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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 https://doi.org/10.5281/zenodo.5606216 (Vos et al., 2021). [ABSTRACT FROM AUTHOR]

The majority of drowning deaths on Australian beaches occur significant distances away from lifeguard services. This study uses results of 459 surveys of beachgoers at five beaches unpatrolled by lifeguards in New South Wales, Australia, to improve understanding of who visits these beaches and why, and to identify risk factors associated with their beach safety knowledge and behaviour. Many unpatrolled beach users were infrequent beachgoers (64.9 %) with poor rip current hazard identification skills, who did not observe safety signage that was present, and yet intended to enter the water to swim (85.6 %) despite being aware that no lifeguards were present. The survey found that the main reasons why beachgoers visited unpatrolled beaches were because they were conveniently close to their holiday accommodation, or they represented a quieter location away from crowds. Future beach safety interventions in Australia need to extend beyond the standard "swim between the flags" message in recognition that many Australian beaches will remain unpatrolled, yet still frequented, for the foreseeable future. Future beach safety interventions for unpatrolled beaches should be tailored towards the varied demographic groups of beach users. [ABSTRACT FROM AUTHOR]

The majority of drowning deaths on Australian beaches occur significant distances away from lifeguard services. This study uses results of 459 surveys of beachgoers at five beaches unpatrolled by lifeguards in New South Wales, Australia to improve understanding of who visits these beaches and why, and to identify risk factors associated with their beach safety knowledge and behaviour. Many unpatrolled beach users were infrequent beachgoers and weak swimmers, with poor rip current hazard identification skills, who did not observe safety signage that was present, and yet intended to enter the water to swim despite being aware that no lifeguards were present. The survey found that the main reasons beachgoers visited unpatrolled beaches were because they were conveniently close to their holiday accommodation, or they represented a quieter location away from crowds. Future beach safety interventions in Australia need to extend beyond the standard 'swim between the flags' message in recognition that people will always frequent unpatrolled beaches. Future beach safety interventions for unpatrolled beaches should be tailored towards the varied types of demographic beach users, such as domestic tourist families, males, and day visitors attracted by social media. [ABSTRACT FROM AUTHOR]

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 https://doi.org/10.5281/zenodo.5606217 (Vos et al., 2021). [ABSTRACT FROM AUTHOR]

Shorelines respond to a number of "drivers" operating on a variety of time‐scales. For some time‐scales (e.g., seasonal), the driver‐shoreline relationship is often evident; however, at longer time‐scales (e.g., multiannual), the shoreline changes may be superimposed on changes at shorter time‐scales and thus are difficult to identify. Here, we predict shoreline evolution from storm events to decadal time‐scales, using a novel approach based on the Complete Ensemble Empirical Mode Decomposition. This approach identifies and links the primary time‐scales in the model drivers (large‐scale sea level pressure [SLP] and/or waves) with the same time‐scales in the shoreline position. The multiscale approach reproduced shoreline changes at two beaches more skillfully than a common shoreline model when SLP and wave information were used in combination. In addition, the analysis can be applied to climate indices, providing the opportunity to link longer time‐scales with climate patterns (e.g., El Niño Southern Oscillation). Plain Language Summary: Beaches are changing constantly, advancing or retreating depending for instance, on the climate and ocean conditions. Beach retreat and advance may occur in cycles (seasonally, annually, or over several decades) or because of particular events such as storms. All these changes are superimposed and difficult to disentangle. Therefore, the same beach can look completely different in summer or winter, and the changes are not the same year after year. Therefore, predicting the beach state over the following months, years, or decades is a daunting task. Here, we introduce a new approach to the prediction of shoreline changes and test it at two beaches (one in New Zealand and the other in Australia). The new approach relates changes in shoreline position with "drivers" (waves and atmospheric patterns) decomposed into time‐scales (e.g., seasonal, annual, and bi‐annual) and uses these connections to predict shoreline changes. Key Points: A novel modeling approach to shoreline prediction is presented and compared with an established model at two study sitesA decomposition of different time‐scales (from storm to climate anomalies) in shoreline and drivers is used to predict shoreline changeThe addition of sea level pressure information to wave bulk parameters as model inputs improves shoreline predictions [ABSTRACT FROM AUTHOR]

