Abstract. Climate warming is leading to the erosion of Arctic permafrost coastlines at accelerating rates, with erosion up to 20 m yr−1 along the Alaska Beaufort Sea. Yet, accurate predictions of this erosion require coupling thermal permafrost dynamics with coastal hydro-morphodynamics, and current models are either computationally prohibitive for long-term simulations or omit important physical processes. To address these issues, a new open-source Python-based model called Arctic-XBeach was developed to couple the morphodynamic model XBeach to a one-dimensional enthalpy-based thermal module. A focus of this first version of Arctic-XBeach is on thermal denudation, the dominant erosion mechanism at sites where elevated beaches limit direct wave–bluff contact. Unlike prior implementations of thermal modules coupled with morphodynamic models, ArcticXBeach uses an event-driven decoupling strategy. Specifically, the thermal module continues to calculate the evolution of the thawed layer during the year, but the morphodynamic module (XBeach) is only activated when simulated storms produce conditions under which thawed sediment is available for removal. Using this decoupled strategy results in a reduction of >99 % in the number of calculations required for each time step in comparison to continuous coupling of the two modules. Validation of the model was performed at Barter Island, Alaska. Observed temperature trends were well-reproduced by the model (RMSE < 1.5 K), and the modeled trends in shoreline & bluff recession matched the observed trends (RMSE of 2.0–4.1 m over evaluation periods spanning 2–3 years each, compared to a total observed retreat of ∼112 m over 70 years with peaks of 6.6 m yr−1). Therefore, Arctic-XBeach has the potential to be used to run seasonal to decadal simulations of thermal- denudation dominated permafrost coastal changes, and also provides a flexible platform to integrate other Arctic-specific processes. Thermal abrasion and block-failure processes are planned as future extensions.

Luminescence dating methods are widely used to date coastal sediments, while luminescence tracing methods are a novel application to reconstruct coastal sediment pathways. Both methods rely on subaqueous resetting (bleaching) of luminescence signals by light. Differences in bleaching between grains and/or luminescence signals encode information on the light exposure history of individual grains and therefore yield information on past sediment transport. Here we assess the potential of multi-signal single-grain feldspar luminescence to inform about sediment pathways at Ameland tidal inlet in the Dutch Wadden Sea. We also tested whether nourished and native sands can be distinguished based on their luminescence signals.Single-grain infrared stimulated luminescence (IRSL50) and post-IR IRSL (pIRIR) were measured from samples collected from modern sea-floor deposits across the inlet. Equivalent dose (De) distributions were assessed using the Central Age Model (CAM), and bootstrapped versions of the Minimum Age Model (bMAM) and Maximum Age Model (bMAX) were applied to the IRSL50 De distributions. Spatial trends in CAM and bMAX-De reveal highest inherited doses at the tip of Ameland in the Borndiep channel, decreasing along transport pathways around the ebb-tidal delta. These patterns indicate erosion of Pleistocene sediments in the Borndiep channel and progressive bleaching of luminescence signals upon transport. Low De values in shallow areas reflect repeated reworking of Holocene sands within the active layer. Nourished and native sediments show indistinguishable luminescence characteristics for our dataset due to their shared Holocene origin.

In the face of climate change, sea level rise, and increased human development on coasts and deltas, better quantification and understanding of coastal sediment transport is essential. Specifically, we need to know more about sediment pathways for system understanding and planning interventions (e.g., nourishments or beneficial reuse of dredged material). Sediment transport models like Delft3D or XBeach adopt an Eulerian (fixed-grid) approach, which is useful for quantifying rates of sediment transport and morphodynamic change. However, tracking the fate of sediment from specific sources using these models is complex and computationally expensive. To better simulate the pathways that sediment takes, we can adopt a Lagrangian (particle-tracking) approach, as is common in oceanographic and water quality studies. To fill these gaps, we present SedTRAILS (Sediment TRAnsport vIsualization and Lagrangian Simulator), a general-use process-based particle tracking model that is fast and easy to use for the coastal community. SedTRAILS provides a suite of analysis tools for better understanding and visualizing sediment pathways. what is special is also how we use it (e.g. querying particle fields to ask management questions, connectivity analysis).

