
Publisher: Elsevier BV
Date: 07-2013
Publisher: Wiley
Date: 26-10-2020
Publisher: Elsevier BV
Date: 05-2018
Publisher: American Geophysical Union (AGU)
Date: 14-07-2020
DOI: 10.1029/2020GL088365
Abstract: The steepness of the beach face is a fundamental parameter for coastal morphodynamic research. Despite its importance, it remains extremely difficult to obtain reliable estimates of the beach‐face slope over large spatial scales (thousands of km of coastline). In this letter, a novel approach to estimate this slope from time series of satellite‐derived shoreline positions is presented. This new technique uses a frequency domain analysis to find the optimum slope that minimizes high‐frequency tidal fluctuations relative to lower‐frequency erosion/accretion signals. A detailed assessment of this new approach at eight locations spanning a range of tidal regimes, wave climates, and sediment grain sizes shows strong agreement ( R 2 = 0.93) with field measurements. The automated technique is then applied across thousands of beaches in eastern Australia and California, USA, revealing similar regional‐scale distributions along these two contrasting coastlines and highlights the potential for new global‐scale insight to beach‐face slope spatial distribution, variability, and trends.
Publisher: California Digital Library (CDL)
Date: 29-10-2023
DOI: 10.31223/X5GX02
Publisher: Research Square Platform LLC
Date: 12-07-2021
DOI: 10.21203/RS.3.RS-666160/V1
Abstract: In the Pacific Basin, El Niño/Southern Oscillation (ENSO) is the dominant mode of interannual climate variability and drives substantial changes in oceanographic forcing, likely having a significant impact on Pacific coastlines. Yet, how sandy coasts respond to these basin-scale changes has to date been limited to a few long-term beach monitoring sites, predominantly on developed coasts. Here we use 35 years of Landsat imagery to map shoreline variability around the Pacific Rim (72,000 beach transects) and identify coherent patterns of beach erosion and accretion controlled by ENSO. We find that approximately one third of all beaches experience significant erosion during El Niño phases, with the Eastern Pacific particularly vulnerable to widespread erosion (most notably during the large 1997/1998 event). In contrast, La Niña events coincide with significant accretion for approximately one quarter of all beaches, although conversely drives substantial erosion in south-east Australia and other localized regions. The significant regional variability in coastal response to ENSO should be considered in light of future projected intensification and shifts in ENSO litudes and flavors.
Publisher: American Geophysical Union (AGU)
Date: 11-2019
DOI: 10.1029/2019JF005184
Abstract: The erosion impact of large coastal storm events typically occurs across broad (100s of km) sections of coastline and may include significant variability both alongshore and vertically between the berm and dunes. Identifying controls of variability in storm erosion is critical to understanding the response of coastlines to present and changing storminess. This contribution analyses immediate pre‐ and post‐storm Lidar data of over 1700 cross‐shore profile transects, determined at every 100 m alongshore and spanning 400km of the southeast Australian coastline. This unique dataset allowed for a data‐driven Bayesian network analysis of the key relationships between the measured storm erosion response and a range of variables describing the antecedent morphology and hydrodynamic forcing at the coastline. It was found that while erosion of the dune and berm was observed to increase with increased exposure of the local profile to incident storm waves, additional erosion controls were found to be different for these two different sections of the beach. Erosion of the berm was specifically linked to the pre‐storm berm volume, with more accreted berms experiencing a greater proportion of erosion of the overall berm, regardless of variability in forcing conditions. In contrast, dune erosion was equally controlled by the exceedance of wave runup above the antecedent dune toe elevation and the width of the beach immediately fronting the dune, with wider beaches resulting in reduced dune erosion. The results of this large, data‐driven analysis provide important affirmation and insights into the primary controls of berm and dune storm erosion.