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 (R2 = 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. Plain Language Summary: How steep a beach is can dictate the way the beach interacts with the incoming ocean waves and therefore is of paramount importance for coastal scientists and engineers, coastal flood modelers, and swim safety officers. However, despite its importance, it is impractical to obtain reliable estimates of the "typical" beach‐face slope along large lengths of sandy coastlines (hundreds to thousands of km) because of the logistics that would be necessary to visit many sites repeatedly to obtain these measurements. This letter describes a new technique to estimate the beach‐face slope in the absence of field observations, relying instead on long‐term publicly available satellite observations and a global tide model. This technique is then applied to thousands of beaches along the coastlines of eastern Australia and California in the United States. Key Points: A novel remote sensing technique to estimate beach‐face slopes from satellite imagery and modeled tides is presentedTime series of shoreline change are transformed into frequency domain to find the slope that minimizes high‐frequency tidal fluctuationsValidation against in situ data shows high accuracy across sites ranging in grain size, tidal range, and wave climate [ABSTRACT FROM AUTHOR]

Shoreline variability at embayed beaches can be characterized into modes where either longshore or cross-shore sediment transport processes dominate the overall shoreline response, or there is a mixed combination of the two. To-date it has been assumed that the relative dominance of these differing modes of longshore and/or cross-shore shoreline behaviour is stationary in time. This concept is tested using a unique 43-year dataset of shoreline positions at Narrabeen-Collaroy beach (southeast Australia) and a rolling five-year window Empirical Orthogonal Function analysis, revealing the new observation of a distinct interannual variability in the dominant cross-shore and longshore modes of shoreline behaviour at this site. The dominant mode of shoreline behaviour was found to range from time periods when the cross-shore mode (referred to as the cross-shore coherent mode) comprised as much as 74 % of the overall shoreline variability, contrasting to other time periods when the alongshore mode of shoreline behaviour (longshore coherent mode) was more dominant, accounting for up to 62 % of the observed shoreline variability. Wave forcing correlation analysis suggests that these modes are controlled by varying influences of wave intensity and wave direction at interannual time scales. Consistent with previous research at this same embayment, the cross-shore coherent mode of shoreline variability appears to be controlled primarily by wave height/intensity, with stronger controls (i.e., higher correlation) when this cross-shore mode was overwhelmingly dominant. In contrast, the contribution of the longshore coherent mode appears to be controlled primarily by wave direction, but also at certain unique times in the time series by wave intensity. Analysis using available topographic and bathymetric data suggests that the observed switch in longshore versus cross-shore dominance may be triggered by extreme storm events, which cause significant and near 'instantaneous' redistribution of sediment across the entire shoreface and beach face. These results highlight the importance of considering a non-stationary shoreline behaviour at embayed beaches and the association of differing modes of dominant shoreline behaviour with interannual wave climate variability. Given observed interannual variability in deep water wave climates more broadly, it is likely that the dominant modes of shoreline variability may also occur at other embayed beaches and should be considered for numerical modelling (and prediction) of future shoreline behaviour. • A 43-year dataset of shoreline position at a wave-dominated embayment is analysed • A rolling five-year window EOF analysis reveals interannual variability in shoreline behaviour • Dominant cross-shore and longshore modes of shoreline behaviour alternate in time at interannual time scales • Modes of shoreline behaviour are controlled by different influences of wave intensity and direction parameters • Implications for adopting a non-stationary approach to coastal shoreline change numerical modelling and future predictions [ABSTRACT FROM AUTHOR]