Abstract. Sediment transport and seabed composition can both be influenced by bioturbation and hydrodynamically driven sediment mixing and deposition. In a dynamic intertidal environment, it is challenging to distinguish the relative contribution of both processes. We aim to unravel their relative importance by combining several tracers, each having its own specific timescale and target particle size. We combined (1) 210Pb that quantifies long-term (years–decades) mixing of fine sediment fractions with (2) Chlorophyll-a and (3) luminophores that both quantify short-term mixing of fine sediment fractions (days–weeks), and (4) multi-grain quartz and single-grain feldspar luminescence dating, which use the bleaching of sand grains’ inherent luminescence signal by light to assess mixing of sand and thereby quantifies long-term mixing. Single grain feldspar luminescence is here for the first time applied in the intertidal environment. We compare results for a sandy and a muddy intertidal flat at the island of Texel (Wadden Sea, the Netherlands), each with their own characteristic benthic community. Recent bioturbation became apparent from Chlorophyll-a and luminophore profiles: particles were rapidly reworked to a depth of decimetres. 210Pb also suggested mixing and non-local exchange of particles by bioturbation. Luminescence age distributions suggest that quartz luminescence signals were fully reset upon recent deposition, while bioturbation enhanced resetting of feldspar luminescence signals. Coarse- and fine-grained tracer profiles show the differential behaviour and reworking of the mud and sand fraction within the sediment matrix: as expected with particle-selective bioturbation, mud is preferentially bioturbated and infiltrates passively, while sand grains have a higher ability to conserve layering. Single-grain feldspar luminescence is a promising technique to demonstrate the long-term reworking of sand grains, however, in young and dynamic environments, a combination of tracers remains necessary to inform on the origin of mixing.

Abstract. Low-lying, tropical coral reef-lined coastlines are becoming increasingly vulnerable to wave-driven flooding due to population growth, coral reef degradation, and sea-level rise. Early-warning systems (EWS) are needed to enable coastal authorities to issue timely alerts and coordinate preparedness and evacuation measures for their coastal communities. At longer time scales, risk management and adaptation planning require of robust assessments of future flooding hazard considering uncertainties. However, due to diversity in reef morphologies and complex reef hydrodynamics compared to sandy shorelines, there have been no robust, analytical solutions for wave runup to allow the development of large-scale coastal wave-driven flooding EWS and risk assessment frameworks for reef-lined coasts. To address the need for a fast, robust prediction of runup along reef-lined coasts, we constructed the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process modeling system. We developed this meta-process model using a training dataset of hydrodynamics and wave runup computed by the XBeach Non-Hydrostatic+ process-based hydrodynamic model for 440 combinations of water level, wave height, and wave period on 195 morphologically diverse representative reef profiles. In validation, the BEWARE-2 modeling system produced runup results that had a root-mean square error of 0.63 m and bias of 0.26 m, relative to runup of 0.17–20.9 m simulated by XBeach Non-Hydrostatic+ for a large range of oceanographic forcing conditions and for a diverse reef morphologies. Incorporating parametric modifications in the modeling system to account for variations in reef roughness and beach slope allows systematic errors (relative bias) in BEWARE-2 predictions to be reduced by a factor of 1.5–6.5 for relatively coarse or smooth reefs, and mild or steep beach slopes. This relatively accurate solution is provided by the BEWARE-2 modeling system 4–5 orders of magnitude faster than the full, process-based hydrodynamic model and could therefore be integrated in large-scale EWS for tropical, reef-lined coasts, as well as used for large-scale flood risk assessments.

