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The process of shoreline change is inherently complex, and reliable predictions of shoreline position remain a key challenge in coastal research. Predicting shoreline evolution could potentially benefit from deep learning (DL), which is a recently developed and widely successful data-driven methodology. However, so far its implementation for shoreline time series data has been limited. The aim of this contribution is to investigate the potential of DL algorithms to predict interannual shoreline position derived from camera system observations at a New Zealand study site. We investigate the application of convolutional neural networks (CNNs) and hybrid CNN-LSTM (Long Short-Term Memory) networks. We compare our results with two established models: a shoreline equilibrium model and a model that addresses timescales in shoreline drivers. Using a systematic search and different measures of fitness, we found DL models that outperformed the reference models when simulating the variability and distribution of the observations. Overall, these results indicate that DL models have potential to improve accuracy and reliability over current models. [ABSTRACT FROM AUTHOR]

Bank retreat plays a fundamental role in fluvial and estuarine dynamics. It affects the cross-sectional evolution of channels, provides a source of sediment, and modulates the diversity of habitats. Understanding and predicting the geomorphological response of fluvial/tidal channels to external driving forces underpins the robust management of water courses and the protection of wetlands. Here, we review bank retreat with respect to mechanisms, observations, and modeling, covering both rivers and (previously neglected) tidal channels. Our review encompasses both experimental and in situ observations of failure mechanisms and bank retreat rates, modeling approaches and numerical methods to simulate bank erosion. We identify that external forces, despite their distinct characteristics, may have similar effects on bank stability in both river and tidal channels, leading to the same failure mode. We review existing data and empirical functions for bank retreat rate across a range of spatial and temporal scales, and highlight the necessity to account for both hydraulic and geotechnical controls. Based on time scale considerations, we propose a new hierarchy of modeling styles that accounts for bank retreat, leading to clear recommendations for enhancing existing modeling approaches. Finally, we discuss systematically the feedbacks between bank retreat and morphodynamics, and suggest that to move this agenda forward will require a better understanding of multifactor-driven bank retreat across a range of temporal scales, with particular attention to the differences (and similarities) between riverine and estuarine environments, and the role of feedbacks exerted by the collapsed bank soil. [ABSTRACT FROM AUTHOR]

Predicting shoreline change is a key issue in coastal research. Predictors, process-based or data-driven, tend to be developed and tested on high-frequency and high-quality data sets. Combining hydrodynamic and morphological variables extracted from video images and artificial neural network allows us to evaluate if sparse data could still provide physically-sound shoreline change predictions. The data set covered a 3-year period with shoreline position data (with an accuracy of ±5 m) available 73 % of the time and 66 % for the morphological parameters (beach state or bar location). The best configuration of the trained shallow (one hidden layer) Feedforward Artificial Neural Network (ANN), includes 10 input variables and 10 nodes allowing to capture the shoreline dynamic at different time scales, from the storm-event to the seasonal scale, and to predict the shoreline position on a 1-year period with a RMSE of about 6.7 m. Increasing the complexity of the architecture of the ANN by increasing the number of hidden layers did not improve the predictions. By modifying the number of input variables in the algorithm, the ANN also allows us to highlight the mitigation effect of the bar during the storm event and its role as sediment buffer during seasonal accretion. [ABSTRACT FROM AUTHOR]

Substantial volumes of sediment are moved on coarse grained beaches through the formation and destruction of beach cusps, yet the processes governing cusp behaviour remain poorly understood. Here, we combine continuous 2D LiDAR scan data with daily UAV topographic surveys and RGB imagery to provide detailed morphological measurements of beach cusps on a composite beach with the aim to investigate the role of sediment size and tidal stage on cusp behaviour. Rapid changes in cusp height and prominence were observed when storm-eroded gravels were readily transported over relatively impermeable sandy substratum, showing the high-order control that mixed matrix sediments have on this process. Post storm, gravels armoured the swash zone overlaying the sand and were rapidly reworked into horns, with the incipient bays simultaneously experiencing erosion. We provide some of the first field observations to show divergent behaviours occurring simultaneously along the beach as cusps adjust to the new dominant hydrodynamic regime, with some areas experiencing a shortening of cusp wavelength through new horn growth, whilst others contemporaneously experienced wavelength growth through the removal of intermediate horns. Cusp formation was generally more pronounced on the falling tide, but some evidence indicates horns can also be consolidated and grow in relief at some stages of individual rising tides. This research demonstrates how feedback between sediments, morphology and hydrodynamics are key to determining cusp form, with these insights only made possible through the novel combination of LiDAR, UAV, and camera methods to provide sufficient temporal and spatial resolution to resolve key processes. • Mobility of coarse sediment controls timescales of beach cusp formation. • Cusp spacing adjustment occurs through divergent behaviours alongshore. • Cusp formation is irregular due to feedbacks between flow, morphology, and sediment. • Cusp growth achieved through contemporaneous horn accretion and bay erosion. [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 description of the geomorphic characteristics in power law forms has been the subject of research, over the past 70 years, and has become the cornerstone of regime theory. However, just why power functions should represent such geomorphic relationships remains poorly understood. Hence, differences in the values of the regime exponents observed for different river systems remain largely unexplained. To address this issue, we derived generic forms of the power law relationships without postulating any power functions of the discharge. The theoretical approach accurately captures the systematic variations of the regime exponents shown by a number of large data sets from previous research. We also explain how frictional resistance is responsible for the systematic variability of regime exponents. Overall, our study provides a robust mechanism to describe the variations of the exponents, along with a deductive explanation of the power laws at the core of fluvial hydraulic geometry. Key Points: We analytically deduce why power functions of water discharge describe the geometric scales of fluvial channel cross sectionsWe demonstrate how frictional resistance may explain the governing relationships of hydraulic geometryOur theoretical approach captures the systematic variations of the power law exponents observed in natural river channels [ABSTRACT FROM AUTHOR]

The spatial distribution of urban areas at the national and regional scales is critical for urban planners and governments to design sustainable and environment-friendly future development plans. The nighttime lights (NTL) data provide an effective way to monitor the urban at different scales however is usually achieved by using empirical threshold-based algorithms. This study proposed a novel Artificial Neural Network (ANN) approach, using moderate resolution imageries as NTL, MODIS NDVI and land surface temperature data, to map urban areas. Both random and maximum dissimilarity distance algorithm sampling methods were considered and compared. The validation of the urban areas extracted from MDA-based ANN against the 2011 US national land cover data showed a reasonable quality (overall accuracy = 97.84; Kappa = 0.74) and achieved more accurate result than the threshold method. This study demonstrates that ANN can provide an effective, rapid, and accurate alternative in extracting urban built-up areas from NTL. [ABSTRACT FROM AUTHOR]

