Search

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. This work would not have been possible without funding from the Strategic Environmental Research and Development Program's grant DOD/SERDP RC-2644 and from the Spanish Ministry of Science and Innovation, project Beach4cast PID2019-107053RB-I00. Ana Rueda funded by a Juan de la Cierva Incorporación Scholarship (IJC2020-04390). Laura Cagigal is funded by a scholarship from the University of Auckland. Open access publishing facilitated by The University of Auckland, as part of the Wiley - The University of Auckland agreement via the Council of Australian University Librarians.

Understanding and predicting the geomorphological response of fluvial and tidal channels to bank retreat underpins the robust management of water courses and the protection of wetlands.

We applied machine learning to improve the accuracy of present predictors of wave setup. Namely, we used an evolutionary-based genetic programming model and a previously published dataset, which includes various beach and wave conditions. Here, we present two new wave setup predictors, a simple predictor, which is a function of wave height, wavelength, and beach slope, and a fitter, but more complex predictor, which is also a function of sediment diameter. The results show that the new predictors outperform existing formulas. Therefore, we conclude that machine learning models are capable of not only improving prediction capability (when compared to classical predictors) but also of providing physically sound descriptions of the processes modelled.

Bathymetric data are essential for accurate predictions of flooding in estuaries, because water depth is a fundamental component in the shallow-water hydrodynamic equations used in numerical models. Where LiDAR or acoustic in-situ surveys are unavailable, recent efforts have centred on the use of satellite images to estimate bathymetry (SDB). This work is aimed at (1) determining the accuracy of SDB, and (2) assessing the suitability of the SDB for surge/tidal modelling of estuaries. The SDB is created by extracting the waterline as it tracks over the bathymetry with changing tides, and is applied to 4 different estuaries in New Zealand: Whitianga, Maketū, Ōhiwa and Tauranga Harbour. Results show that the waterline method provides similar bathymetries to the LiDAR with root-mean squared error equal to 0.2 m, and it is slightly improved when two proposed correction methods are applied to the bathymetry derivations: the removing of statistical bias (by 2 cm) and hydrodynamic modelling correction (by 1 cm). Finally, the use of SDB in numerical simulations of surge levels is assessed for Tauranga Harbour with 4 different scenarios that explore the use of SDB in comparison to bathymetry data collected using non-satellite survey methods. One of these includes the well-known Stumpf-ratio method to extract the SDB of subtidal regions (so that only satellite information is used). The use of the satellite derived bathymetry in hydrodynamic models does not result in significant differences in terms of water levels, when compared with the scenario modelled using surveyed bathymetry.

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 (Formula presented.) along the north/east coasts. The projected near-term (NEA21C) period shows mostly a (Formula presented.) increase, whilst for the long-term (END21C) period, increased and decreased (Formula presented.) 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.

Coastal landforms can sometimes result in unique and visually mesmerizing spatially-organized patterns. Different spatial patterns develop over scales ranging from centimeters to tens of kilometers, and are observed at the shoreline (e.g., ripples, beach cusps, shoreline undulations), in the surf zone (e.g., crescentic or multiple sandbars) and even in the continental shelf (e.g., sand ridges, sand waves) where wind waves may play a minor role. Here, we provide a review of the characteristics of rhythmic patterns that develop in the nearshore and of some of their formative processes, a topic of ongoing debate within the research community.

Emerging research shows that microplastic pollution could be impacting seafloor ecosystem function, but this has been primarily demonstrated without environmental and ecological context. This causes uncertainty in the real-world effects of microplastic pollution and leaves out essential information guiding policy and mitigation. In this study, we take a well-supported sampling design and statistical approach commonly employed in benthic ecology to evaluate real-world effects of microplastic pollution on coastal, benthic ecosystem function. We utilised environmental gradients in the Waitemata Harbour of Auckland, New Zealand to evaluate the importance of commonly assessed biological, chemical, and geological sediment variables and the characteristics of microplastic contaminants in driving essential ecosystem functions. Our results showed that models including microplastic terms were more accurate and explained more variability than those without microplastic terms, highlighting that microplastics impact real-world seafloor ecosystem function. Specifically, microplastic fibers significantly influenced oxygen flux (p0.03) and the diverse forms of microplastics (i.e., richness) significantly influenced ammonium flux (p0.02). Additionally, interactions between microplastic fiber concentrations and mollusc abundances significantly contributed to oxygen flux (p0.02). These results provide the first evaluation of in situ relationships between microplastics and ecosystem function. Even more importantly, this study suggests the value of environmental and ecological context for addressing microplastic impacts on benthic ecosystems and argues for further field examination.

