ORCID Profile
0000-0001-9884-6917
Current Organisation
University of New South Wales
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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.
Maritime Engineering | Natural Hazards | Physical Geography and Environmental Geoscience | Maritime Engineering not elsewhere classified | Physical Oceanography | Civil Engineering not elsewhere classified | Ocean Engineering | Geomorphology | Oceanography Not Elsewhere Classified | Geology | Control Systems, Robotics and Automation | Environmental Engineering Modelling | Oceanography | Marine Geoscience | Physical Oceanography | Human Geography not elsewhere classified | Fluidisation and Fluid Mechanics | Human Geography | Environmental Monitoring | Interdisciplinary 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 | Land and water management | Physical and chemical conditions | Ecosystem Assessment and Management of Coastal and Estuarine Environments | Civil Construction Design | Environmentally Sustainable Construction not elsewhere classified | Wave Energy | Climate change |
Publisher: Elsevier BV
Date: 05-2010
Publisher: Elsevier BV
Date: 10-2012
Publisher: Elsevier BV
Date: 2006
Publisher: Elsevier BV
Date: 05-2012
Publisher: Elsevier BV
Date: 05-2012
Publisher: Elsevier BV
Date: 07-2017
Publisher: Elsevier BV
Date: 05-2012
Publisher: American Geophysical Union (AGU)
Date: 06-2004
DOI: 10.1029/2003JC002214
Publisher: Springer Science and Business Media LLC
Date: 15-03-2021
DOI: 10.1038/S41597-021-00874-2
Abstract: A Correction to this paper has been published: 0.1038/s41597-021-00874-2.
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: 09-2009
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41597-020-0496-5
Abstract: Real-world observational datasets that record and quantify pressure-stressor-response linkages between effluent discharges and natural aquatic systems are rare. With global wastewater volumes increasing at unprecedented rates, it is urgent that the present dataset is available to provide the necessary information about microbial community structure and functioning. Field studies were performed at two time-points in the Austral summer. Single-species and microbial community whole effluent toxicity (WET) testing was performed at a complete range of effluent concentrations and two salinities, with accompanying environmental data to provide new insights into nutrient and organic matter cycling, and to identify ecotoxicological tipping points. The two salinity regimes were chosen to investigate future scenarios based on a predicted salinity increase at the study site, typical of coastal regions with rising sea levels globally. Flow cytometry, licon sequencing of 16S and 18S rRNA genes and micro-fluidic quantitative polymerase-chain reactions (MFQPCR) were used to determine chlorophyll-a and total bacterial cell numbers and size, as well as taxonomic and functional ersity of pelagic microbial communities. This strong pilot dataset could be replicated in other regions globally and would be of high value to scientists and engineers to support the next advances in microbial ecotoxicology, environmental biomonitoring and estuarine water quality modelling.
Publisher: Wiley
Date: 23-07-2020
Publisher: Wiley
Date: 23-04-2020
Publisher: Elsevier BV
Date: 08-2010
Publisher: Springer Science and Business Media LLC
Date: 09-11-2016
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: SPIE-Intl Soc Optical Eng
Date: 03-03-2017
Publisher: Elsevier BV
Date: 07-2013
Publisher: Elsevier BV
Date: 05-2007
DOI: 10.1016/J.NEUNET.2007.04.007
Abstract: The temporal evolution of nearshore sandbars (alongshore ridges of sand fringing coasts in water depths less than 10 m and of paramount importance for coastal safety) is commonly predicted using process-based models. These models are autoregressive and require offshore wave characteristics as input, properties that find their neural network equivalent in the NARX (Nonlinear AutoRegressive model with eXogenous input) architecture. Earlier literature results suggest that the evolution of sandbars depends nonlinearly on the wave forcing and that the sandbar position at a specific moment contains 'memory', that is, time-series of sandbar positions show dependencies spanning several days. Using observations of an outer sandbar collected daily for over seven years at the double-barred Surfers Paradise, Gold Coast, Australia several data-driven models are compared. Nonlinear and linear models as well as recurrent and nonrecurrent parameter estimation methods are applied to investigate the claims about nonlinear and long-term dependencies. We find a small performance increase for long-term predictions (>40 days) with nonlinear models, indicating that nonlinear effects expose themselves for larger prediction horizons, and no significant difference between nonrecurrent and recurrent methods meaning that the effects of dependencies spanning several days are of no importance.
