Search

Changes in upstream land-use have significantly transformed downstream coastal ecosystems around the globe. Restoration of coastal ecosystems often focuses on local-scale processes, thereby overlooking landscape-scale interactions that can ultimately determine restoration outcomes. Here we use an idealized bio-morphodynamic model, based on estuaries in New Zealand, to investigate the effects of both increased sediment inputs caused by upstream deforestation following European settlement and mangrove removal on estuarine morphology. Our results show that coastal mangrove removal initiatives, guided by knowledge on local-scale bio-morphodynamic feedbacks, cannot mitigate estuarine mud-infilling and restore antecedent sandy ecosystems. Unexpectedly, removal of mangroves enhances estuary-scale sediment trapping due to altered sedimentation patterns. Only reductions in upstream sediment supply can limit estuarine muddification. Our study demonstrates that bio-morphodynamic feedbacks can have contrasting effects at local and estuary scales. Consequently, human interventions like vegetation removal can lead to counterintuitive responses in estuarine landscape behavior that impede restoration efforts, highlighting that more holistic management approaches are needed. Upstream land-use changes are transforming coastal environments around the globe. Mangrove removal aims at restoring estuarine ecosystems but counterintuitively enhances sediment trapping. More holistic management approaches are needed. [ABSTRACT FROM AUTHOR]

Topographic and bathymetric data are essential for accurate predictions of flooding in estuaries because water depth and elevation data are fundamental components of the shallow-water hydrodynamic equations used in models for storm surges and tides. Where lidar or in situ acoustic surveys are unavailable, recent efforts have centred on using satellite-derived bathymetry (SDB) and satellite-derived topography (SDT). This work is aimed at (1) determining the accuracy of SDT and (2) assessing the suitability of the SDT and SDB for extreme water level modelling of estuaries. The SDT was created by extracting the waterline as it tracks over the topography with changing tides. The method was applied to four different estuaries in Aotearoa / New Zealand: Whitianga, Maketū, Ōhiwa and Tauranga harbours. Results show that the waterline method provides similar topography to the lidar with a root-mean-square error equal to 0.2 m, and it is slightly improved when two correction methods are applied to the topography derivations: the removal of statistical bias (0.02 m improvement) and hydrodynamic modelling correction of waterline elevation (0.01 m improvement). The use of SDT in numerical simulations of surge levels was assessed for Tauranga Harbour in eight different simulation scenarios. Each scenario explored different ways of incorporating the SDT to replace the topographic data collected using non-satellite survey methods. In addition, one of these scenarios combined SDT (for intertidal zones) and SDB (for subtidal bathymetry), so only satellite information is used in surge modelling. The latter SDB is derived using the well-known ratio–log method. For Tauranga Harbour, using SDT and SDB in hydrodynamic models does not result in significant differences in predicting high water levels when compared with the scenario modelled using surveyed bathymetry. [ABSTRACT FROM AUTHOR]

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. [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]

We developed a new hindcast for storm surge at a 0.25° spatial scale for the whole New Zealand area using a statistical downscaling technique that links the mean local atmospheric conditions with the maximum storm surge levels at a daily scale. After validating the hindcast against sea level instrumental records from 17 tidal gauges around New Zealand, the same technique has been applied to obtain storm surge projections until 2,100 using different global climate models. The global climate models have been previously classified according to their ability to reproduce the past climatology in the studied area and seven models have been selected in order to explore their effect on storm surge projections. For the two representative Concentration Pathways studied, the projections indicate that the storm surge associated with the 50 years return period will increase in magnitude in the Southern areas while it will decrease in the Northern region. Even where a decreasing linear trend over the annual maxima is observed in the future time series, sporadic events of higher magnitude than the historical peaks can be. [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]

Understanding marine climate variability is important for coastal planning and marine operations. It is also particularly challenging for complicated settings (e.g., islands) and data‐poor regions. The aim of this work is to establish a relationship between daily synoptic atmospheric patterns, and wave and storm surge conditions around New Zealand waters, based on instrumental and reanalysis data. The daily predictor we developed is able to represent sea and swell wave conditions as well as storm surge variability over different temporal scales. However, when climate variability is analysed on a longer temporal period, based on the 20th century reanalysis, large inhomogeneities are found. This highlights the dangers related to assessing climate variability, especially in data‐poor regions (such as New Zealand), where inhomogeneities could be interpreted as actual changes. This work is conceived to present a general methodology to relate atmospheric conditions to regional wave and water level variables, which are drivers of coastal change. The established relationship allows to explore climate variability at different temporal scales. Our approach is general and leads to a relationship between waves and water levels with atmospheric conditions, which is envisaged to be a useful tool for the broad scientific community studying coastal changes. [ABSTRACT FROM AUTHOR]

The article presents a study that examined how incorporating restricted colonist dispersal decreases the range of spatial and temporal rates of disturbance under which benthic communities can persist, using model parameters representative of a New Zealand marine biogenic-structured community. Researchers used a spatially explicit patch dynamic model to show the interaction of the disturbance regime and colonization processes in regulating community dynamics and landscape structure in marine benthic systems. They concluded that the scale of the disturbance regime and dispersal processes are fundamentally coupled, and knowing the scales of both processes is important in predicting change in the structure and diversity of benthic communities threatened by cumulative change.

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: 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]

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: 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]

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. • Two new online initiatives provided unexpected benefits during the COVID-19 pandemic. • Both initiatives contributed to creating a sense of community and belonging for the researchers involved. • The main prerequisite was high-quality and impactful research. • Diversity and inclusion were considered a priority, thus increasing diversity and inclusion. • Our results suggest that there is a place for short online events in a pandemic-free future. [ABSTRACT FROM AUTHOR]

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. • A new hindcast of New Zealand is presented and its partitioned data is explored. • The spatial distribution of wind-sea and swells parameters was extensively analyzed. • Atmospheric indices were found to modulate wind-seas and swells in different ways. • The relationship between wind-seas, swells and spectral partitioning was depicted. • This analysis can help the understanding of other complex wave climates worldwide. [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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)