Double sandbar systems often characterize the surf zone of wave-dominated beaches and display a variety of poorly explained spatial configurations. Here, we explore the morphodynamic stability of double-barred beaches using a model based on linear stability analysis. Surf zone hydrodynamics are described by coupling depth and wave-averaged conservation of mass and momentum with the wave energy and phase equations, including roller dynamics. A simplified sediment transport formulation relates flow to seabed changes. Under normal wave incidence, an alongshore uniform coast with a cross-shore profile characterized by the presence of two sandbars can be unstable, thereby resulting in the development of crescentic and/or rip channel patterns. Our study demonstrates that sandbar coupling can be either in phase (highs and lows of both sandbars are at the same alongshore position) or out of phase (highs and lows of one sandbar correspond to lows and highs of the other sandbar). In line with observations, results of simulations show a large variability in the possible emerging bottom patterns. Our analysis indicates that modes of which the amplitude of the inner sandbar perturbation is larger than that of the outer sandbar are dominant for large height–depth differences between the two sandbar crests and small offshore wave heights. Patterns related to the outer sandbar dominate for small values of the difference in sandbar depth. For intermediate differences between the two sandbar depths, patterns on both longshore bars appear to be fully coupled (similar growth rates and strongly correlated pattern shapes). For relatively large waves and large depth over the outer sandbar, patterns can also develop close to the shoreline and/or inner surf zone together with patterns in the inner or outer sandbar. [ABSTRACT FROM AUTHOR]

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 individual 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. [ABSTRACT FROM AUTHOR]

We performed a series of laboratory experiments to study the growth and development of wave-generated ripples under constant and varying conditions. There are two aspects of our study. First, under time varying wave conditions, we measure the rate of ripple adjustment and the equilibrium mean ripple wavelength before and after the change in forcing. Our experiments with increasing wave forcing (i.e., increasing wave amplitude or wave period) lead to faster ripple growth and larger final wavelengths. Decreasing wave forcing leads to shorter ripple wavelengths and hysteresis. Existing predictors provide a reasonable description of both the final equilibrium spacing and of the spacing evolution after wave conditions are changed. The presence of defects (crestline irregularities) impacts the final equilibrium ripple wavelength. Second, we investigate the role of initial perturbation on ripple growth and geometry. Larger initial perturbations in the bed lead to faster growth of ripples and larger initial ripple wavelength. Our results suggest that irregularities at the pattern scale, such as defects and initial bed perturbations, are likely to impact ripple evolution and can be a control factor on hysteresis. [ABSTRACT FROM AUTHOR]

A range of computer science methods termed machine learning (ML) enables the extraction of insight and quantitative relationships from multidimensional datasets. Here, we review the use of ML on supervised regression tasks in studies of coastal morphodynamics and sediment transport. We examine aspects of 'what' and 'why', such as 'what' science problems ML tools have been used to address, 'what' was learned when using ML, and 'why' authors used ML methods. We find a variety of research questions have been addressed, ranging from small-scale predictions of sediment transport to larger-scale sand bar morphodynamics and coastal overwash on a developed island. We find various reasons justify the use of ML, including maximize predictability, emulation of model components, the need for smooth and continuous nonlinear regression, and explicit inclusion of uncertainty. The expanding use of ML has allowed for an expanding set of questions to be addressed. After reviewing the studies we outline a set of best practices for coastal researchers using machine learning methods. Finally we suggest possible areas for future research, including the use of novel machine learning techniques and exploring open data that is becoming increasingly available. [ABSTRACT FROM AUTHOR]

The long-term morphodynamic evolution of tidal networks on tidal flats is investigated using a two-dimensional numerical model. We explore the physical processes related to the development of the morphology and the presence of equilibrium configurations. Tidal networks are simulated over a rectangular domain representing a tidal platform, a different setting compared to estuaries (subject to riverine influence) and lagoons (offshore bars constricting the flow). In the early and middle phases of the tidal network evolution, large sediment patches with rhombus-like shape form and gradually migrate in the flood direction, even though the overall sediment flux is ebb-directed. A cross-section-averaged 'equilibrium' state is asymptotically approached after about 500 years. The area and peak discharge of the lower flat cross-sections at year 500 approximately show a 1:1 relationship, which is in agreement with field observations. We also show that model results are consistent with the Q-A relationship (peak discharge Q versus cross-sectional area A), which is obtained under the assumption of a constant Chézy friction. [ABSTRACT FROM AUTHOR]

Morphodynamic equilibrium is a widely adopted yet elusive concept in the field of geomorphology of coasts, rivers and estuaries. Based on the Exner equation, an expression of mass conservation of sediment, we distinguish three types of equilibrium defined as static and dynamic, of which two different types exist. Other expressions such as statistical and quasi-equilibrium which do not strictly satisfy the Exner conditions are also acknowledged for their practical use. The choice of a temporal scale is imperative to analyse the type of equilibrium. We discuss the difference between morphodynamic equilibrium in the “real world” (nature) and the “virtual world” (model). Modelling studies rely on simplifications of the real world and lead to understanding of process interactions. A variety of factors affect the use of virtual-world predictions in the real world (e.g., variability in environmental drivers and variability in the setting) so that the concept of morphodynamic equilibrium should be mathematically unequivocal in the virtual world and interpreted over the appropriate spatial and temporal scale in the real world. We draw examples from estuarine settings which are subject to various governing factors which broadly include hydrodynamics, sedimentology and landscape setting. Following the traditional “tide-wave-river” ternary diagram, we summarize studies to date that explore the “virtual world”, discuss the type of equilibrium reached and how it relates to the real world. [ABSTRACT FROM AUTHOR]

We describe the coupled biotic and abiotic dynamics in intertidal environments using a point model that includes suspended sediment deposition, wave- and current-driven erosion, biofilm sediment stabilization, and sediment production and stabilization by vegetation. We explore the effects of two widely different types of vegetation: salt-marsh vegetation and mangroves. These two types of vegetation, which colonize distinct geographical areas, are characterized by different biomass productivities and stabilization mechanisms. We show that changing vegetation and biofilm properties result in differing stable states, both in their type and number. The presence of the biofilm exerts a dominant control on the tidal flat (lower intertidal) equilibrium elevation and stability. Vegetation controls the elevation of the marsh platform (i.e., the upper intertidal equilibrium). The two types of vegetation considered lead to similar effects on the stability of the system despite their distinct biophysical interactions. [ABSTRACT FROM AUTHOR]