Abstract Optical turbidity and acoustic sensors have been widely used in laboratory experiments and field studies to investigate suspended particulate matter concentration over the last four decades. Both methods face a serious challenge as laboratory and in‐situ calibrations are usually required. Furthermore, in coastal and estuarine environments, the coexistence of mud and sand often results in multimodal particle size distributions, amplifying erroneous measurements. This paper proposes a new approach of combining a pair of optical turbidity‐acoustic sensors to estimate the total concentration and sediment composition of a mud/sand mixture in an efficient way without an extensive calibration. More specifically, we first carried out a set of 54 bimodal size regime experiments to derive empirical functions of optical‐acoustic signals, concentrations, and mud/sand fractions. The functionalities of these relationships were then tested and validated using more complex multimodal size regime experiments over 30 optical‐acoustic pairs of 5 wavelengths (420, 532, 620, 700, 852 nm) and six frequencies (0.5, 1, 2, 4, 6, 8 MHz). In the range of our data, without prior knowledge of particle size distribution, combinations between optical wavelengths 620–700 nm and acoustic frequencies 4–6 MHz predict mud/sand fraction and total concentration with the variation <10% for the former and <15% for the later. The results also suggest that acoustic‐acoustic signals could be combined to produce meaningful information regarding concentration and mud/sand fraction, while no useful knowledge could be extracted from a combination of optical‐optical pairs. This approach therefore enables the robust estimation of suspended sediment concentration and composition, which is particularly practical in cases where calibration data is insufficient.

Multiple tidal inlet systems like the Wadden Sea have long been considered as separated basins, bordered by so-called tidal divides. Recently, it was however shown that fluxes of water and sediment occur over the borders of these basins, especially during wind events. In this paper, the wind-driven fluxes over these borders and the residual flow of water through the main inlet are studied. The study is based on flow measurements at the tidal divides and in the main inlet of the Ameland Inlet system in the Dutch Wadden Sea and on numerical modelling. The measurements were carried out during 40 days in the fall of 2017, including both calm conditions and storm events. Numerical simulations of a full year have been used for upscaling results from the measurements to system scale exchange flows, and to unravel the effects of several mechanisms. The wind-driven variability in exchange flows between back-barrier basins at tidal divides was measured in the field and reproduced by the numerical model. Water level set up increases the water depth and thus the conveyance capacity at tidal divides, such that the exchange flows increase in magnitude. The flow conditions due to wind forcing are similar for both tidal divides of the Ameland Basin. The conveyance capacity and therefore the total volume exchange are however different. This leads to a residual compensation flow through the main inlet, which is directed outward (i.e., in the ebb direction) during winds from the prevailing southwestern wind direction. The net discharge through the main inlet is therefore a consequence of the residual flows over the tidal divides.

Many coral reef islands are low-lying, which in combination with population growth, sea level rise and possibly more frequent extreme weather events is likely to result in increased coastal risk (e.g. Storlazzi et al., 2015). On smaller scales of O(10 km) wave-driven coastal inundation can be accurately predicted with advanced models such as XBeach (Roelvink et al., 2009), at already high computational costs. For larger scales, larger number of islands, for scenario modelling, and for implementation in early warning systems, computationally faster methods are needed. Reduced physics models, which neglect some of the processes (e.g. non-hydrostatic pressure gradient term and viscosity), are a potential solution. However, their accuracy and the best method to force them has not been established. In this research we propose a new methodology to model wave-driven flooding on coral reef-lined coasts. A look-up-table (LUT), composed of XBeach model runs, is combined with a reduced-physics model, SFINCS (Leijnse et al., 2021), to achieve high accuracy predictions at limited computational expense. The LUT consists of pre-run 1D XBeach simulations for several reef profiles from Scott et al. (2020), forced with different offshore wave and water level conditions. Wave conditions close to the shore as predicted by the LUT are used to force SFINCS which then simulates the wave runup, overtopping and flooding. These are forced in SFINCS using random wave timeseries from an interpolated parameterized wave spectrum following Athif (2020). The accuracy of the method is investigated for 6 distinctive cross-shore profiles from Scott et al. (2020), for two wave scenarios (gentle swell and stormy conditions). Results of complete XBeach simulations are compared to LUT-SFINCS simulations with different boundary forcing locations. The sensitivity analysis shows that the preferred boundary location to initialize the SFINCS model is at a water depth between 0.5 m and 2.5 m, preferably shoreward of the reef edge. Errors introduced by the generated parameterized spectra lead to runup estimation errors of up to around 40% depending on reef geometry. The developed methodology will be applied to a case study of Majuro Island, the Republic of Marshall Islands, as proof of concept. References Athif, A. A. (2020). Computationally efficient modelling of wave driven flooding in Atoll Islands: Investigation on the use of a reduced-physics model solver SFINCS. Master’s thesis, IHE, the Netherlands. Leijnse, T., van Ormondt, M., Nederhoff, K., and van Dongeren, A. (2021). Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind-and wave- driven processes. Coastal Engineering, 163:103796. Roelvink, D., Reniers, A., Van Dongeren, A. P., De Vries, J. V. T., McCall, R., and Lescinski, J. (2009). Modelling storm impacts on beaches, dunes and barrier islands. Coastal engineering, 56(11-12), 1133-1152. Scott, F., Antolinez, J. A. A., Mccall, R., Storlazzi, C., Reniers, A., and Pearson, S. (2020). Hydro-Morphological Characterization of Coral Reefs for Wave Runup Prediction. Frontiers in Marine Science, 7(May):1–20. Storlazzi, C. D., Elias, E. P., and Berkowitz, P. (2015). Many atolls may be uninhabitable within decades due to climate change. Scientific reports, 5:14546.

