Geology topics

Margaret L. Palmsten

Publications and source records attributed to Margaret L. Palmsten.

At least 19 recordsLinked to original sources

USGS2026

Effects of storm surge exceedance value on overwash and inundation forecasts

Hurricane induced sediment transport and flooding can cause catastrophic damage to coastal communities. Forecasts test our understanding of the drivers of sediment transport and flooding, as well as quantify potential storm effects on coastlines. Real-time availability of forecasts allows emergency response and management decisions to be made with additional information. This study analyzed the skill of probabilistic forecasts of overwash and inundation along the Louisiana coastline from back-to-back Hurricanes Laura and Delta in 2020. To test skill, forecasts were compared with observations of mean water level relative to beach elevations and evidence of overwash and inundation identified in post-storm aerial imagery. We found that probabilistic forecasts accurately identified areas where overwash and inundation were likely to occur. In some cases, forecasts also produced a conservative estimation of overwash and inundation. For the first time, we explored the role of exceedance value in probabilistic forecasts of overwash and inundation and found that choice of exceedance value can influence forecasts. Additionally, we found that waves contributed up to 27% of the mean water level and up to 63% of the extreme water level during Hurricanes Laura and Delta.

Louisiana, Texas↗

USGS2026

Decadal-scale characteristics of natural and anthropogenic dune morphology along North Carolina Barrier Islands (SE Atlantic Coast)

Dunes offer protection to coastal communities from storms, yet quantitative research characterizing human influences on dune systems across decades and 10–100 km spatial scales constitutes a known data gap. This study analyzed a multidecadal archive of dune crest elevations and positions to map mesoscale spatiotemporal trends in foredune morphology across the barrier island coastline of North Carolina, SE Atlantic coast. Results are summarized within four categories of coastline representing a range of coastal management intensities, integrating beach width and dune lateral accommodation space to assess the comparative influence of differing intensities of anthropogenic intervention on dune morphology. These categories account for the presence of structures, roads, and alongshore connectivity to anthropogenic sediment sources (beach nourishment). These categories show distinct dune and beach system characteristics. Dunes are largest in the areas with the longest legacy of coastal management. As categories decrease in development intensity, dune and beach system characteristics generally depart from the large, static dunes and narrow beaches consistent with hold-the-line management. Where small or transgressive dunes exist on heavily developed coasts, they coincide with relatively strong hydrodynamic forcing or sediment-limiting geology. There is evidence of indirect coastal management influence on undeveloped barrier islands with alongshore connectivity to developed barriers. While this analysis was conducted at the mesoscale, the results provide researchers with the framework to make insights at smaller scales than those demonstrated in this study.

North Carolina↗

USGS2025

Surface ice effects on water levels, wave dynamics and wave runup

Surface ice-induced changes in hydrodynamics may have significant implications on coastal hazards such as erosion and flooding. The objective of this study was to investigate how Lake Superior's water levels (WLs) and wave dynamics, that is, hydrodynamics, as well as the wave power and wave runup are influenced by the formation of surface ice. This study utilized a coupled circulation and spectral wave model, ADvanced CIRCulation Model (ADCIRC) + Simulating WAves Nearshore (SWAN). In this study, we considered six different ice-on, incorporating either ice thickness or concentration, and one hypothetical ice-free, ignoring any form of ice forcing, scenarios. The impact of surface ice on lake's WLs was found to be fairly insignificant. In contrast, surface ice-induced modifications in wave spectra resulted in smaller significant wave heights but longer peak wave periods. These observations were attributed to less energetic and narrower wave spectra of ice-on models compared to that of the ice-free model. The power loss caused by surface ice in a month was found to have enough capacity to meet the electrical demands of 55–100 households for an entire year in the United States. According to wave runup comparisons of ice-on and ice-free models at different regions, the effect of surface ice on wave runup could potentially exacerbate the adverse effect of coastal flooding by increasing the wave runup more than 20 cm. Such a geographic variation in the wave runup was observed to be influenced by the distance traveled by the waves within the ice field and duration of ice-wave interaction.

Lake Superior↗

USGS2025

An expert elicitation to inform coastal management decision-making for mitigating future hazards

A scientific expert elicitation was conducted to address the feasibility of restoring coastal environments in response to future hazards to best meet management objectives. Subject matter experts produced probabilistic estimates of coastal change metrics used to evaluate decision objectives and alternatives informed by a stakeholder advisory group. Changes in salt marsh extents, storm surge flooding and barrier island morphology by the year 2050 were estimated for three scenarios of management actions (no action, interior headland restoration, beach and dune nourishment), while also considering the effects of future sea level rise (SLR). Collectively the participants were confident in their expectations of increased storm surge flooding with SLR, regardless of management interventions. Estimates of marsh response had large uncertainty, but experts generally hypothesized that marsh area would decrease with increasing SLR if no action was taken, especially in areas already experiencing marsh deterioration. There was agreement that dune heights and barrier island widths would decrease with SLR if no action was taken. Experts felt that beach and dune nourishment may reduce the amount of erosion under future SLR. All experts recognized the dynamic effects of SLR and feedback between bio-geo-physical processes that govern coastal systems. Participants agreed that size and location of management actions were important factors for influencing the coastal response. Expert elicitation is novel in the context of coastal management decision making and can be a useful tool for informing future scientific needs and providing rapid results to end users to inform reallocation of resources surrounding research and application.