We present results from laboratory experiments on flow through submerged arrays of rigid cylinders embedded in a sandy bed. Using rigid, cylindrical elements to mimic vegetation and benthos, we account for only the physical effects resulting from their presence, eliminating biological factors, such as biofilms and root systems. In line with previous findings, rigid arrays modify the flow mean and turbulent velocity statistics. However, even if the flow speed is significantly damped within dense arrays, the amount of sediment that gets lifted into suspension increases as the density of the array increases due to array– and cylinder-scale turbulence. We present a first attempt to provide predictive relationships of suspended sediment concentration using an alternative approach for the Shields parameter with an empirical coefficient to account for turbulence generated by submerged arrays of rigid cylinders. A similar analysis, using a ratio of populated to non-populated Shields parameter, is conducted to predict resuspension as a function of array density. [ABSTRACT FROM AUTHOR]

We extend a numerical model to explore the morphodynamics of intertidal flats, with a specific focus on the sorting dynamics of sand and mud. We investigate the effect of tidal currents, wind waves, sediment properties, external sediment supply, flocculation and initial bed composition on the cross-shore profile shape and sediment sorting of intertidal flats. Consistent with existing analytical theories and benchmark simplified numerical solutions, the equilibrium cross-shore profile of intertidal flats simulated by the extended model is convex-up when tidal currents dominate and it progressively becomes concave-up when the strength of wind waves increases. The equilibrium profile is influenced by the external sediment supply which can lead to the seaward advance of intertidal flats. In line with field observations, mud tends to deposit on the upper intertidal flats when wind waves are relatively weak, while sand is mainly distributed on the middle and lower tidal flats. When wind waves are strong, both sand and mud are more easily resuspended and eroded, resulting in a noticeably concave-up profile near the high water mark. The initial bed composition (e.g., percentage of mud and sand fractions) is also found to play an important role: the intertidal flat is more convex-up in a muddier environment. Numerical modeling demonstrates that sediment properties (e.g., critical shear stress for erosion, settling velocity) and flocculation can pronouncedly influence the sediment sorting dynamics by modifying the initiation threshold and the advection distance of entrained sediments. Application of the extended model to a natural study site indicates a qualitative agreement with field observations. [ABSTRACT FROM AUTHOR]

A three-year dataset (2007–2010) of shoreline and sandbar positions derived from video observations of an open sandy beach (Biscarrosse, France) is analyzed, to explore the impact of storms on the seasonal shoreline dynamics. The results indicate that a clear seasonality is observed in the offshore significant wave height and in the occurrence of ‘winter storm’ events that are defined as periods with significant wave height greater than 4 m lasting at least 12 h. Data indicate that the range of variation of the inner sandbar positions (120 m) is two and a half times larger than the range of variation of the shoreline position. Correlation analyses suggest that the offshore conditions do not conclusively explain the position of the inner bar. Shoreline positions show a clear seasonal pattern, displaying a stable position occurring in February and July, providing evidence of seasonal-recovery although analysis of storm activity indicates that the number and intensity of storms is highly variable over the three years. The Biscarrosse data show that rapid erosion can be observed also under moderate conditions, and that beach recovery after the storm season can be relatively rapid. [ABSTRACT FROM AUTHOR]

Abstract: Applying complex systems perspectives to geomorphic systems leads to the conclusion that cause and effect in landscape systems does not always apply in the ways that common sense and traditional assumptions would suggest. Geomorphologists have long thought that events must have causes and that landscape structures exist where they do for particular reasons. In addition, since the rise of process geomorphology, geomorphologists have often assumed that small-scale processes directly cause large-scale, long-term landscape evolution; that for understanding or predicting the large-scale behaviors, the details of the small-scale processes matter; and that large-scale processes do not directly cause behaviors at much smaller scales. However, in self-organized systems, autogenic events can arise from feedbacks internal to the system, without any variation in the forcing to cause the event. Similarly, structures within self-organized patterns in the landscape can emerge spontaneously, even though there may not be any pre-existing heterogeneity to cause the localization of the structure. In addition, cause and effect can operate from large scales to small ones as well as the reverse, and interactions that emerge at larger scales can determine the characteristics of the landscape, independent of the details of the small-scale processes. To exemplify these points, we will use research on ‘sorted bedforms’, striking shallow seabed grain-sized sorted patterns on scales ranging from tens of meters to kilometers. The stripes of coarse sand or gravel that are segregated from intervening fine-sand domains were originally ascribed to hypothesized, spatially focused currents. However, more recent modeling and field observations point to a self-organization mechanism in which the locations of the features do not correspond with any heterogeneity in the forcing or antecedent conditions. Very recent modeling work shows that regionally the pattern can spontaneously break down and reform, without any corresponding change in the forcing. Experiments with different approaches to modeling these features, and very different ways of representing the small scale processes, tend to cause essentially identical behavior and characteristics at the scale of the pattern—suggesting that emergent interactions at the large scale more directly explain, or cause, the phenomena than do the small scale processes. Finally, as for many systems, behaviors at small scales are strongly influenced by larger scale behaviors. We also use select examples from a range of landscape-evolution studies to contrast predictions made using traditional assumptions about cause and effect from those made using a complex-systems approach. [Copyright &y& Elsevier]

Abstract: A sequence of daily beach surveys acquired over one month covering an area larger than 100,000m2, was analyzed to study morphological changes resulting from a cluster of storms. The beach response was highly variable in both the cross- and alongshore. A cumulative storm effect was not observed, despite one storm being characterized by a 10-year return period that had significant wave height (Hs) of 8.1m and a peak wave period (Tp) of 17s. Instead, storms that can potentially cause significant erosion in terms of Hs had a limited effect on the morphology because the large wave height was coupled to either neap tides, normally-incident short-waves (f >0.04Hz), or low levels of infragravity (0.004< f <0.04Hz) energy. Multiple linear regression analysis shows that volumetric changes in the upper part of the beachface are explained by offshore wave characteristics (period, height and direction), tidal range or by infragravity energy in the inner surf zone (assessed using pressure and velocity measurements). The results indicate that it is not possible to scale-up single-storm erosion studies into predictions of cluster-storm erosion. [Copyright &y& Elsevier]