Publisher: Elsevier BV
Date: 10-2016
Publisher: Cambridge University Press (CUP)
Date: 2023
DOI: 10.1017/CFT.2023.1
Abstract: Fjord systems are transition zones between land and sea, resulting in complex and dynamic environments. They are of particular interest in the Arctic as they harbour ecosystems inhabited by a rich range of species and provide many societal benefits. The key drivers of change in the European Arctic (i.e., Greenland, Svalbard, and Northern Norway) fjord socio-ecological systems are reviewed here, structured into five categories: cryosphere (sea ice, glacier mass balance, and glacial and riverine discharge), physics (seawater temperature, salinity, and light), chemistry (carbonate system, nutrients), biology (primary production, biomass, and species richness), and social (governance, tourism, and fisheries). The data available for the past and present state of these drivers, as well as future model projections, are analysed in a companion paper. Changes to the two drivers at the base of most interactions within fjords, seawater temperature and glacier mass balance, will have the most significant and profound consequences on the future of European Arctic fjords. This is because even though governance may be effective at mitigating/adapting to local disruptions caused by the changing climate, there is possibly nothing that can be done to halt the melting of glaciers, the warming of fjord waters, and all of the downstream consequences that these two changes will have. This review provides the first transdisciplinary synthesis of the interactions between the drivers of change within Arctic fjord socio-ecological systems. Knowledge of what these drivers of change are, and how they interact with one another, should provide more expedient focus for future research on the needs of adapting to the changing Arctic.
Publisher: Elsevier BV
Date: 03-2013
Publisher: Frontiers Media SA
Date: 20-12-2021
DOI: 10.3389/FMARS.2021.788657
Abstract: Sandy beaches comprise approximately 31% of the world's ice-free coasts. Sandy coastlines around the world are continuously adjusting in response to changing waves and water levels at both short (storm) and long (climate-driven, from El-Nino Southern Oscillation to sea level rise) timescales. Managing this critical zone requires robust, advanced tools that represent our best understanding of how to abstract and integrate coastal processes. However, this has been hindered by (1) a lack of long-term, large-scale coastal monitoring of sandy beaches and (2) a robust understanding of the key physical processes that drive shoreline change over multiple timescales. This perspectives article aims to summarize the current state of shoreline modeling at the sub-century timescale and provides an outlook on future challenges and opportunities ahead.
Publisher: MDPI AG
Date: 02-11-2022
DOI: 10.3390/JMSE10111633
Abstract: 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.
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 10-2018
Publisher: World Scientific Publishing Company
Date: 04-2011
Publisher: California Digital Library (CDL)
Date: 13-01-2021
DOI: 10.31223/X54C73
Publisher: California Digital Library (CDL)
Date: 31-01-2022
DOI: 10.31223/X5Q592
Abstract: Coastal storms cause widespread damage to property, infrastructure, economic activity and the environment. Along open sandy coastlines, two of the primary coastal storm hazards are coastal flooding by elevated ocean water levels and beach erosion as the result of storm wave action. At continental margins characterized by a shallow, wide continental shelf, coastal storms are more commonly associated with lified storm surge and the damaging impacts caused by flooding of low-lying land. In contrast, along margins where the continental shelf is narrow and deep, coastal storm impacts are more often characterized by extensive beach erosion, due to the typically lower magnitude of storm surge but a higher proportion of deepwater wave energy reaching the shoreline. A new Storm Hazard Matrix is presented that integrates these two distinct but inherently linked open coast hazards. The approach is based on the combination of two hazard scales. The first is a ‘coastal flooding hazard scale’ that follows an established framework in which hazards are predominately driven by the vertical increase in ocean water levels during storms. The second is a storm wave ‘beach erosion hazard scale’ where hazards are predominately driven by the horizontal recession of the sandy beach and dune. The resulting framework comprises a total of nine unique combinations of flooding/erosion storm hazard regimes, from which six unified, qualitative indicators of the total storm hazard level ranging from ‘Low’ to ‘Extreme’ are defined. Real-world application of the Storm Hazard Matrix is explored at contrasting coastlines for two major storm events, encompassing an extratropical cyclone that impacted the coastline of southeast Australia in June 2016, and Hurricane Ivan that impacted the Gulf Coast of the United States in 2004. The new approach is shown to identify and distinguish between the severity of localized coastal flooding and/or coastal erosion, as well as provide enhanced insight to the nature, magnitude and alongshore variation of coastal storm hazards along the impacted coastline. Within the context of disaster risk reduction, preparedness and operational early warning, implementation of the Storm Hazard Matrix has the potential to deliver robust evaluations of storm hazards spanning a wider variety of both wave-dominated and surge-dominated coasts.