Understanding the interactions between dune systems and beaches is critical to determining the short-term shoreline response and the long-term resilience. In this study, almost 15 years of monthly beach/dune measurements were analysed for three different profiles at Vougot Beach, France to understand and predict shoreline changes from intra- to multi-annual time- scales. Four migration modes: advance/retreat (translation modes) and steepening/flattening (rotation modes) were identified through a centroid analysis. The analysis showed that translation and rotation can occur simultaneously, with long-term trends of beach retreat and profile steepening (lower beach retreating and upper beach advancing), which was interrupted by two energetic wave events causing profile flattening (lower beach advancing and upper beach retreating). These two observations are evidence of how the sediment contribution resulting from the dune erosion events temporarily caused a large advance in the shoreline position. A recent modelling approach that accounts for different time-scales is applied to predict the shoreline changes, showing significant improvements in comparison to a traditional shoreline equilibrium model when time-scales related with the dune erosion and recovery are considered. The results showed that the dune system affects the beach profile evolution both spatially, with different impacts at different elevations along the cross-shore profile, and temporally, by periodically redistributing the sediment in the system. Plain Language Summary Changes in the shoreline position are the result of a delicate balance between hydrodynamic (e.g., waves, currents, water levels) and morphology (e.g., dunes, beachface). Dunes are a natural barrier to storms and much of their ability to stand erosive events is related to their recovery after a storm. At the same time, the beachface often responds to incoming waves by either changing its slope (rotation mode) or by advancing/retreating (translation mode). Using 15 years of profile measurements at Vougot beach, France, we identified the different modes and observed if, when and how they occur. Our analysis shows that the evolution of the beach system was controlled by the sediment exchanges and redistribution between the dune and the intertidal beach. Different elevations of the intertidal beach profile showed distinct behaviour and different time-scales of change. Our work provides evidence that a multi-temporal scale approach is necessary to predict sediment redistribution along the beach profile.

Understanding sediment sorting and bedding dynamics has high value to unravelling the mechanisms underlying geomorphological, geological, ecological and environmental imprints of tidal wetlands and hence to predicting their future changes. Using the Nanhui tidal flat on the Changjiang (Yangtze) Delta, China, as a reference site, this study establishes a schematized morphodynamic model coupling flow, sediment dynamics and bed level change to explore the processes that govern sediment sorting and bedding phenomena. Model results indicate an overall agreement with field data in terms of tidal current velocities, suspended sediment concentrations (SSCs), deposition thicknesses and sedimentary structures. Depending on the variation of tidal current strength, sand-dominated layers (SDLs) and mud-dominated layers (MDLs) tend to form during spring and neap tides, respectively. Thinner tidal couplets are developed during daily scale flood–ebb variations. A larger tidal level variation during a spring–neap tidal cycle, associated with a stronger tidal current variation, favours the formation of SDLs and tidal couplets. A larger boundary sediment supply generally promotes the formation of tidal bedding, though the bedding detail is partially dependent on the SSC composition of different sediment types. Sediment properties, including for example grain size and settling velocity, are also found to influence sediment sorting and bedding characteristics. In particular, finer and coarser sediment respond differently to spring and neap tides. During neap tides, relatively small flow velocities favour the deposition of finer sediment, with limited coarser sediment being transported to the upper tidal flat because of the larger settling velocity. During spring tides, larger flow velocities transport more coarser sediment to the upper tidal flat, accounting for distinct lamination formation. Model results are qualitatively consistent with field observations, but the role of waves, biological processes and alongshore currents needs to be included in further studies to establish a more complete understanding.