A desired outcome in the construction of a detached emerged breakwater is the formation of an accretionary salient in its lee to augment the beach, improve beach amenity and provide an additional buffer from storm waves. The extent to which this salient forms and its morphology are strongly controlled by the breakwater geometry with respect to the original shoreline, sediment availability, and local wave climate. The purpose of this paper is to identify how breakwater geometry and orientation of gaps between individual breakwaters alter the direction of waves entering the gaps and change the asymmetry of the salients. Four distinct breakwater sites along the Emilia-Romagna coastline in Northern Italy were chosen for a detailed field and desktop study comprising three-dimensional topographic and bathymetric surveys, sediment sampling, LiDAR flights and historical shoreline mapping. The orientations of the shorelines at these four sites range over 43°, resulting in different exposures to the dominant waves. The oblique orientations of the gaps between individual breakwater segments at three of the four sites effectively create a “gap window” between breakwaters favoring the exposure of short-period waves from the north and diminishing the effect of longer waves from the dominant east. Salients can be symmetrical despite an acute angle of approach of the dominant deep water waves where refraction is enhanced by offshore topography and breakwaters are parallel to the shore. Waves approaching normal to the gap window undergo less diffraction due to their shorter length relative to the gap window width and undergo less attenuation by breaking and bottom friction if they are locally generated and have short periods. Greater breaking-wave energy on the gap-facing slope of the salient can create shoreline and morphological asymmetry. The implication is that breakwater orientations can be designed or altered to selectively dampen or facilitate wave energy to enhance sediment transport in a desired direction, provided that breakwaters are not too far offshore and sediment availability is not restricted to affect salient formation. Adjusting exposure via gap orientation can create morphologies that cannot be inferred from process-dominant conditions. [ABSTRACT FROM AUTHOR]

CoastSnap is a low-cost community beach monitoring program that turns everyday smartphones into devices to measure coastal response to storms, sea-level rise, human modifications and other factors. Underpinning CoastSnap is a stainless-steel smartphone cradle that is installed overlooking a beach in a location easily accessible to the public. Using the cradle for image positioning, passers-by simply take a photo of the coast and upload it to a centralized database, which in turn provides a crowd-sourced record of coastline change over time. Behind this simple idea are advanced image processing algorithms that then enable the shoreline position (and other coastal features) to be mapped from the community snapshots in a scientifically rigorous manner. First established in Sydney, Australia in 2017, the network of CoastSnap stations has grown rapidly over the past five years to now encompass 200 monitoring locations in 21 countries. Analysis of the 44 Australian stations managed by the Authors indicates strong community participation, with over 10,000 images and 4000 community participants to date and an image submission frequency ranging from approximately weekly to daily (average = 2.6 images/station/week). Example practical applications of CoastSnap include: as a tool to monitor high-frequency shoreline change and coastal inlet dynamics; to support conservation efforts on protected coastlines; and to directly inform the timing of dredging and beach nourishment activities. This paper describes the background and evolution of the project and discusses its successes, challenges as well as future directions. • CoastSnap demonstrates how community smartphone images can accurately monitor coastal change. • Global CoastSnap network now comprises 200 stations in 21 countries. • Participation statistics in Australia indicate strong community uptake (weekly to sub-daily imagery). [ABSTRACT FROM AUTHOR]

Abstract: Coastal monitoring across a broad range of time-scales was recognized in the latest report by the Intergovernmental Panel on Climate Change as key to better understanding the likely impacts of climate change at the coast. A unique and historic coastal monitoring program undertaken at the Collaroy–Narrabeen embayment in south-eastern Australia comprises: 1) 30years of monthly conventional (Emery method) surveys of five cross-shore profile lines; 2) three years of monthly three-dimensional surveys of the entire embayment using RTK-GPS mounted to an all-terrain vehicle (ATV); and 3) four years of hourly shoreline measurements using coastal imaging technology (ARGUS). This study evaluates the strengths and limitations of conventional, RTK-GPS and image-derived surveys for coastal monitoring at daily to decadal coastal time-scales. High-accuracy RTK-GPS was used to first assess the accuracy of the conventional and image-derived survey methods. The magnitude of daily to decadal coastal variability was then characterized by calculating the temporal semivariogram of the integrated survey dataset. With both measurement errors and the degree of beach variability quantified, the corresponding signal-to-noise ratios (SNR) of each survey method at different time-scales were determined. The value of the simple and cost-effective Emery method was verified by this analysis, with measurement error significantly smaller than the degree of overall beach variability (SNR=8.4). The accuracy, speed and efficiency of ATV-mounted RTK-GPS meanwhile make it suitable for three-dimensional beach surveys. Image-derived surveys were found to be an effective means of remotely measuring the considerable degree of beach variability identified at time-scales of less than one month. These measurements however become indistinguishable from survey noise (i.e. SNR≤1) when considering typical weekly (or smaller) variations at large distances from the cameras. [ABSTRACT FROM AUTHOR]