Publisher: Coastal Engineering Research Council
Date: 30-01-2011
DOI: 10.9753/ICCE.V32.SEDIMENT.95
Abstract: Spatial and temporal variability of longshore transport potential for a 35-km stretch of sandy coastline on the east coast of Australia is examined using a 25-year data set. Six-hourly offshore wave data is binned into yearly wave classes using a global k-means algorithm that accounts for wave height, period, and direction simultaneously. Wave class estimates are shoaled into the nearshore using MIKE 21 Spectral Wave (SW) model. Longshore transport is calculated using the formulas of K huis (1991 2002) and Bayram et al. (2007) and show good agreement with previously published estimates for the Gold Coast, suggesting the wave classification scheme sufficiently represents the variability in yearly wave data. Results show large temporal and spatial variability of transport potential along the coastline. Spatial variation is attributed to shoreline orientation and wave exposure, while temporal variability is significantly correlated with variations in the Southern Oscillation Index.
Publisher: Springer Science and Business Media LLC
Date: 12-04-2016
Abstract: Long-term observational datasets that record and quantify variability, changes and trends in beach morphology at sandy coastlines together with the accompanying wave climate are rare. A monthly beach profile survey program commenced in April 1976 at Narrabeen located on Sydney’s Northern Beaches in southeast Australia is one of just a handful of sites worldwide where on-going and uninterrupted beach monitoring now spans multiple decades. With the Narrabeen survey program reaching its 40-year milestone in April 2016, it is timely that free and unrestricted use of these data be facilitated to support the next advances in beach erosion-recovery modelling. The archived dataset detailed here includes the monthly subaerial profiles, available bathymetry for each survey transect extending seawards to 20 m water depth, and time-series of ocean astronomical tide and inshore wave forcing at 10 m water depths, the latter corresponding to the location of in idual survey transects. In addition, on-going access to the results of the continuing monthly survey program is described.
Publisher: Elsevier BV
Date: 12-2019
Publisher: Coastal Engineering Research Council
Date: 14-12-2012
DOI: 10.9753/ICCE.V33.SEDIMENT.98
Abstract: A robust and practical methodology for predicting future shoreline behaviour along sandy coastlines would be valuable to a broad range of coastal engineering applications. Present approaches for predicting shoreline evolution range from simple linear trend models, which cannot predict observed complex behaviour, to coupled hydrodynamic / sediment transport models, with seasonal to multi-year forecasting generally beyond present model capabilities. In this work a simple empirical shoreline variability model, ShoreFor (Shoreline Forecast), is investigated using a multi-decadal dataset to assess model performance at daily to decadal timescales. Model performance is assessed at five alongshore locations within an embayed study site that experience varying exposure to the offshore wave climate due to prominent adjacent headlands and display alongshore variable behaviour. To determine model sensitivity to input wave conditions, both the measured offshore and transformed (modelled) nearshore wave data are used and results compared. Strengths and limitations of the ShoreFor model are identified and discussed, along with ongoing model development and planned application of this modelling technique for shoreline forecasting using future water level and wave climate scenarios.