The use of power law forms to describe hydraulic geometry is a classic subject with a history of over 70 years. Two distinct forms of power laws have been proposed: at-a-station hydraulic geometry (AHG) and downstream hydraulic geometry (DHG). Although the utility of these semiempirical expressions is widely recognized, they remain poorly understood in terms of the mechanisms underlying the differences between AHG and DHG, as well as the variability among different systems. In this study, we attempt to address these basic issues. Two hypotheses are proposed: (a) the different geomorphic relationships represented by AHG and DHG result from the control of lateral adjustment of the bank and flow turbulence over short and long timescales, respectively; and (b) the systematic variability of the AHG and DHG exponents is related to the description of the frictional resistance. These two hypotheses are embedded in our theoretical models and lead to explicit functional forms for AHG and DHG. The verification of our hypotheses is based on a large data set consisting of over 550 b-f-m exponents and 120 power law hydraulic relations. The analysis highlights the role of uncertainties in data acquisition and theoretical/statistical explanations. In addition, the theoretical expressions of AHG also provide an explanation of at-many-stations hydraulic geometry (AMHG) in a physical sense. Overall, our work provides new insights into the fundamental theory of power laws and hydraulic geometry.

Wave-induced flooding is a major coastal hazard for the low-lying atolls of the Pacific. These flooding events are expected to increase over time, which may cause significant coastal damage in some locations. Coastal flooding analysis (forensic or forecasted) is particularly challenging in these small islands due to the co-occurrence of several swells and local seas propagating in a complex configuration of archipelagos. Therefore, assessing the contribution of swells and wind seas on the flooding hazards that threaten the atoll islands requires the spectral characterization of the wave climate, since integrated wave parameters do not accurately represent the wave conditions in these environments. On the other hand, the relative short records of wave conditions, represent only a small fraction of the possible range of combinations that could produce a wave-induced flooding event. For these reasons, we propose the analysis of all the spectral energy arriving toward a study site, by isolating and parameterizing each swell train. Then, taking into account the link with large-scale climatic patterns (i.e., El Niño Southern Oscillation), we present a new multi-modal seas emulator capable of generating infinitely long time series of synthetic individual swell trains and seas. This new climate-based emulator allows a better understanding of swell behavior in the Pacific, and the generation of multimodal wave conditions to populate the historical records as a key point to perform robust coastal flood risk assessments considering climate variability.

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.

Determining the characteristics of pipe flow and the effect of friction resistance is relevant to a variety of applications in hydraulic and hydrological engineering such as flood control, river restoration and ground runoff prediction. In the Nikuradse’s experiments, the relative roughness and the bulk Reynolds number are used to scale the Darcy friction factor thereby determining the mean velocity. Recent observations using permeable-walled pipes however indicate that the friction factor can significantly deviate from the results obtained in Nikuradse’s approach. Here, we propose a concise model to estimate the mean velocity of the pipe flow over permeable walls. The model is formulated using a data-driven approach based on the analytical solution of the mean velocity and the similarity analysis (dimension conservation) of the two extreme cases: impermeable and porous pipe flow. We show that the proposed approach can derive a physically meaningful formula for the mean velocity. Furthermore, we propose a simple momentum transfer model which confirms the findings from the data-driven approach. The momentum transfer model indicates that the friction factor can be scaled with two different relative hydraulics radius scales, which are intrinsically determined by two different eddy sizes. Lastly, the present approach is examined by comparing it with another approximate formula and the limited experimental data in the literature.

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 ...

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. T...

The global COVID-19 pandemic has seen extended lockdowns, isolation periods and travel restrictions across many countries around the world since early 2020. Some countries, such as Australia and New Zealand, closed their international borders in early 2020 preventing researchers travelling to other parts of the world. To facilitate the exposure of our students' work, and for them to meet international researchers, as well as foster a sense of coastal community, we started a zoominar series (seminars via Zoom) in April 2020. The Coast2Coast zoominar series had therefore humble origins but we soon discovered that there was an appetite for more widely sharing science across the coastal research disciplines. The Coast2Coast zoominar grew rapidly, attracting researchers from many countries around the world who presented and attended fortnightly online seminars. In just one year and a half we had 38 presentations with roughly 1900 attendees, creating a sense of community and belonging for the researchers involved. In early 2021, two of the co-authors, Giovanni (GC) and Ana (AVC) decided to expand and take this sense of community further creating the Coast2Cast podcast series, where researchers are asked research and non-research questions. In only 7 months, the podcasts have attracted more than 3700 listeners. Importantly, while the main prerequisite was high-quality and impactful research, diversity and inclusion were also a priority in selecting and inviting speakers for the zoominars and guests for the podcast. Importantly, our survey results suggest that there is a place for online events similar to Coast2Coast and Coast2Cast in a pandemic-free future, and that the coastal community involved has greatly benefited from such initiatives.