Publisher: Elsevier BV
Date: 07-2021
Publisher: Coastal Education and Research Foundation
Date: 05-2007
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: Elsevier BV
Date: 2011
Publisher: Elsevier BV
Date: 04-2019
Publisher: Copernicus GmbH
Date: 25-03-2022
DOI: 10.5194/ESSD-14-1345-2022
Abstract: Abstract. Sandy beaches are unique environments composed of unconsolidated sediments that are constantly reshaped by the action of waves, tides, currents, and winds. The most seaward region of the dry beach, referred to as the beach face, is the primary interface between land and ocean and is of fundamental importance to coastal processes, including the dissipation and reflection of wave energy at the coast and the exchange of sediment between the land and sea. The slope of the beach face is a critical parameter in coastal geomorphology and coastal engineering, as it is needed to calculate the total elevation and excursion of wave run-up at the shoreline. However, datasets of the beach-face slopes along most of the world's coastlines remain unavailable. This study presents a new dataset of beach-face slopes for the Australian coastline derived from a novel remote sensing technique. The dataset covers 13 200 km of sandy coast and provides an estimate of the beach-face slope every 100 m alongshore accompanied by an easy-to-apply measure of the confidence of each slope estimate. The dataset offers a unique view of large-scale spatial variability in the beach-face slope and addresses the growing need for this information to predict coastal hazards around Australia. The beach-face slope dataset and relevant metadata are available at 0.5281/zenodo.5606216 (Vos et al., 2021).
Publisher: Elsevier BV
Date: 02-2007
Publisher: Elsevier BV
Date: 03-2017
Publisher: Copernicus GmbH
Date: 07-06-2016
DOI: 10.5194/ISPRS-ANNALS-III-7-67-2016
Abstract: Abstract. This paper presents the comparisons of three soft classification methods and three sub-pixel mapping methods for the classification of coastal areas at sub-pixel level. Specifically, SPOT-7 multispectral images covering the coastal area of Perth are selected as the experiment dataset. For the soft classification, linear spectral unmixing model, supervised fully-fuzzy classification method and the support vector machine are applied to generate the fraction map. Then for the sub-pixel mapping, the sub-pixel ixel attraction model, pixel swapping and wavelets method are compared. Besides, the influence of the correct fraction constraint is explored. Moreover, a post-processing step is implemented according to the known spatial knowledge of coastal areas. The accuracy assessment of the fraction values indicates that support vector machine generates the most accurate fraction result. For sub-pixel mapping, wavelets method outperforms the other two methods with overall classification accuracy of 91.79% and Kappa coefficient of 0.875 after the post-processing step and it also performs best for waterline extraction with mean distance of 0.71m to the reference waterline. In this experiment, the use of correct fraction constraint decreases the classification accuracy of sub-pixel mapping methods and waterline extraction. Finally, the post-processing step improves the accuracy of sub-pixel mapping methods, especially for those with correct coefficient constraint. The most significant improvement of overall accuracy is as much as 4% for the sub-pixel ixel attraction model with correct coefficient constraint.
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: Elsevier BV
Date: 05-2006
Publisher: Coastal Education and Research Foundation
Date: 05-2016
Publisher: American Geophysical Union (AGU)
Date: 23-12-2011
DOI: 10.1029/2011JF001989
Publisher: Elsevier BV
Date: 07-2014
Publisher: Elsevier BV
Date: 07-2016
Publisher: American Society of Civil Engineers (ASCE)
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 02-2023
Publisher: Elsevier BV
Date: 09-2009
Publisher: American Society of Civil Engineers
Date: 23-03-2000
Publisher: Elsevier BV
Date: 12-2017
Publisher: Wiley
Date: 1995
Publisher: Wiley
Date: 2009
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: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 08-2016
Publisher: Springer Science and Business Media LLC
Date: 20-01-2021
DOI: 10.1038/S41597-021-00805-1
Abstract: High quality laboratory measurements of nearshore waves and morphology change at, or near prototype-scale are essential to support new understanding of coastal processes and enable the development and validation of predictive models. The DynaRev experiment was completed at the GWK large wave flume over 8 weeks during 2017 to investigate the response of a sandy beach to water level rise and varying wave conditions with and without a dynamic cobble berm revetment, as well as the resilience of the revetment itself. A large array of instrumentation was used throughout the experiment to capture: (1) wave transformation from intermediate water depths to the runup limit at high spatio-temporal resolution, (2) beach profile change including wave-by-wave changes in the swash zone, (3) detailed hydro and morphodynamic measurements around a developing and a translating sandbar.