Publisher: Coastal Education and Research Foundation
Date: 05-2016
Publisher: American Geophysical Union (AGU)
Date: 29-01-2011
DOI: 10.1029/2010JC006382
Publisher: Elsevier BV
Date: 04-2022
Publisher: World Scientific Publishing Company
Date: 04-2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 11-2022
Publisher: Springer Science and Business Media LLC
Date: 21-09-2015
DOI: 10.1038/NGEO2539
Publisher: Elsevier BV
Date: 06-2015
Publisher: Elsevier BV
Date: 10-2012
Publisher: Coastal Education and Research Foundation
Date: 03-03-2016
DOI: 10.2112/SI75-078.1
Publisher: Springer Science and Business Media LLC
Date: 02-2023
Publisher: Elsevier BV
Date: 03-2022
Publisher: Springer Science and Business Media LLC
Date: 04-09-2018
DOI: 10.1057/S41599-018-0154-0
Abstract: Robust data are the base of effective gender ersity policy. Evidence shows that gender inequality is still pervasive in science, technology, engineering and mathematics (STEM). Coastal geoscience and engineering (CGE) encompasses professionals working on coastal processes, integrating expertise across physics, geomorphology, engineering, planning and management. The article presents novel results of gender inequality and experiences of gender bias in CGE, and proposes practical steps to address it. It analyses the gender representation in 9 societies, 25 journals, and 10 conferences in CGE and establishes that women represent 30% of the international CGE community, yet there is under-representation in prestige roles such as journal editorial board members (15% women) and conference organisers (18% women). The data show that female underrepresentation is less prominent when the path to prestige roles is clearly outlined and candidates can self-nominate or volunteer instead of the traditional invitation-only pathway. By analysing the views of 314 survey respondents (34% male, 65% female, and 1% ‘‘other’’), we show that 81% perceive the lack of female role models as a key hurdle for gender equity, and a significantly larger proportion of females (47%) felt held back in their careers due to their gender in comparison with males (9%). The lack of women in prestige roles and senior positions contributes to 81% of survey respondents perceiving the lack of female role models in CGE as a key hurdle for gender equality. While it is clear that having more women as role models is important, this is not enough to effect change. Here seven practical steps towards achieving gender equity in CGE are presented: (1) Advocate for more women in prestige roles (2) Promote high-achieving females (3) Create awareness of gender bias (4) Speak up (5) Get better support for return to work (6) Redefine success and, (7) Encourage more women to enter the discipline at a young age. Some of these steps can be successfully implemented immediately (steps 1–4), while others need institutional engagement and represent major societal overhauls. In any case, these seven practical steps require actions that can start immediately.
Publisher: Elsevier BV
Date: 08-2022
Publisher: World Scientific Publishing Company
Date: 04-2011
Publisher: Elsevier BV
Date: 12-2017
Publisher: Elsevier BV
Date: 05-2013
Publisher: The University of Queensland
Date: 2020
Publisher: American Geophysical Union (AGU)
Date: 09-2014
DOI: 10.1002/2014JF003106
Abstract: Coastal zone management requires the ability to predict coastline response to storms and longer‐term seasonal to interannual variability in regional wave climate. Shoreline models typically rely on extensive historical observations to derive site‐specific calibration. To circumvent the challenge that suitable data sets are rarely available, this contribution utilizes twelve 5+ year shoreline data sets from around the world to develop a generalized model for shoreline response. The shared dependency of model coefficients on local wave and sediment characteristics is investigated, enabling the model to be recast in terms of these more readily measurable quantities. Study sites range from microtidal to macrotidal coastlines, spanning moderate‐ to high‐energy beaches. The equilibrium model adopted here includes time varying terms describing both the magnitude and direction of shoreline response as a result of onshore/offshore sediment transport between the surf zone and the beach face. The model contains two coefficients linked to wave‐driven processes: (1) the response factor ( φ ) that describes the “memory” of a beach to antecedent conditions and (2) the rate parameter ( c ) that describes the efficiency with which sand is transported between the beach face and surf zone. Across all study sites these coefficients are shown to depend in a predictable manner on the dimensionless fall velocity ( Ω ), that in turn is a simple function of local wave conditions and sediment grain size. When tested on an unseen data set, the new equilibrium model with generalized forms of φ and c exhibited high skill (Brier Skills Score, BSS = 0.85).