Abstract: Tidal network morphodynamics is an active field of research and advances achieved over the last decade, particularly with respect to laboratory experiments and numerical modelling, have lead to fundamental insight about their functioning. We address how these advances have specifically contributed to the understanding of tidal network functioning, including the interaction between physical and biological processes. We discuss how the prediction of the long-term evolution of tidal networks is still limited and we focus on how it is hampered by three specific challenges. We first discuss the approach to long-term predictions, then focus on the coupling between physical and biological processes, and finally attempt to introduce the role of anthropic drivers in the evolution of these systems. [Copyright &y& Elsevier]

Sea-level rise has a strong influence on tidal systems, and a major focus of climate change effect studies is to predict the future state of these environmental systems. Here, we used a model to simulate the morphological evolution of tidal embayments and to explore their response to a rising sea level. The model was first used to reproduce the formation of channels and intertidal flats under a stable mean water level in an idealised and initially unchannelled tidal basin. A gradual rise in sea level was imposed once a well-developed channel network had formed. Simulations were conducted with different sea-level rise rates and tidal ranges. Sea-level rise forced headward erosion of the tidal channels, driving a landward expansion of the channel network and channel development in the previously non-inundated part of the basin. Simultaneously, an increase in channel drainage width in the lower part of the basin occurred and a decrease in the overall fraction of the basin occupied by channels could be observed. Sea-level rise thus altered important characteristics of the tidal channel network. Some intertidal areas were maintained despite a rising sea level. However, the size, shape, and location of the intertidal areas changed. In addition, sea-level rise affected the exchange of sediment between the different morphological elements. A shift from exporting to importing sediment as well as a reinforcement of the existing sediment export was observed for the simulations performed here. Sediment erosion in the inlet and the offshore transport of sediment was enhanced, resulting in the expansion of the ebb-tidal delta. Our model results further emphasise that tidal embayments can exhibit contrasting responses to sea-level rise. [ABSTRACT FROM AUTHOR]

Abstract: We integrate published data sets of field and laboratory experiments of wave ripples and use genetic programming, a machine learning paradigm, in an attempt to develop a universal equilibrium predictor for ripple wavelength, height, and steepness. We train our genetic programming algorithm with data selected using a maximum dissimilarity selection routine. Thanks to this selection algorithm; we use less data to train the genetic programming software, allowing more data to be used as testing (i.e., to compare our predictor vs. common prediction schemes). Our resulting predictor is smooth and physically meaningful, different from other machine learning derived results. Furthermore our predictor incorporates wave orbital ripples that were previously excluded from empirical prediction schemes, notably ripples in coarse sediment and long wavelength, low height ripples (‘hummocks’). This new predictor shows ripple length to be a weakly nonlinear function of both bottom orbital excursion and grain size. Ripple height and steepness are both nonlinear functions of grain size and predicted ripple length (i.e., bottom orbital excursion and grain size). We test this new prediction scheme against common (and recent) predictors and the new predictors yield a lower normalized root mean squared error using the testing data. This study further demonstrates the applicability of machine learning techniques to successfully develop well performing predictors if data sets are large in size, extensive in scope, multidimensional, and nonlinear. [Copyright &y& Elsevier]

Abstract: Tidal embayments are characterized by a wide variety of landscape features, often including either complex tidal channel networks or extensive flood-tidal deltas. The origin of these features and the influence of hydrodynamic drivers and initial geological setting on their long-term characteristics are essentially unexplored. A model was applied to simulate the long-term morphological evolution of tidal embayments, with the purpose of providing insight into the environmental conditions that lead to the differences in tidal embayment morphology. Numerical simulations indicated that the interaction between hydrodynamics, sediment transport, and the evolving topography gives rise to the formation of channel networks. The tidal range and the depth of the initially unchannelized tidal basin controlled the way in which the morphology evolved and determined the timescale over which channels and intertidal areas developed. Channel network formation occurred more rapidly when the tidal range increased and/or when the initial basin depth decreased. Tidal basins with a large initial depth showed the development of a flood-tidal delta and for these deep basins channel incision could remain absent over long timescales. Both tidal range and initial bathymetry affected final basin hypsometry and channel network characteristics, including the channel density and the fraction of the basin occupied by the channels. All the simulated morphologies, with different combinations of the tidal range and depth of the basin, evolved towards a state of less morphodynamic activity for which the relative intertidal area was proportional to the ratio of tidal amplitude to basin depth. [Copyright &y& Elsevier]

Abstract: Using a detailed set of hydrodynamic and suspended-sediment observations, we developed data-driven algorithms based on Boosted Regression Trees and Artificial Neural Networks to predict suspended-sediment reference (near-bed) concentration using water depth, wave-orbital semi-excursion, wave period and bed-sediment grainsize as inputs. With one exception, the response of the data-driven algorithms was physically sound; the exception was the response to water depth. Outside of the range covered by the data, predictor performance could not be assessed and is not necessarily reliable. Boosted Regression Trees provide the best predictor of suspended-sediment reference concentration and have a clear explanatory power. Artificial Neural Networks provide slightly poorer predictions. Although the response of the latter is more difficult to interpret, they can be more easily included in numerical models simulating larger (in space) and longer (in time) morphodynamic behavior. Within the range of variability provided by the measurements, these algorithms outperform conventional process-based predictors. [Copyright &y& Elsevier]

Numerical simulations of cross-shore wave transformation and associated wave setup were performed for 100,000 realistic combinations of wave height, period, and beach profile. Results of numerical simulations were compared with a widely used empirical predictor of wave setup, and the outcome was a large variability in setup relative to that calculated by the empirical predictor. The variability, comparable in magnitude to the scatter around the empirical predictor developed with field observations, arose from wave energy dissipation over the cross-shore profile that was not taken into account. The beach-face slope commonly used in empirical predictors can be a poor descriptor of wave transformation across the beach profile, where most of the wave energy dissipation and setup generation occurs. Shoreline setup appears to be far more dependent on accurate characterization of the offshore profile (e.g., bar location and depth) than the beach-face slope. [ABSTRACT FROM AUTHOR]