National weather forecasting agencies routinely issue a range of hazard warnings. But to our knowledge, along sandy coastlines where storm waves and storm surge can result in widespread but location-specific beach erosion and beachfront flooding, no national-scale early warning service for these hazards is presently operational. This paper outlines the scientific basis and implementation of a new framework for large area coastal storm hazards forecasting, currently being tested along the southwest (Indian Ocean) and southeast (Pacific Ocean) coasts of Australia. The system provides 7-day rolling predictions of localized beach erosion and/or coastal flooding linked to forecasted extreme weather events. Coastal setting influences the nature and occurrence of these hazards, with sandy beaches along wave-dominated coasts more prone to erosion and at surge-dominated coasts to flooding. An existing nearshore water-level forecasting system and a new inshore wave modeling capability are used to forecast beach erosion and coastal flooding at every 100 m along the shore. At the regional scale O(100–1 000 km of coastline), a threshold-based decision tree model categorises the predicted extent, location, and severity of erosion and flooding. At a more local scale O(100–1 000 m), physics-based modeling using XBeach focuses on vulnerable or high-value locations, providing specific storm hazard indicators tailored to local needs. This two-tier approach is feasible for national implementation due to the reduced computational effort, limiting intensive modeling to pre-identified critical locations. Delft-FEWS manages the data and modeling workflow, ensuring scalability and compatibility with existing forecast infrastructure. Initial evaluations of the system are promising, with a detailed 2-year evaluation in progress. Future enhancements could include the use of satellite imagery for real-time beach width and dune topography assimilation and exploring alternative modeling approaches to further improve forecast accuracy. • A framework for coastal storm hazards early warning over very large areas is developed. • The severity of hazards is predicted every 100 m alongshore by parametric modeling. • Site-specific storm hazard indicators at vulnerable sites are predicted by XBeach. • 7-day rolling forecasts of storm hazards are communicated via a web portal. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: The objectives of this study are to examine the response of a dune and beach system on the Adriatic coastline in northern Italy to the arrival of storms, compare it with seasonal (months) and medium-term (3-year) morphodynamic change, and evaluate results predicted by the numerical model XBeach. The studied coastline stretches 4km from the Bevano River mouth to the north of the site to the township of Lido di Classe to the south, where the beach is protected by coastal structures. Fieldwork consisted of topographic profile surveys using RTK-DGPS technology (7 times over an approx. 3-year period). 103 samples of surface sediment were collected along 20 of the cross-shore profiles at 6 distinct cross-shore positions, selected on the basis of morphological beach characteristics. Data analyses of dune and beach slopes enabled the study area to be divided into 6 separate morphological zones using the spatial (longshore and cross-shore) variation of morphologies located on the backshore and intertidal beach observed in a preliminary survey of the area. Other criteria were a spatial consistency in beach slopes and/or presence/absence of intertidal morphologies identified in the aerial photographs and Lidar data. The swash zone slope did not show any significant variability for the entire area. A weak seasonal trend in the variability of the mean foredune slope was observed, with steeper slopes typically during winter and flatter slopes during summer. Analysis of grain size revealed that the beach sediment is well-sorted fine sand tending to medium, with a decreasing trend in size from the Bevano River mouth southwards towards Lido di Classe. According to the Masselink and Short (1993) classification, the natural part of the study site has an Intermediate Barred Beach (IBB) and following the Short (1999) classification, results in a modally LBT (longshore bar-trough) or LTT (low tide terrace) with a small section being TBR (transverse bar and rip). Storms are considered the main factor controlling changes in the beach and dune slope. The most significant storm was recorded in March 2010 with a peak significant wave height of 3.91m. Contrary to the seasonal dune trend, several foredune slopes were observed to flatten following this event, which can be attributed to the action of dune slumping from the already weakened dune state. Modelling of foredune erosion, using a process-based model (XBeach), reproduced the erosion of the upper beach and dune toe reasonably well, but is currently limited by the acceptable slope value for dune stability, which does not account for biotic factors (e.g. plant roots). The comparison between the storm impact categories of Sallenger (2000) and the DSF (Dune Stability Factor) of Armaroli et al. (2012) shows a very good correspondence between the effects of the winter 2008–2009 storms and the vulnerability of the dune system predicted using both classifications. [Copyright &y& Elsevier]