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2009
Publisher: Springer Science and Business Media LLC
Date: 20-07-2017
DOI: 10.1038/S41598-017-05792-1
Abstract: Extratropical cyclones (ETCs) are the primary driver of large-scale episodic beach erosion along coastlines in temperate regions. However, key drivers of the magnitude and regional variability in rapid morphological changes caused by ETCs at the coast remain poorly understood. Here we analyze an unprecedented dataset of high-resolution regional-scale morphological response to an ETC that impacted southeast Australia, and evaluate the new observations within the context of an existing long-term coastal monitoring program. This ETC was characterized by moderate intensity (for this regional setting) deepwater wave heights, but an anomalous wave direction approximately 45 degrees more counter-clockwise than average. The magnitude of measured beach volume change was the largest in four decades at the long-term monitoring site and, at the regional scale, commensurate with that observed due to extreme North Atlantic hurricanes. Spatial variability in morphological response across the study region was predominantly controlled by alongshore gradients in storm wave energy flux and local coastline alignment relative to storm wave direction. We attribute the severity of coastal erosion observed due to this ETC primarily to its anomalous wave direction, and call for greater research on the impacts of changing storm wave directionality in addition to projected future changes in wave heights.
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier
Date: 2020
Publisher: Elsevier BV
Date: 09-2016
Publisher: Copernicus GmbH
Date: 22-10-2019
DOI: 10.5194/NHESS-19-2295-2019
Abstract: Abstract. After decades of study and significant data collection of time-varying swash on sandy beaches, there is no single deterministic prediction scheme for wave runup that eliminates prediction error – even bespoke, locally tuned predictors present scatter when compared to observations. Scatter in runup prediction is meaningful and can be used to create probabilistic predictions of runup for a given wave climate and beach slope. This contribution demonstrates this using a data-driven Gaussian process predictor a probabilistic machine-learning technique. The runup predictor is developed using 1 year of hourly wave runup data (8328 observations) collected by a fixed lidar at Narrabeen Beach, Sydney, Australia. The Gaussian process predictor accurately predicts hourly wave runup elevation when tested on unseen data with a root-mean-squared error of 0.18 m and bias of 0.02 m. The uncertainty estimates output from the probabilistic GP predictor are then used practically in a deterministic numerical model of coastal dune erosion, which relies on a parameterization of wave runup, to generate ensemble predictions. When applied to a dataset of dune erosion caused by a storm event that impacted Narrabeen Beach in 2011, the ensemble approach reproduced ∼85 % of the observed variability in dune erosion along the 3.5 km beach and provided clear uncertainty estimates around these predictions. This work demonstrates how data-driven methods can be used with traditional deterministic models to develop ensemble predictions that provide more information and greater forecasting skill when compared to a single model using a deterministic parameterization – an idea that could be applied more generally to other numerical models of geomorphic systems.
Publisher: MDPI AG
Date: 03-12-2020
DOI: 10.3390/RS12233953
Abstract: Nearshore morphology is a key driver in wave breaking and the resulting nearshore circulation, recreational safety, and nutrient dispersion. Morphology persists within the nearshore in specific shapes that can be classified into equilibrium states. Equilibrium states convey qualitative information about bathymetry and relevant physical processes. While nearshore bathymetry is a challenge to collect, much information about the underlying bathymetry can be gained from remote sensing of the surfzone. This study presents a new method to automatically classify beach state from Argus daytimexposure imagery using a machine learning technique called convolutional neural networks (CNNs). The CNN processed imagery from two locations: Narrabeen, New South Wales, Australia and Duck, North Carolina, USA. Three different CNN models are examined, one trained at Narrabeen, one at Duck, and one trained at both locations. Each model was tested at the location where it was trained in a self-test, and the single-beach models were tested at the location where it was not trained in a transfer-test. For the self-tests, skill (as measured by the F-score) was comparable to expert agreement (CNN F-values at Duck = 0.80 and Narrabeen = 0.59). For the transfer-tests, the CNN model skill was reduced by 24–48%, suggesting the algorithm requires additional local data to improve transferability performance. Transferability tests showed that comparable F-scores (within 10%) to the self-trained cases can be achieved at both locations when at least 25% of the training data is from each site. This suggests that if applied to additional locations, a CNN model trained at one location may be skillful at new sites with limited new imagery data needed. Finally, a CNN visualization technique (Guided-Grad-CAM) confirmed that the CNN determined classifications using image regions (e.g., incised rip channels, terraces) that were consistent with beach state labelling rules.