Abstract: Beach cusps are a common feature of steep reflective and intermediate beaches. Although many observations of beach cusp spacing exist, there are few observations quantifying the incipient formation, evolution and eventual destruction of these features. Beach cusp morphodynamics were analyzed using a 3-year dataset of video images collected at Tairua Beach (New Zealand). Twenty-four beach cusp episodes were selected to monitor the cycle of beach face changes, from planar to the appearance of the cusp patterns and back to planar again. Observations show that beach cusp disappearance can be ascribed not only to the erosive influence of storms but also to the persistence of accretionary conditions leading to the infilling of beach cusp bays and the development of an alongshore continuous berm. We also report observations of changes in beach cusp spacing over time which can be attributed to the merging of adjacent cusps within the cusp field, with the overall cusp spacing re-adjusting to accommodate the disappearance of a horn. Although the self-organization theory provides a better fit to the data and theory, we were unable to conclusively refute any of the mechanisms causing beach cusp formation since both existing theories, subharmonic standing edge wave and self-organization, can predict the trend in the observed beach cusp spacing. These observations show that initial beach cusp formation primarily occurs (around 70% of the episodes analyzed) under mildly accretionary conditions and, when accretion persists, the pattern disappearance is likely to occur as a result of bay infilling to form a featureless berm. [Copyright &y& Elsevier]

The relationships between functional linkages within communities and community dynamics are fundamental to biodiversity-stability relationships. By teasing apart the hidden layers within artificial neural networks (ANNs), we developed webs defining how functional groups influence each other's temporal dynamics. ANNs were based on 15 years of bimonthly monitoring of macrobenthic communities on three intertidal sandflats in Manukau Harbor (New Zealand). Sites differed in web topology and diversity, with the site dominated by one functional group exhibiting only a few strong links, the lowest α-, β-, and γ-diversity, and the highest temporal stability in a-diversity. However, positive interactions between functional groups, nonconcordant with harborwide or sitespecific environmental variables, always dominated the interaction webs. The increased number of links we observed with increased temporal variation of species richness within functional groups and overall diversity supports the insurance hypothesis. While our findings suggest that there may be no consistent model characterizing the topology of temporal interactions between functional groups, decreasing diversity is likely to decouple interactions between functional groups and decrease ecosystem functionality. [ABSTRACT FROM AUTHOR]

Abstract: The nearshore region exhibits many striking morphological patterns with a variety of spatial and temporal scales. The formation of these rhythmic features has been initially ascribed, depending on the pattern in question, to spatial structures in the flow or geological constrains. These forcing templates have been hypothesized to provide the spatial structure that becomes imprinted on the shoreline or seabed morphology. More recently, new explanations for rhythmic patterns have involved interactions between fluid flow and sediment transport that create morphological feedbacks and lead to pattern self-organization. While forcing-template models do not explicitly treat transport of the sediment that makes up the pattern, self-organization models focus on the strong couplings within flow/sediment systems, and on interactions between emergent structures. We illustrate the sweeping shift from template explanations to self-organization by discussing four nearshore patterns: beach cusps, surfzone crescentic sandbars, inner-shelf sorted bedforms, and large-scale cuspate shorelines. Models involving self-organization show that local interactions between flow and sediment transport can collectively give rise to patterns with large-scale coherence and that the driving feedbacks can be associated with either topographical or grain-size composition instabilities. An approach based on self-organization also allows researchers to establish limitations in the predictability of the occurrence of rhythmic patterns and characteristics as well as to study mechanisms leading to the observed variability of pattern or lack of regularity. [Copyright &y& Elsevier]

We explore the role of biophysical feedbacks occurring at the patch scale (spatial scale of tens of meters) that influence bivalve physiological condition and affect patch stability by developing a numerical model for the pinnid bivalve, Atrina zelandica, in cohesive sediments. Simulated feedbacks involve bivalve density, flow conditions (assumed to be primarily influenced by local water depth and .peak current speed), suspended sediment concentration (evaluated through a balance between background concentration, deposition, and erosion), and changes in the physiology of Atrina derived from empirical study. The model demonstrates that high bivalve density can lead to skimming flow and to a concomitant decrease in resuspension that will affect suspended sediment concentration over the patch directly feeding back on bivalve physiology. Consequently, for a given flow and background suspended sediment load, the stability of a patch directly depends on the size and density of bivalves in the patch. Although under a range of conditions patch stability is ensured independently of bivalve density, simulations clearly indicate that sudden changes in bivalve density or suspended sediment concentration can substantially affect patch structure and lead to different stable states. The model highlights the role of interactions between organisms, flow, and broader scale environmental conditions in providing a mechanistic explanation for the patchy occurrence of benthic suspension feeders. [ABSTRACT FROM AUTHOR]

Biomorphodynamic interactions, the feedback loops that operate between physical processes, biology and morphology, affect the long-term evolution of estuaries. This paper outlines how consideration of such interactions and implementation through innovative modelling techniques can become the next crucial step needed to advance understanding of estuarine evolution. [ABSTRACT FROM AUTHOR]

Wave-generated ripples are macroscopic roughness elements that influence fluid flow and sediment transport. For a major group of ripples (orbital ripples), morphology (height and wavelength) is set by the wave conditions. In natural conditions, where wave forcing is highly variable, ripple morphology is frequently changing. We investigate the rate of morphological change after changes in wave conditions (i.e., wave height and period), using laboratory experiments with a step-change in wave forcing. The adjustment time of ripple morphology to new conditions –– the hysteresis time scale (hereafter referred to simply as hysteresis) –– is proportional to changes in wave orbital diameter, and the coefficient of proportionality differs for decreasing and increasing orbital diameter. When the Shields parameter is lower than a threshold (0.043), there is no change in ripple morphology (or changes are extremely slow). In addition, we find the presence of defects (irregularities from straight parallel crestlines) reduces the hysteresis time scale. The dependence of hysteresis on defect density implies that a larger density of defects results in faster ripple adjustment, confirming previous theoretical and numerical model results. • Widening and narrowing of orbital diameter corresponds to the different changing rate of hysteresis. • If the Shields parameter is below a certain value, pre-existing ripples do not change or change extremely slowly. • Larger defect densities result in shorter hysteresis for cases with the same Shields parameter. [ABSTRACT FROM AUTHOR]