Publisher: Coastal Education and Research Foundation
Date: 03-03-2016
DOI: 10.2112/SI75-084.1
Publisher: Elsevier BV
Date: 08-2021
Publisher: American Society of Civil Engineers
Date: 23-03-2001
Publisher: Elsevier BV
Date: 10-2003
Publisher: American Geophysical Union (AGU)
Date: 07-2007
DOI: 10.1029/2006JC003799
Publisher: Elsevier BV
Date: 06-2010
Publisher: Elsevier BV
Date: 09-2009
Publisher: Wiley
Date: 17-01-2017
DOI: 10.1002/ESP.4088
Publisher: Elsevier BV
Date: 09-2014
Publisher: American Society of Civil Engineers
Date: 23-03-2001
Publisher: Elsevier BV
Date: 08-2013
Publisher: Elsevier BV
Date: 2001
Publisher: Coastal Education and Research Foundation
Date: 07-2005
DOI: 10.2112/03-0071.1
Publisher: Elsevier BV
Date: 06-2018
Publisher: IEEE
Date: 07-2013
Publisher: Coastal Education and Research Foundation
Date: 02-11-2014
DOI: 10.2112/SI72-016.1
Publisher: University of Toronto Press Inc. (UTPress)
Date: 06-2007
Abstract: Remote sensors are widely used in coastal morphodynamic research, and users are often confronted with abundant data sensors generated by these sensors. These data, if properly explored, can be used to study and manage many coastal features and processes that are not well understood. As an ex le, we present the exploration of rip channels. Coastal data sets are currently explored using animated image sequences. Users are dissatisfied, however, because exploration remains largely a subjective and time-consuming process. In particular, detecting the presence and evolution of relatively small, highly dynamic rip channels has proved difficult. This article examines how the visual exploration of rip objects can be improved. We first look at the factors limiting exploratory use of conventional animations for rip studies and argue that two main factors are responsible: data complexity and animation design based on images that mimic reality. Then we present an ex le of how the current approach to visualizing time series of coastal images can be improved by computational methods, particularly by feature tracking. Next, we describe a visualization prototype and discuss the representational, data-mining, and interactive functionality resulting from such a combination in an environment dedicated to the exploration of dynamic objects.
Publisher: Geological Society of London
Date: 2012
DOI: 10.1144/SP361.10
Publisher: The Oceanography Society
Date: 09-2017
Publisher: Elsevier BV
Date: 07-2009
Publisher: Elsevier BV
Date: 03-2016
Publisher: Springer Science and Business Media LLC
Date: 27-09-2007
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: Coastal Education and Research Foundation
Date: 28-04-2014
DOI: 10.2112/SI-120.1
Publisher: Elsevier BV
Date: 10-2010
Publisher: Copernicus GmbH
Date: 18-11-2021
Abstract: Abstract. Sandy beaches are unique environments composed of unconsolidated sediments that are constantly reshaped by the action of waves, tides, currents, and winds. The most seaward region of the dry beach, referred to as the beach face, is the primary interface between land and ocean and is of fundamental importance to coastal processes, including the dissipation and reflection of wave energy at the coast, and the exchange of sediment between the land and sea. The slope of the beach-face is a critical parameter in coastal geomorphology and coastal engineering, necessary to calculate the total elevation and excursion of wave run-up at the shoreline. However, datasets of the beach-face slope remain unavailable along most of the world’s coastlines. This study presents a new dataset of beach-face slopes for the Australian coastline derived from a novel remote sensing technique. The dataset covers 13,200 km of sandy coast and provides an estimate of the beach-face slope at every 100 m alongshore, accompanied by an easy to apply measure of the confidence of each slope estimate. The dataset offers a unique view of large-scale spatial variability in beach-face slope and addresses the growing need for this information to predict coastal hazards around Australia. The beach-face slope dataset and relevant metadata are available at 0.5281/zenodo.5606217 (Vos et al., 2021)
Publisher: Elsevier BV
Date: 12-2008
Publisher: Informa UK Limited
Date: 2014
Publisher: Coastal Education and Research Foundation
Date: 2006
DOI: 10.2112/05A-0004.1
Publisher: Elsevier BV
Date: 10-1998
Publisher: American Society of Civil Engineers (ASCE)
Date: 2014
Publisher: Elsevier BV
Date: 09-2018
Publisher: Copernicus GmbH
Date: 10-2018
Abstract: Abstract. How storm events contribute to long-term shoreline change over decades to centuries remains an open question in coastal research. Sand and gravel coasts exhibit remarkable resilience to event-driven disturbances, and, in settings where sea level is rising, shorelines retain almost no detailed information about their own past positions. Here, we use a detailed, multi-decadal observational record of shoreline position to demonstrate quantitative indications of morphodynamic turbulence – signal shredding – in a sandy beach system. We find that, much like other dynamic sedimentary systems, processes of sediment transport that affect shoreline position at relatively short time-scales obscure or erase physical evidence of external forcing. This suggests that large forcing events like major coastal storms, even when their effects are recorded, may convey less about the dynamics of long-term shoreline change – and vice versa – than coastal researchers might wish.
