Lagoon water-level oscillations driven by rainfall and wave climate

Barrier breaching and subsequent inlet formation represent critical processes that ensure the temporary or permanent connection and transference of water, nutrients, or living organisms between a lagoon and the open sea. Here, we investigate the conditions inducing natural barrier breaching through a 34 months monitoring program of water-level oscillations within a shallow lagoon and the adjacent nearshore, at the Northern coast of the Iberian Peninsula, Louro lagoon. Seven natural openings were identified to have occurred during the three monitored wet seasons, from the 2009 to 2012, (Wet1, Wet2 and Wet3); four in the Wetl, two in the Wet2 and one in. the Wet3. The openings were grouped in three types depending on the observed relation between the lagoon water-level (L-wl), the estimated berm height (B-h) and the water-level at the beach (B-wl): (i) openings by lagoon outflow, which include those characterized by L-wl higher than B-h and lower B-wl; (ii) openings by wave inundation, including those induced by B-wl higher than B-h, and (iii) mixed openings, which result from a combination of the two previous conditions. We observed that L-wl is modulated by the rainfall regime (R-f) and can be explained by the accumulated precipitation. We estimated applying runup equations to obtain B-h and B-wl which depend on the wave climate and tidal level. The inlet lifespan was found to be regulated by the wave climate and rainfall regime; in particular barrier sealing was associated with a sudden increase in wave period and a reduction in precipitation. This work proves that the natural openings could be predicted successfully with support to medium term water-level monitoring programs, which in turn may significantly contribute to strategic decision making for management and conservation purposes.Xunta de Galicia [08MDS036000PR, PlanI2C-ED481B 2014/132-0]MICINN [CTM2012-39599-C03-01]Portuguese Science Foundation [IF/01047/2014]info:eu-repo/semantics/publishedVersio

Prediction of overwash in alongshore variable barrier islands [Previsão da ocorrência de galgamentos em ilhas barreira com variabilidade longilitoral]

Overwash prediction is very important for coastal zone management. This work intends to identify alongshore variations in storm impact and evaluate the role of sub-aerial and submerged morphologies in overwash occurrence. For this study, 24 cross-shore topo-bathymetric profiles were set on Barreta Island (Ria Formosa barrier island system, Portugal). Pre- and post-overwash surveys were made between August 2012 and April 2013. During overwash events, tidal levels and wave parameters at breaking were obtained. Overwash occurred under storm and non-storm conditions, the latter coincident with spring high-tide. Beach morphology was spatially variable, and changeable from one overwash episode to the next. Predictions of overwash occurrence were made using the Overwash Potential, defined as the difference between runup and barrier elevation. Several runup equations were tested, and the results compared to the actual observations. The selected predictor provided an accuracy of 88% for the identification of the locations where overwash occurred. This study proves that nearshore and foreshore morphologies have a major impact on the longshore distribution of overwash.info:eu-repo/semantics/publishedVersio

Response of wave-dominated and mixed-energy barriers to storms

EPSRC funded EP/I035390/1 The full text is under embargo until 15.05.15

Comparing coastal storm impact to decadal change in barrier island ecosystems

Highly dynamic coastal systems respond to disturbance events with a combination of topographic and vegetative changes. Sea level rise impacts on barrier islands have been quantified, but storm effects on vegetation are limited. Here we quantified barrier island vegetation change in response to an isolated storm event and compared to long-term periods. We hypothesized that disturbance-resisting areas with high woody vegetation cover and/or high foredune elevation would experience minimal transitions after a storm event, whereas disturbance-reinforcing areas with low vegetation cover and low foredune elevation would experience greater transitions between ecosystem states after a storm event. Patterns of dissonance were found at the island-scale, as net loss of woodland cover occurred during the storm and a net gain occurred through decadal regimes, indicative of a slow growing late successive vegetation responding to disturbance. Using sub-islands transects, significant correlations between stable upland vegetation covers (both woodland and grassland) and percent bare suggests that the amount of upland land cover may be important in upland community response to storm events. Maximum bare elevation was significantly correlated to woodland cover, indicative of disturbance resisting domains. Significant correlations found between pre-storm woodland cover (both area and percent) and non-changing grasslands suggest that the existence of woody vegetation is dependent on the establishment and extent of stable grasslands. No correlations were found with area of marshland converted to upland post storm. My results did not fully support my hypothesis but document upland vegetation interactions with elevation amidst a moderate coastal storm

Characterizing storm-induced coastal change hazards along the United States West Coast