Publisher: American Geophysical Union (AGU)
Date: 03-2019
DOI: 10.1029/2018JF004895
Publisher: Elsevier BV
Date: 10-2019
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 11-2012
Publisher: MDPI AG
Date: 24-09-2021
DOI: 10.3390/JMSE9101053
Abstract: There is an increasing interest in the broad-scale implementation of coastal erosion early warning systems (EWS) with the goal of enhancing community preparedness to extreme coastal storm wave events. These emerging systems typically rely on process-based models to predict the storm-induced morphological change. A key challenge with incorporating these models in EWSs is the need for up-to-date nearshore and surf zone bathymetry data, which is difficult to measure routinely, but potentially important for accurate erosion forecasting. This study evaluates the degree to which up-to-date bathymetry is required for accurate coastal erosion predictions using the morphodynamic model XBeach and, subsequently, whether a range of “representative” and/or “synthetic” bathymetries can be used for the bottom boundary, when a survey of the immediate pre-storm bathymetry is not available. Twelve storm events at two contrasting sites were modelled using six different bathymetry scenarios, including the expected “best case” bathymetry surveyed immediately pre-storm. These results indicate that alternative bathymetries can be used to obtain sub-aerial erosion predictions that are similar (and in some cases better) than those resulting from the use of an immediately pre-storm surveyed bathymetry, provided that rigorous model calibration is undertaken prior. This generalized finding is attributed to specific parametrizations in the XBeach model structure that are optimized during the calibration process to match the particular bottom boundary condition used. This study provides practical guidance for the selection of suitable nearshore bathymetry for use in operational coastal erosion EWSs.
Publisher: Elsevier BV
Date: 08-2021
Publisher: Wiley
Date: 17-01-2017
DOI: 10.1002/ESP.4088
Publisher: Elsevier BV
Date: 07-2022
Publisher: California Digital Library (CDL)
Date: 28-07-2023
DOI: 10.31223/X5W66T
Abstract: Almar and colleagues (2023) are correct in stating that, “understanding and predicting shoreline evolution is of great importance for coastal management.” Amongst the different timescales of shoreline change, the interannual and decadal timescales are of particular interest to coastal scientists as they reflect the integrated system response to the Earth’s climate and its natural modes of variability. Therefore, establishing the links between shoreline change and climate variability at the global scale would be a major achievement. However, we find that the work of Almar et al.1 does not achieve this goal because: (i) the satellite-based method does not meet the current standards of practice and produces inaccurate results, (ii) the spatial coverage of the shoreline dataset is not adequate for a global analysis, (iii) the relevance of the statistical analyses between the shoreline data and independent variables is questionable, and (iv) the findings do not capture physical patterns of shorelines developed from field-based observations.
Start Date: 2017
End Date: 2019
Funder: NSW Environmental Trust Environmental Research Program
View Funded ActivityStart Date: 2015
End Date: 2017
Funder: Australian Research Council
View Funded ActivityStart Date: 2017
End Date: 2019
Funder: Australian Research Council
View Funded ActivityStart Date: 02-2015
End Date: 06-2019
Amount: $423,200.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2023
End Date: 12-2026
Amount: $932,168.00
Funder: Australian Research Council
View Funded ActivityStart Date: 10-2018
End Date: 06-2024
Amount: $505,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 10-2020
End Date: 09-2025
Amount: $370,000.00
Funder: Australian Research Council
View Funded Activity