Publisher: Wiley
Date: 12-1994
DOI: 10.1111/J.1439-0485.1994.TB00053.X
Abstract: Abstract. The interstitial system of sandy beaches is lacunar and has its dimensions defined by the sand granulometry. It can be described by features such as pore size, porosity, permeability, and water content. The most important process occurring in this system, water filtration, is driven by inputs of freshwater from groundwater discharge, and inputs of seawater by tides, wave run‐up, and subtidal wave pumping. Reflective beaches have seawater input effected mainly by waves they filter large water volumes with short residence times. Dissipative beaches display the opposite patterns, slowly filtering small volumes input by tides. Flow patterns and their effects on interstitial climate are described. The water table of the beach moves in response to groundwater discharge, tides, and waves and influences erosion/accretion processes on the beach face: a high water table promotes erosion. A series of moisture zones can be recognised from the dry surface sand at upper tide levels, to permanently saturated sand below the low tide water table, namely: a stratum of dry sand, a stratum of retention, a stratum of resurgence, and stratum of saturation. Interstitial chemistry is briefly described in terms of salinity changes, organic loads, oxygen content, and nutrient cycling. It is concluded that the interstitial environment of sandy beaches spans a continuum between physically and chemically controlled extremes: the former condition occurs on coarse sand reflective beaches, which experience low organic inputs and high filtration rates of large water volumes — resulting in powerful hydrodynamic forces the latter occurs on dissipative beaches of fine sand, which are subject to high organic inputs and low filtration volumes — resulting in stagnation and steep vertical chemical gradients. Many intermediate situations occur and these are more favourable to interstitial life than either of the extremes.
Publisher: Wiley
Date: 26-10-2020
Publisher: World Scientific Publishing Company
Date: 03-2003
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: Elsevier BV
Date: 10-2016
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: 08-2011
Publisher: Elsevier BV
Date: 03-2013
Publisher: Elsevier BV
Date: 08-2011
Publisher: Elsevier BV
Date: 2008
Publisher: Elsevier BV
Date: 11-2010
Publisher: Copernicus GmbH
Date: 18-11-2021
Publisher: American Society of Civil Engineers (ASCE)
Date: 05-2006
Publisher: Wiley
Date: 12-06-2009
DOI: 10.1002/JOC.1962
Publisher: Elsevier BV
Date: 11-2009
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: Copernicus GmbH
Date: 18-01-2019
Abstract: Abstract. How storm events contribute to long-term shoreline change over decades to centuries remains an open question in coastal research. Sand and gravel coasts exhibit remarkable resilience to event-driven disturbances, and, in settings where sea level is rising, shorelines retain almost no detailed information about their own past positions. Here, we use a high-frequency, multi-decadal observational record of shoreline position to demonstrate quantitative indications of morphodynamic turbulence – “signal shredding” – in a sandy beach system. We find that, much as in other dynamic sedimentary systems, processes of sediment transport that affect shoreline position at relatively short timescales may obscure or erase evidence of external forcing. This suggests that the physical effects of annual (or intra-annual) forcing events, including major storms, may convey less about the dynamics of long-term shoreline change – and vice versa – than coastal researchers might wish.
Publisher: American Geophysical Union (AGU)
Date: 24-02-2009
DOI: 10.1029/2007JF000888
Publisher: Springer Science and Business Media LLC
Date: 21-09-2015
DOI: 10.1038/NGEO2539
Publisher: American Geophysical Union (AGU)
Date: 09-1598
DOI: 10.1002/2014JF003390
Publisher: Coastal Education and Research Foundation
Date: 03-03-2016
DOI: 10.2112/SI75-078.1
Publisher: Elsevier BV
Date: 05-2013
Publisher: Elsevier BV
Date: 06-2007
Publisher: Elsevier BV
Date: 12-1993
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: American Geophysical Union (AGU)
Date: 03-2019
DOI: 10.1029/2018JF004895
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 06-1995
Publisher: Elsevier BV
Date: 07-2022
Publisher: Elsevier BV
Date: 06-2018
Publisher: Elsevier BV
Date: 07-2016
Publisher: Springer Science and Business Media LLC
Date: 25-12-2014
Start Date: 03-2011
End Date: 03-2014
Amount: $340,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2007
End Date: 12-2010
Amount: $304,000.00
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: 01-2011
End Date: 03-2015
Amount: $210,000.00
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 ActivityStart Date: 07-2021
End Date: 06-2024
Amount: $427,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2011
End Date: 07-2014
Amount: $292,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2014
End Date: 12-2017
Amount: $465,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2004
End Date: 07-2008
Amount: $155,000.00
Funder: Australian Research Council
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