The role of three-dimensionality (3D) in modulating both flow and sediment transport remains poorly understood. 3D bed elevation measurements are difficult to obtain due to irregular dune shapes and submergence. Using photogrammetric tools for topographic reconstruction has become popular in surface studies, yet water refraction makes through-water image capturing of submerged dunes still challenging. We show that through-water images and Structure from Motion (SfM) tools can produce accurate Digital Elevation Models (DEMs) of a measured dune field, with a high level of detail. It is a low-cost and non-intrusive alternative for submerged bed elevation measurements. We provide a detailed SfM workflow, introduce and discuss the use of camera coordinates and underwater ground control points, and processing steps needed to obtain high accuracy DEMs. Our method results in DEMs with mm resolution in controlled laboratory conditions. New data for 23 dune field DEMs from 6 experiments were obtained and are presented. The dune field DEM time series provide insights on dune interaction processes. In our experiments, merging and defect creation were most common. Merging decreases the number of bedforms, and defect creation is responsible for more bedforms. Dunes continue to interact and jostle after achieving equilibrium. Simple crests are much more frequently observed than irregular, sinuous or double crests. Two-dimensional (2D) crest shapes were observed, although crest shapes were generally of 3D nature. Observed dune migration rates are not steady and vary in time and space. Bedform splitting speeds up dune migration, whilst neighbouring dunes tend to accelerate or decelerate. We identify a cascade of processes and show that 3D DEMs at high frequency are required to resolve observed rapid deformations and interaction of dunes. The identified dune interaction processes are inherent to sediment flux (variability), whereas the temporal component of the underlying sediment transport processes is still not well understood in relation to average transport. Unlabelled Image [ABSTRACT FROM AUTHOR]

Predicting recreational water quality is one of the most difficult tasks in water management with major implications for humans and society. Many data-driven models have been used to predict water quality indicators to allow a real time assessment of public health risk. This assessment is most commonly based on Faecal Indicator Bacteria (FIB), with the value of FIB compared with thresholds published in guidelines. However, FIB values usually tend to be unbalanced within water quality datasets, with small proportions of data exceeding guideline thresholds and far larger numbers that do not. This can be a limiting factor in the uptake of model predictions since, even if the overall accuracy is high, the sensitivity of the predictions can be low. To address this issue, this paper proposes an adaptive synthetic sampling algorithm (ADASYN) to generate synthetic above-threshold FIB instances and test the validity of the approach for the prediction of recreational water quality. The models in this paper are based on four machine learning techniques: k-mean nearest neighbour, boosting decision tree, support vector machine, and multi-layer perceptron artificial neural network and are applied to five different locations in Auckland, New Zealand. Aside from support vector machine, all models provide favourable predictions with relatively high sensitivity (around 75%) and overall accuracy (over 90%), indicating that both the compliant and exceedance conditions can be effectively predicted through the use of more sophisticated model training which involves artificial data. Considering the model accuracy and stability, boosting decision trees (BDT) and multi-layer perceptron artificial neural (MLP-ANN) network are the best two models and the multi-layer perceptron is the most efficient with the shortest computation time. Image 1 • Applied ADASYN to address the problem of unbalanced water quality datasets. • Ssessed the ability of machine learning models when using a balanced dataset. • Compared results at different locations using different machine learning models. [ABSTRACT FROM AUTHOR]

Wave runup is one of the most critical parameters contributing to coastline flooding and shoreline change. Many formulas have been developed to empirically predict wave runup characteristics. However, large errors are still associated to these estimates, feeding a debate on the best approach to describe runup through simple parameterizations. In this work we present a comprehensive review on runup, setup and swash empirical models. We use a large database of field measurements to verify the predictive capability of recent formulas, addressing possible sources of variability. We identify the effect of the nearshore bathymetry as an important factor missing in empirical predictors and examine this issue through an analysis of runup simulated with the SWASH model over different barred and linear bathymetries. The details of the submerged beach profile affect estimates, especially with respect to setup values. The lack of standardization in measuring, post-processing and sharing runup data, limits the application of previous published databases on new analysis. We list a set of recommendations that can be used as guidelines for new measurements to broaden the applicability of the datasets in future studies. Finally, we discuss the remaining questions that still need to be further explored. [ABSTRACT FROM AUTHOR]

Wave climatologies from historical and projected simulations of the ACCESS1.0, MIROC5 and CNRM-CM5 Global Circulation Models (GCM) were sourced from the Coordinated Ocean Wave Climate Project (COWCLIP) and downscaled using the SWAN wave model. Biases between GCM's historical simulations and a regional hindcast were assessed, and the two best-performing models (ACCESS1.0, MIROC5) had their projections analysed. A general increase in wave height and period was observed along the south/west, together with a decrease in $H_s$ H s along the north/east coasts. The projected near-term (NEA21C) period shows mostly a $H_s$ H s increase, whilst for the long-term (END21C) period, increased and decreased $H_s$ H s are present. The areas of statistically significant changes are larger in the END21C than in the NEA21C period. The wave direction change is counter-clockwise along the west and clockwise along the east coasts. This study is a first assessment of historical and projected GCM-forced waves along New Zealand and the database we generated can be of great value for renewable energy research, risk assessment and the mitigation of future coastal hazards. [ABSTRACT FROM AUTHOR]

Abstract: When modelling urban expansion dynamics, cellular automata models focus mostly on the physical environments and cell neighbours, but ignore the 'human' aspect of the allocation of urban expansion cells. This limitation is overcome here using an intelligent self-adapting multiscale agent-based model. To simulate the urban expansion of Auckland, New Zealand, a total of 15 urban expansion drivers/constraints were considered over two periods (2000–2005, 2005–2010). The modelling takes into consideration both a macro-scale agent (government) and micro-scale agents (residents of three income levels), and their multi-level interactions. In order to achieve reliable simulation results, ABM was coupled with an artificial neural network to reveal the learning process and heterogeneity of the multi-sub-residential agents. The ANN-ABM accurately simulated the urban expansion of Auckland at both the global and local scales, with kappa simulation value at 0.48 and 0.55, respectively. The validated simulation result shows that the intelligent and self-adapting ANN-ABM approach is more accurate than an ABM with a general type of agent model (kappa simulation = 0.42) at the global scale, and more accurate than an ANN-based CA model (kappa simulation = 0.47) at the local scale. Simulation inaccuracy stems mostly from the outdated master land use plan. [ABSTRACT FROM AUTHOR]

As populations around volcanoes grow, the potential for society to be impacted by lava flows is increasing. While lava flows are known to ignite, bulldoze and/or bury structures, little is known about potential impacts to buried infrastructure. We measure temperature profiles below molten rock to constrain a heat transfer model. Thermomagnetic and palaeomagnetic measurements on soil samples from beneath a 2014 Hawaiian lava flow are then used to verify the model. Finally, we illustrate the model's utility in lava flow hazard assessments by modelling a hypothetical lava flow active for 4 weeks in Auckland (New Zealand). The modelling predicts the upper 1.7 m of dry soil would exceed 100 °C after 1 week, and the upper 3.8 m of soil would exceed 100 °C after 4 weeks. Determining the depth profile of substrate heating has important implications for planning and preparedness (e.g. siting buried infrastructure), volcanic impact and risk assessments, and decision-making before and during lava flow crises (e.g. mitigation measures to be employed). [ABSTRACT FROM AUTHOR]