Many coral reef-lined coasts are low-lying with elevations <4 m above mean sea level. Climate-change-driven sea-level rise, coral reef degradation, and changes in storm wave climate will lead to greater occurrence and impacts of wave-driven flooding. This poses a significant threat to their coastal communities. While greatly at risk, the complex hydrodynamics and bathymetry of reef-lined coasts make flood risk assessment and prediction costly and difficult. Here we use a large (>30,000) dataset of measured coral reef topobathymetric cross-shore profiles, statistics, machine learning, and numerical modeling to develop a set of representative cluster profiles (RCPs) that can be used to accurately represent the shoreline hydrodynamics of a large variety of coral reef-lined coasts around the globe. In two stages, the large dataset is reduced by clustering cross-shore profiles based on morphology and hydrodynamic response to typical wind and swell wave conditions. By representing a large variety of coral reef morphologies with a reduced number of RCPs, a computationally feasible number of numerical model simulations can be done to obtain wave runup estimates, including setup at the shoreline and swash separated into infragravity and sea-swell components, of the entire dataset. The predictive capability of the RCPs is tested against 5,000 profiles from the dataset. The wave runup is predicted with a mean error of 9.7–13.1%, depending on the number of cluster profiles used, ranging from 312 to 50. The RCPs identified here can be combined with probabilistic tools that can provide an enhanced prediction given a multivariate wave and water level climate and reef ecology state. Such a tool can be used for climate change impact assessments and studying the effectiveness of reef restoration projects, as well as for the provision of coastal flood predictions in a simplified (global) early warning system.

Waves are important drivers for reef hydrodynamics, and therefore strongly contribute to flooding over reef-lined coasts. While high-frequency waves are largely dissipated when they propagate over the reef flat due to breaking and friction, low-frequency (LF) waves are generally able to reach the back-reef beach. There, they can reflect and form (quasi-) standing wave patterns, which under resonant conditions can lead to disproportionally high run-up on the beach (e.g., Pequignet et al., 2009; Gawehn et al., 2016). The probability of this phenomenon is expected to increase due to sea-level rise (e.g., Pequignet et al., 2009). In this study, we numerically investigate long wave resonance and the processes enhancing or limiting the resonant amplification of long waves over the reef flat. Besides the role of frictional dissipation (e.g., Pomeroy et al. 2012), we investigate how the nonlinear transformation of long waves influences the amplification rate.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/caZcI8YYs0I