Buoyant plastics enter estuaries largely from urban streams and an unknown fraction is retained before further transport to the open ocean. Plastic drifters were launched in a well-mixed estuary to simulate the movement of surface buoyant plastics. Two experiments were conducted, one during spring tides and one during neap tides, both with similar river flows and winds. Stronger tidal currents during spring tides resulted in larger dispersion and further downstream transport of the drifters. Half of the drifters were grounded within two tidal cycles. During the neap experiment, even more of the drifters (87%) were retained in the estuary. The grounding of such a high proportion of drifters suggests that much of the plastic pollution in estuaries of this type remains close to the riverine source. These findings imply that local clean-up programs removing grounded litter can reduce over half of the plastic pollution input to these estuaries.

Coastal sediments, where microplastics (MPs) accumulate, support benthic microalgae (BMA) that contribute to ecosystem functions such as primary production, nutrient recycling and sediment biostabilization. The potential interactions between MPs, BMA and associated properties and functions remain poorly understood. To examine these interactions, a survey of 22 intertidal sites was conducted. MP abundance, size and a suite of MP diversity indices (based on color and shape) were determined from surface sediments alongside biochemical and physical properties. MPs were detected at all sites and dominated by polypropylene (34%), polyester (18%) and polyethylene (11%). Fragment and fiber dominance (16-92% and 6-81% respectively) and color-shape category diversity varied significantly by site. Distance-based linear models demonstrated that estuary-wide, mean grain size and mud were the best predictors of MP abundance-diversity matrices, but variance explained was low (9%). Relationships were improved when the data was split into sandy and muddy habitats. In sandy habitats (8% mud), physical properties of the bed (mean grain size, mud content and distance from the estuary mouth) were still selected as predictors of MP abundance-diversity (14% variance explained); but a number of bivariate relationships were detected with biochemical properties such as BMA associated pigments and organic matter. In muddy habitats (8% mud), porewater ammonium was lower when fiber abundance and overall MP diversity were higher. The inclusion of porewater ammonium, organic matter content and pheophytins alongside physical properties explained a greater percentage of the variance in MP abundance-diversity for muddy habitats (21%). The results highlight the importance of examining plastic shapes and MP categories in addition to abundance and emphasize that functionally different habitats should be examined separately to increase our understanding of MP-biota-function relationships.

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 timescales (e.g., multiannual), the shoreline changes may be superimposed on changes at shorter time-scales and thus are diffcult to identify. Here, we predict shoreline evolution from storm events to decadal timescales, 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).

A high resolution partitioned wave hindcast of New Zealand waters is presented together with validation results against 9 buoy deployments that are representative of the local wave climate. An analysis of integrated and partitioned mean wave parameters was conducted together with a study of the correlation between wave height anomalies and atmospheric indices. A directional spatial analysis was also performed to identify and quantify wave systems that are not detectable by in situ buoys or hindcast integrated parameters. The presented study outlines a framework of how partitions can be analyzed in order to improve our understanding of the local wave climate in terms of wind-sea and swell waves.

Reliable predictions and accompanying uncertainty estimates of coastal evolution on decadal to centennial time scales are increasingly sought. So far, most coastal change projections rely on a single, deterministic realization of the unknown future wave climate, often derived from a global climate model. Yet, deterministic projections do not account for the stochastic nature of future wave conditions across a variety of temporal scales (e.g., daily, weekly, seasonally, and interannually). Here, we present an ensemble Kalman filter shoreline change model to predict coastal erosion and uncertainty due to waves at a variety of time scales. We compare shoreline change projections, simulated with and without ensemble wave forcing conditions by applying ensemble wave time series produced by a computationally efficient statistical downscaling method. We demonstrate a sizable (site-dependent) increase in model uncertainty compared with the unrealistic case of model projections based on a single, deterministic realization (e.g., a single time series) of the wave forcing. We support model-derived uncertainty estimates with a novel mathematical analysis of ensembles of idealized process models. Here, the developed ensemble modeling approach is applied to a well-monitored beach in Tairua, New Zealand. However, the model and uncertainty quantification techniques derived here are generally applicable to a variety of coastal settings around the world.