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone. [ABSTRACT FROM AUTHOR]

Tropical cyclones are associated with extreme winds, waves, and storm surge, being among most destructive natural phenomena. Developing capability for a rapid impact estimate is crucial for coastal applications and risk preparedness. When predicting waves characteristics associated to tropical cyclones, the traditional approach involves a two‐step procedure (a) a Holland‐type wind vortex model and (b) numerical simulations using a wave generation model, using buoy and satellite measurements for validation. In this work, we take advantage of the increasing amount of remote sensing observational data and propose a new empirical model to estimate the wind wave footprint of tropical cyclones. For this purpose, we construct a dataset with over a million satellite observations of waves triggered by tropical cyclones assuming a circular shape of the TC influence area and defining composites of significant wave height as a function of representative parameters of the track characteristics like the minimum pressure, its forward velocity, and its latitude. The validation against buoy data confirms the usefulness of the model for a first and rapid estimation of the wave footprint, although an underestimation of the most extreme events is observed due to the relatively small number of observations recorded. Due to its efficiency, the model can be applied for rapid estimations of wave footprints in operational systems, reconstruction of historical or synthetic events and risk assessments. [ABSTRACT FROM AUTHOR]

We develop a biomorphodynamic model to investigate sediment and vegetation dynamics on a schematic intertidal flat characterized by an initially well-mixed sand-mud mixture. Major interactions between tides, wind waves, salt marshes, sediment transport and sea level rise (SLR) are taken into account. For a bare flat under only tidal action, the model predicts a convex cross-shore profile with the surficial distribution of mud and sand on the upper and lower part of the intertidal flat, respectively. When wind waves are strong, the intertidal flat is highly eroded resulting in a concave profile near the high water mark. This behavior is pronouncedly altered when the intertidal flat is vegetated with the presence of salt marshes. Numerical results suggest that a considerable amount of mud can still remain in the vegetated region even when wave action is strong. A steeper transition zone forms at the boundary between salt marshes and bare flats because of the differential sediment deposition in the two neighboring regions. The inclusion of wind waves is found to considerably enhance the size of the marsh-edge transition zone. For the numerical experiments designed in this study, the profile shape and sediment sorting behavior of tidal flats are not significantly modified by a gradual rising sea level. However, the impacts of SLR on vegetated tidal flats are still manifold: (a) driving the landward migration of intertidal zone and salt marshes; (b) enhancing sediment erosion on intertidal flats; and (c) drowning salt marshes under limited sediment supply with the constrain of seawalls. Finally, model results suggest that organic carbon accumulation on marshlands may be enhanced with an increasing SLR rate provided that salt marshes are not drowned. [ABSTRACT FROM AUTHOR]

This paper reports a scientific inquiry carried out within the management process of an exceptional accumulation of reeds and seagrasses that took place in December 2019 on Poetto beach (Cagliari, southern Sardinia, western Mediterranean). The magnitude of the event raised concern within the local community and tourism service providers especially for the compromised beach accessibility caused by this large amount of biomass. The scientific inquiry is carried out in support of coastal management, to assess the berm processes before the removal of the reed wracks decided by the local municipality. By means of a numerical approach, this work devotes special attention to the runup induced by storms in the presence of reed and seagrass deposits on a low-lying backshore. Field surveys reported relatively large conductivity parameters in the presence on reed and seagrass deposits. The numerical approach shows that the increased beach permeability can eventually mitigate coastal flooding induced by storms. These results highlight the ecosystem services provided by reed and seagrass wracks together with the implications for coastal protection and management. • Large permeability values were measured in areas with seagrass and reed deposits. • A numerical approach assesses runup and infiltration processes on a sandy beach. • Reed and seagrass wracks can mitigate flooding by increasing beach permeability. [ABSTRACT FROM AUTHOR]

Abstract: We analyse a seven-year dataset (1999–2005) of shoreline and sandbar variations derived from video observations at the embayed Tairua Beach, New Zealand, to explore sandbar–shoreline coupling and to determine how this coupling is related to alongshore-averaged sandbar–shoreline separation and beach rotation. Our results quantify the coupling between the sandbar and the shoreline which is directly related to the reduced separation between the sandbar and the shoreline. Using a simple predictive shoreline model, we show that this behaviour is related to the energy of the incoming waves. Our observations are obtained from a headland-enclosed beach and show aspects of the morphological state that relate to the existence of headlands that are not considered in the Wright and Short beach state classification. Both the sandbar and shoreline at Tairua Beach rotate relatively quickly (<1month) during the winter storm events, when the storms are accompanied by strong alongshore components, gradually returning during the summer months. The sandbar–shoreline coupling length scale is controlled by this rotation, with large wavelengths occurring when the sandbar is strongly rotated. [Copyright &y& Elsevier]

Researchers have extensively investigated the back-barrier islands morphodynamics using numerical methods. However, the influence of rocky mouth islands, which may be submerged by sea-level rise, has been rarely explored. Using the Dongshan Bay in southern China as a reference, this study numerically explores the long-term morphodynamic effect of geological constraints (e.g. rocky islands) for back-barrier basins. Model results indicate that the spatial configuration of mouth islands can considerably affect the morphological development of tidal basins. The presence of mouth islands narrows the inlet cross-sectional area, increasing flow velocity and residual current, resulting in more sediment suspension and transport. Meanwhile, mouth islands tend to increase erosion in the tidal basin and sedimentation in the ebb-delta area. Furthermore, the spatial distribution of mouth islands can also affect tidal basin evolution: the basin-side mouth islands tend to cause more basin erosion with higher tidal currents and more sediment transport. In contrast, the delta-side ones may increase relative sediment deposition in the basin. Finally, larger tidal prisms are observed with more mouth islands and with basin-side mouth islands, suggesting that the number and location of islands can affect the relationship between the tidal prism and inlet cross-sectional area. This modelling study furthers the understanding of barrier basin morphodynamics affected by rocky mouth islands and informs management strategies under a changing environment. [ABSTRACT FROM AUTHOR]