First posted May 29, 2020 For additional information, contact: Contact InformationPacific Coastal & Marine Science CenterU.S. Geological SurveyPacific Science Center2885 Mission St.Santa Cruz, CA 95060 Bathymetric and topographic surveys performed annually along the coastlines of northern Oregon and southwestern Washington documented changes in beach and nearshore morphology between 2014 and 2019. Volume change analysis revealed measurable localized erosion and deposition throughout the study area, but significant net erosion at the regional scale (several kilometers [km]) was limited to Benson Beach, Wash., a 3-km-long stretch of coastline immediately north of the Columbia River inlet. Despite the placement of approximately 6.3 million cubic meters (Mm3) of sand dredged from the Columbia River navigational channel at nearshore placement sites located nearby, Benson Beach eroded 2.1±0.8 Mm3 over the 5-year (yr) monitoring time period (420,000 cubic meters/year [m3/yr]). A hydrodynamic and sediment transport model was applied to simulate sediment transport fluxes, and a new visualization technique was developed to evaluate the linkages between nearshore dredge placement sites and adjacent coastlines near the mouth of the Columbia River. The model results indicate the dominance of wave processes on sediment-transport patterns outside of the inlet and suggest that the current configuration of the nearshore dredge placement sites can be improved to more efficiently enhance the sediment budget of Benson Beach to reduce erosion and mitigate associated coastal change hazards.

This paper presents an application of the Bayesian belief network for coastal erosion management at the regional scale. A “Bayesian ERosion Management Network” (BERM-N) is developed and trained based on yearly cross-shore profile data available along the Holland coast. Profiles collected for over 50 years and at 604 locations were combined with information on different sand nourishment types (i.e., beach, dune, and shoreface) and volumes implemented during the analyzed time period. The network was used to assess the effectiveness of nourishments in mitigating coastal erosion. The effectiveness of nourishments was verified using two coastal state indicators, namely the momentary coastline position and the dune foot position. The network shows how the current nourishment policy is effective in mitigating the past erosive trends. While the effect of beach nourishment was immediately visible after implementation, the effect of shoreface nourishment reached its maximum only 5–10 years after implementation of the nourishments. The network can also be used as a predictive tool to estimate the required nourishment volume in order to achieve a predefined coastal erosion management objective. The network is interactive and flexible and can be trained with any data type derived from measurements as well as numerical models.

Rennix Gap Bog is a sub-alpine topogenic peatland that contains up to 2 m of organic-rich sediments that have built up over the last approximately 12,000 years. This paper summarises the research and teaching activities that have been undertaken at the site, which has included consideration of the sediment stratigraphy, radiometric dating, palynology, charcoal analyses, dendrochronology and recently, the testate amoebae community composition has been documented. Much of this work is unpublished but has relevance for any future research and provides a long-term context for many contemporary environmental issues, including for issues of relevance to the management of fire in this landscape and vegetation more broadly. In the contemporary environment, the surface of the bog is vegetated with a complex mosaic of Carex fen, sub-alpine Sphagnum shrub bog and Poa costiniana tussock grassland. Pollen analysis suggests that this vegetation has been relatively stable for 10,000 years and prior to that the site was surrounded by sparse vegetation, similar to the alpine herb-grass community of contemporary higher altitude ecosystems. Charcoal analyses suggest that fire activity has varied through time but increased significantly in the historic period. Rennix Gap Bog has not only attracted considerable research but has also been an invaluable, accessible, site for field-based teaching and learning.

The assessment of coastal flood risk on a reef-lined coastline presents several challenges.From the probabilistic side, we need to consider all possible events that could occur in the system, taking into account the different contributions of waves, storm surges, and tides that contribute to the total water level.To estimate reliable flood extents, we need to accurately model the complex wave processes that occur across the reef.To explore the multivariate nature of coastal flooding, we rely on a climate emulator that accounts for climate variability and simulates time series of all the variables involved.Due to the computational constraints to numerically simulate thousands of events, we explore the feasibility of using a recently developed tool, the HyCreWW (Hybrid Coral Reef Wave and Water level) meta-model to estimate wave run-up and flooding extents.Limitation of a 1D assessment are analyzed and results compared with 2D modeling.