Traditional methods to assess the probability of storm-induced erosion and flooding from extreme water levels have limited use along the U.S. West Coast where swell dominates erosion and storm surge is limited. This effort presents methodology to assess the probability of erosion and flooding for the U.S. West Coast from extreme total water levels (TWLs), but the approach is applicable to coastal settings worldwide. TWLs were derived from 61 years of wave and water level data at shore-perpendicular transects every 100-m along open coast shorelines. At each location, wave data from the Global Ocean Waves model were downscaled to the nearshore and used to empirically calculate wave run-up. Tides were simulated using the Oregon State University?s tidal data inversion model and non-tidal residuals were calculated from sea-surface temperature and pressure anomalies. Wave run-up was combined with still water levels to generate hourly TWL estimates and extreme TWLs for multiple return periods. Extremes were compared to onshore morphology to determine erosion hazards and define the probability of collision, overwash, and inundation

Process-based indicators to assess storm induced coastal hazards

Storms are responsible for several hazards (e.g. overwash, erosion, inundation) in coastal areas, leading to the destruction of property and loss of life in populated areas. Various indicators are used to express potential storm impact and describe the associated hazards. The most commonly used indicators include either forcing parameters (e.g. wave height, sea level) or coastal morphologies (e.g. dune height or berm width). Whereas they do not represent the processes associated with storm induced hazards in coastal areas. Alternatively, a hazard could be better characterised if process-based indicators are used instead. Process-based indicators express the result of the forcing mechanisms acting over the coastal morphology and reflect both hydrodynamic and morphological characteristics. This work discusses and synthesizes the most relevant process-based indicators for sandy shores subject to overwash, erosion and inundation promoted by storms. Those include: overwash depth, potential and extent; shoreline, berm or dune retreat; vertical erosion; and inundation depth and extent. The selection of a reduced set of process-based indicators to identify coastal hazards induced by storms in sandy coasts will facilitate comparison of different coastal behaviours for distinct storm return periods, and help to optimise coastal management plans, thereby contributing to the reduction of coastal risks.info:eu-repo/semantics/publishedVersio

Dynamic allometry in coastal overwash morphology

Allometry refers to a physical principle in which geometric (and/or metabolic) characteristics of an object or organism are correlated to its size. Allometric scaling relationships typically manifest as power laws. In geomorphic contexts, scaling relationships are a quantitative signature of organization, structure, or regularity in a landscape, even if the mechanistic processes responsible for creating such a pattern are unclear. Despite the ubiquity and variety of scaling relationships in physical landscapes, the emergence and development of these relationships tend to be difficult to observe - either because the spatial and/or temporal scales over which they evolve are so great or because the conditions that drive them are so dangerous (e.g. an extreme hazard event). Here, we use a physical experiment to examine dynamic allometry in overwash morphology along a model coastal barrier. We document the emergence of a canonical scaling law for length versus area in overwash deposits (washover). Comparing the experimental features, formed during a single forcing event, to 5 decades of change in real washover morphology from the Ria Formosa barrier system, in southern Portugal, we find differences between patterns of morphometric change at the event scale versus longer timescales. Our results may help inform and test process-based coastal morphodynamic models, which typically use statistical distributions and scaling laws to underpin empirical or semi-empirical parameters at fundamental levels of model architecture. More broadly, this work dovetails with theory for landscape evolution more commonly associated with fluvial and alluvial terrain, offering new evidence from a coastal setting that a landscape may reflect characteristics associated with an equilibrium or steady-state condition even when features within that landscape do not.Funding Agency NERC Natural Environment Research Council NE/N015665/2 Leverhulme Trust RPG-2018-282info:eu-repo/semantics/publishedVersio

Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goldstein, E. B., Buscombe, D., Lazarus, E. D., Mohanty, S. D., Rafique, S. N., Anarde, K. A., Ashton, A. D., Beuzen, T., Castagno, K. A., Cohn, N., Conlin, M. P., Ellenson, A., Gillen, M., Hovenga, P. A., Over, J.-S. R., Palermo, R., Ratliff, K. M., Reeves, I. R. B., Sanborn, L. H., Straub, J. A., Taylor, L. A., Wallace E. J., Warrick, J., Wernette, P., Williams, H. E. Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement. Earth and Space Science, 8(9), (2021): e2021EA001896, https://doi.org/10.1029/2021EA001896.Classifying images using supervised machine learning (ML) relies on labeled training data—classes or text descriptions, for example, associated with each image. Data-driven models are only as good as the data used for training, and this points to the importance of high-quality labeled data for developing a ML model that has predictive skill. Labeling data is typically a time-consuming, manual process. Here, we investigate the process of labeling data, with a specific focus on coastal aerial imagery captured in the wake of hurricanes that affected the Atlantic and Gulf Coasts of the United States. The imagery data set is a rich observational record of storm impacts and coastal change, but the imagery requires labeling to render that information accessible. We created an online interface that served labelers a stream of images and a fixed set of questions. A total of 1,600 images were labeled by at least two or as many as seven coastal scientists. We used the resulting data set to investigate interrater agreement: the extent to which labelers labeled each image similarly. Interrater agreement scores, assessed with percent agreement and Krippendorff's alpha, are higher when the questions posed to labelers are relatively simple, when the labelers are provided with a user manual, and when images are smaller. Experiments in interrater agreement point toward the benefit of multiple labelers for understanding the uncertainty in labeling data for machine learning research.The authors gratefully acknowledge support from the U.S. Geological Survey (G20AC00403 to EBG and SDM), NSF (1953412 to EBG and SDM; 1939954 to EBG), Microsoft AI for Earth (to EBG and SDM), The Leverhulme Trust (RPG-2018-282 to EDL and EBG), and an Early Career Research Fellowship from the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (to EBG). U.S. Geological Survey researchers (DB, J-SRO, JW, and PW) were supported by the U.S. Geological Survey Coastal and Marine Hazards and Resources Program as part of the response and recovery efforts under congressional appropriations through the Additional Supplemental Appropriations for Disaster Relief Act, 2019 (Public Law 116-20; 133 Stat. 871)