Abstract: Alongshore variability in swash motions – shoreline oscillations about the mean water level on the beach face – were investigated using video images and a high-resolution morphology survey on an intermediate beach. Under mild, swell-dominated offshore wave conditions, alongshore variation of up to 78% in significant runup height Rs (defined as 4 times the standard deviation of the swash time series) was observed. This variation was predominantly driven by energy at the incident (>0.05Hz) frequencies (where most of the swash energy was observed), and, consistent with previous observations, was mainly controlled by changes in the slope of the beach face (measured at the mean swash location). However, alongshore patterning in wave breaking over the sandbar caused variation in the degree of wave dissipation along the beach and also resulted in alongshore changes to swash motions. Although alongshore changes in beach slope and wave breaking patterning over the bar were observed to be typically correlated, both were needed in a regression model to provide the best explaination of alongshore changes in Rs. At infragravity frequencies (<0.05Hz), alongshore variability was not well associated either with changes in beach slope or wave breaking patterning. Low-mode edge waves were observed in the swash measurements and their contribution to the total energy spectrum was greatest near the location where a shoal was observed, suggesting this shoal may play a role in forcing. The edge waves may have contributed to the swash variability observed at infragravity frequencies. However, in these reflective conditions, the infragravity band plays a secondary role in controlling alongshore variations to swash motions. [Copyright &y& Elsevier]

Abstract: Groundwater seepage is known to influence beach erosion and accretion processes. However, field measurements of the variation of the groundwater seepage line (GWSL) and the vertical elevation difference between the GWSL and the shoreline are limited. We developed a methodology to extract the temporal variability of the shoreline and the wet–dry boundary using video imagery, with the overarching aim to examine elevation differences between the wet–dry boundary and the shoreline position in relation to rainfall and wave characteristics, during a tidal cycle. The wet–dry boundary was detected from 10min time-averaged images collected at Ngaranui Beach, Raglan, New Zealand. An algorithm discriminated between the dry and wet cells using a threshold related to the maximum of the red, green, and blue intensities in Hue-Saturation-Value. Field measurements showed this corresponded to the location where the water table was within 2cm of the beachface surface. Time stacks and time series of pixels extracted from cross-shore transects in the video imagery, were used to determine the location of the shoreline by manually digitizing the maximum run-up and minimum run-down location for each swash cycle, and averaging the result. In our test data set of 14 days covering a range of wave and rainfall conditions, we found 6 days when the elevation difference between the wet–dry boundary and the shoreline remained approximately constant during the tidal cycle. For these days, the wet–dry boundary corresponded to the upper limit of the swash zone. On the other 8 days, the wet–dry boundary and the shoreline decoupled with falling tide, leading to elevation differences of up to 2.5m at low tide. Elevation differences between the GWSL and the shoreline at low tide were particularly large when the cumulative rainfall in the preceding month was greater than 200mm. This research shows that the wet–dry boundary (such as often used in video shoreline-finding algorithms) is related to groundwater seepage on low-sloped, medium to fine sand beaches such as Ngaranui Beach (mean grain size ∼0.27mm, beach slope ∼1:70) and may not be a good indicator of the position of the shoreline. [Copyright &y& Elsevier]

Abstract: Morphological observations (terrestrial laser scanning) and sediment analysis are used to study beach cusp morphodynamics at Melbourne Beach (Florida, USA), a moderately sloped beach characterized by fine sand. The study couples rapid high-resolution surveying with surficial sediment sampling over multiple tidal cycles. Surveys were run ~500m alongshore and sediment samples were collected intertidally over a period of 5days. Beach cusp location within larger scale beach morphology is shown to directly influence cusp growth as either gross erosional or gross accretional. Sediment characteristics within the beach cusp morphology are reported coincident with cusp evolution. Variations in particle size distribution kurtosis are exhibited as the cusps evolve, however no significant correlation is seen between grain size and position between horn and embayment. During the end of the study, a storm resulted in beach cusp destruction and increased sediment sorting. [Copyright &y& Elsevier]

Abstract: This paper introduces a semi-automatic computer algorithm designed to detect rip current channels in video imagery. As a case study, this method is applied to 3.3years of video data from an embayed beach to demonstrate the link between antecedent surf zone morphology, wave energy and up/down transitions in beach state. An objective measure of rip channel change was developed to define six significant rip reconfiguration events and relate these events to wave energy. Over the period of study no complete resets of the nearshore morphology occurred. The analysis indicates that direct correlation of rip patterns with the instantaneous wave conditions is not a useful way to demonstrate how rips and waves interact. The average wave energy over a period of ten days, combined with storm duration were good indicators of rip channel change, demonstrating that in general, beach morphology responds with a time lag to changes in forcing. Rip channels with a short cross-shore length and narrow alongshore spacing responded faster to changes in wave conditions than rips with a long cross-shore length and wider alongshore spacing. To force changes in the rip morphology, longer rip channels required wave events of higher energy and/or a longer duration. Offshore islands protect the beach under certain wave approach angles, sometimes resulting in a dual-width surf zone, which was narrow at the sheltered end and wide at the exposed end of the beach. The wider surf zone end was characterised by three dominant and persistent rip channels, whereas the narrow surf zone section contained a number of smaller rips which evolved rapidly under wave forcing. Our observations demonstrate the importance of rip channel size in controlling the response time of nearshore morphology. [Copyright &y& Elsevier]

Abstract: We observed the onshore migration (3.5 m/day) of a nearshore sandbar at Tairua Beach, New Zealand during 4 days of low-energy wave conditions. The morphological observations, together with concurrent measurements of waves and suspended sediment concentrations, were used to test a coupled, wave-averaged, cross-shore model. Because of the coarse bed material and the relatively low-energy conditions, the contribution of the suspended transport to the total transport was predicted and observed to be negligible. The model predicted the bar to move onshore because of the feedback between near-bed wave skewness, bedload, and the sandbar under weakly to non-breaking conditions at high tide. The predicted bathymetric evolution contrasts, however, with the observations that the bar migrated onshore predominantly at low tide. Also, the model flattened the bar, while in the observations the sandbar retained its steep landward-facing flank. A comparison between available observations and numerical simulations suggests that onshore propagating surf zone bores in very shallow water (<0.25 m) may have been responsible for most of the observed bar behaviour. These processes are missing from the applied model and, given that the observed conditions can be considered typical of very shallow sandbars, highlight a priority for further field study and model development. The possibility that the excess water transported by the bores across the bar was channelled alongshore to near-by rip-channels further implies that traditional cross-shore measures to judge the applicability of a cross-shore morphodynamic model may be misleading. [Copyright &y& Elsevier]