Numerical coastal erosion models are used by engineers to predict the magnitude of storm erosion at the coastline. In particular, the 'dry' region of the beach, extending landwards from the waterline to include the beach face, berm and dunes, is a particular focus of interest to managers, planners and other coastal practitioners. However, the choice of the most appropriate numerical model to predict subaerial beach erosion requires careful consideration of the strengths and limitations of each model, and the quality and quantity of field data available for both model calibration and prediction. While no model can perfectly replicate observed upper beach erosion, this study specifically assesses the quantity of field calibration data required to achieve optimum model performance for coastal storm erosion modelling applications. Two of the most commonly used, but differently formulated, coastal erosion profile models are compared: the process-based and more complex model XBeach, and the semi-empirical and significantly simpler model SBEACH. A rigorous calibration technique (the Generalised Likelihood Uncertainty Estimation) is applied to both models, using a comprehensive dataset of pre- and post-storm topographic measurements collected over four differing storm events at Narrabeen-Collaroy Beach in southeast Australia, as well as at two adjacent embayed beaches. When applying the two numerical models using their default parameters (i.e., with no model calibration), SBEACH was found to be the more skilful model and XBeach default parameters were found to have no predictive skill along this stretch of coastline. Once calibrated with detailed field observations obtained before and after a single storm event, XBeach validation skill rose considerably and provided predictions of subaerial beach profile change with greater skill (87% better Brier Skill Score on average for the same calibration data) than SBEACH. Overall XBeach model performance was found to marginally improve when field observations obtained from additional storm events were included in the calibration process, whereas SBEACH showed negligible improvement. A comparison was made of the options available for transferring previously-calibrated parameters to adjacent locations, finding spatial proximity to be the most sensitive indicator of model performance for a transferred parameter set. Due to the alongshore variability in pre-storm topography as well as wave exposure at the sites tested, the spatial coverage of data was more important for the calibration process than the magnitude of the individual storm(s) used for a specific calibration. The results of this study underscore the need for careful consideration of the available calibration field data when choosing and optimising coastal erosion models. • Default XBeach parameters were found to be non-skilful at coastal sites in southeast Australia. • The XBeach model outperformed the SBEACH model when one or more calibration storm event field datasets were available. • Collection of calibration pre- and post-storm field data at specific locations of interest was important. • Spatial proximity was found to be a good performance indicator of calibrated parameter values transferred to new locations. [ABSTRACT FROM AUTHOR]

Waves interact with headlands on embayed beaches through refraction, diffraction and attenuation and can create alongshore gradients in wave energy and beach response. This energy gradient shifts alongshore with changes in wave direction, especially during storms when waves may come from a direction different to average conditions. To better predict embayed beach storm responses, improved identification of exposed and headland shadowed zones is needed. Here we present a generalised geometric approach to quantify the alongshore distance shadowed by headlands, called the shadow edge (Y sh), differentiating exposed and headland shadowed zones. Our approach uses headland geometry collected from readily available imagery, combined with measured or modelled storm wave direction, reducing the reliance on complex nearshore wave models derived from relatively scarce bathymetric data. We use monthly topographic beach surveys (2015–2019) at nine embayed beaches in SE Australia to investigate the impacts of headland and embayment geometry relative to storm wave direction (i.e., exposure). Further, beach responses were compared to erosion and recovery rates across different embayment geometries with varying levels of geological control on beach morphodynamics. We found that storm frequency, headland shadowing and embayment geometry control the alongshore magnitude of beach erosion and recovery rates. Mean subaerial beach volume losses to six high-energy storms were on average 3.5 times higher in exposed zones (42.7 ± 40.7 m3/m) than headland shadowed zones (12.1 ± 23.6 m3/m). Our geometric approach provides a simple alternative to predict headland influence on beach morphodynamics. The approach can be applied at a regional scale and could be integrated into early warning systems to predict coastal erosion. [Display omitted] • Generalised geometric approach defines headland shadow zones on beaches using open-access data. • Storm erosion is 3.5 times higher in exposed zones than headland shadow zones. • Results could help predict beach response to climate change-induced shifts in storm wave direction. • This approach could easily complement complex nearshore wave models. [ABSTRACT FROM AUTHOR]