Modeling the response of a beach restoration project in Louisiana to two consecutive hurricanes

The current study is concentrated in modeling the cross-shore beach profile evolution and severe erosion of the dune (overwash) of a restored barrier island due to Hurricanes Gustav (2008) and Ike (2008) in coastal Louisiana. Pre-storm and post-storm survey data sets of Chaland Headland located in Plaquemines Parish, LA, were analyzed and categorized based on the overwash processes, and numerically modeled using SBEACH (Storm-induced BEAch CHange). The model results were compared with the measured topographic data. A total of 10 survey profiles were used in this study. SBEACH simulates cross-shore beach, berm and dune erosion produced by storm waves and water levels. The model was calibrated for site specific conditions; sensitivity tests were conducted with varying water levels, wave heights and median grain sizes. Hurricanes Gustav and Ike forcing conditions were applied and the model profiles were then compared with survey profiles. It was found that, although SBEACH is capable of reproducing the shape of the post-storm profiles to some extent, the amount of measured erosion on the foreshore slopes of the measured beach profile is much greater than the modeled erosion. Dune erosion of the measured profiles is also greater than the modeled profiles. It is also found that some of the empirical parameters of SBEACH need to be adjusted beyond the recommended values to obtain better simulation results. SBEACH does not account for any longshore sediment transport due to longshore currents. Also the surge level gradient across the profile is not considered in the model. In general, the beach profile evolution processes are three-dimensional and complex. Although a one dimensional model could be a helpful tool in the preliminary stages of a project to estimate the shape of the post-storm profile, the three dimensional effects should be considered to obtain accurate results, in particular under hurricane conditions

Morphological changes, beach inundation and overwash caused by an extreme storm on a low-lying embayed beach bounded by a dune system (NW Mediterranean)

The geomorphological evolution of a low-lying, micro-tidal sandy beach in the western Mediterranean, Pals beach, was characterized using airborne Light Detection and Ranging (LiDAR) data. Data were collected in prior to and six months after the impact of an extreme storm with a return period of approx. 50 years, with the aim of characterizing the beach's response to the storm. The use of repeated high-resolution topographic data to quantify beach geomorphic changes has allowed assessment of the accuracy of different proxies for estimating beach volume changes. Results revealed that changes in the shoreline position cannot accurately reproduce beach volume changes on low-lying beaches where overwash processes are significant. Observations also suggested that volume estimations from beach profiles do not accurately represent subaerial volume changes at large profile distances on beaches with significant alongshore geomorphological variability. Accordingly, the segmentation of the beach into regularly spaced bins is proposed to assess alongshore variations in the beach volume with the accuracy of the topographic data. The morphological evolution of Pals beach during the study period showed a net shoreline retreat (- 4 m) and a significant sediment gain on the subaerial beach (+ 7.5 m3/m). The net gain of sediment is mostly due to the impact of the extreme storm, driving significant overwash processes that transport sediment landwards, increasing volume on the backshore and dunes. The increase of volume on the foreshore and the presence of cuspate morphologies along the shoreline also evidence post-storm beach recovery. Observed morphological changes exhibit a high variability along the beach related to variations in beach morphology. Changes in the morphology and migration of megacusps result in a high variability in the shoreline position and foreshore volume changes. On the other hand, larger morphological changes on the backshore and larger inundation distances occur when the beach and the dunes are lower, favouring the dominance of overwash. The observed storm-induced morphological changes differ from predicted beach storm impacts because of spatial and temporal variations in the beach morphology, suggesting that detailed morphological parameters and indicators used for predicting beach vulnerability to storms should be regularly updated in order to represent the pre-storm beach conditions. Finally, observed morphological changes in Pals Bay evidenced a different behaviour between natural and urban areas, with better post-storm beach recovery on natural areas where the beach is not artificially narrowed.Peer ReviewedPostprint (author's final draft