Alabama, Mississippi↗

USGS2025

Multiscale framework for assessing land cover change on barrier islands from extreme storms and restoration

Often found along the estuarine-marine interface, barrier islands and mainland coastal zones are shaped by tides, currents, extreme storms, and relative sea-level rise. These systems provide ecosystem services such as storm surge and wave attenuation, erosion protection to inland areas, habitat for fish and wildlife, recreation, and tourism. Given the importance of these ecosystems coupled with their dynamic nature, information on how these coastal systems are changing can help to inform natural resource management. Remote sensing advancements have led to an abundance of data for monitoring change in coastal settings. This study developed a multiscale framework that can provide trajectory information from screening-level analyses by using existing or custom moderate spatial resolution land cover maps. Using the north-central Gulf Coast as a case study, the trajectory of land cover area for barrier islands and mainland coastal zones was assessed using several geospatial data sets, including: (1) long-term moderate-resolution remote sensing products with an annual (or more frequent) temporal frequency; (2) a restoration database ( e.g. , beach/dune restoration, sediment placement, and dune enhancement); and (3) a tropical storm database. Due to the coarser spatial resolution of data sets used for screening-level analyses, detailed or application-specific analyses are often needed to reduce uncertainty in smaller changes that may not be captured. These may include land cover change analyses ( i.e. this study), periodic land cover maps with higher spatial resolution and more detailed land cover classes, or elevation-related analyses ( e.g. , dune change or inundation change). Using this framework, abrupt changes in land cover on Dauphin Island, Alabama, resulting from extreme storms were detected using moderate spatial resolution screening-level data, while restoration impact analyses may require higher resolution data. Further, land cover change analyses that incorporate change allocation provide robust information for understanding land cover change in dynamic coastal settings.

Alabama, Florida↗

USGS2024

Cumulative effects assessment of restoration programs: A framework to assess achievement of regional and programmatic goals

Increasing global investments focused on conservation and restoration of natural resources aim to address challenges presented by climate change and biodiversity loss. Many restoration and conservation program assessments examine individual actions, assuming additive effects only, failing to acknowledge or capture potential synergistic or antagonistic effects across a region or program. Cumulative effects assessments (CEA) provide a more ecologically relevant framework to assess the outcome of large restoration efforts. These assessments are critical given the increasing frequency of projects and the potential for cross-project interaction, yet there are few efforts to document the presence and patterns of cumulative effects for large-scale restoration programs. Understanding both the individual and cumulative effects of projects within a large restoration program can also inform the conceptualization of future large-scale restoration efforts by enabling the full suite of outcomes to be evaluated and considered against no-action scenarios in future planning. Here, we describe the development of a conceptual framework for CEA from large-scale restoration efforts.

Alabama, Florida↗

USGS2024

Vortex trapping of suspended sand grains over ripples

Coastal hydrodynamics and morphodynamics integrate the effects of small-scale fluid-sediment interactions; yet, these small-scale processes are not well understood. To investigate sediment trapping by turbulent coherent structures or vortices, the transport of coarse sand over ripples was analyzed in a small-oscillatory flow tunnel with phase-separated Particle Image and Tracking Velocimetry. Results from one of the first direct measurements of vortex-trapped sand grains under oscillatory flows are presented. The vortices mobilized sand grains along the ripple slopes just prior to flow reversal and transported the suspended sediment grains. During several flow cycles, some sand grains were temporarily trapped in the vortex, prescribing semi-circular trajectories off-center from the vortex core in quadrants of the vortex that were closest to the ripple slope, as illustrated by Nielsen (1992, https://doi.org/10.1142/1269 ). Comparisons of the horizontal sediment grain velocity with the horizontal fluid velocity yielded a linear relationship with a slope of 0.87. The vertical grain velocities also varied linearly with the vertical fluid velocity with a slope of approximately 1 and an offset of −0.08 m s −1 . The offset is close to the still water settling velocity for coarse sand grains, as hypothesized during vortex trapping. Additionally, estimates of the off-center distance, between the centers of the semi-circular sediment paths and vortex cores, compared well with the ratio of the settling velocity to the radian frequency of the vortex yielding a linear regression slope of 0.99. Improved understanding of vortex trapping effects on sediment dynamics may decrease uncertainty in model predictions of large-scale coastal hydrodynamics and sediment transport.

Journal of Geophysical Research: Earth Surface↗

USGS2024

Shaping the coast: Accounting for the human wildcard in projections of future change

Coastal change and evolution are the product of physical drivers (e.g., waves) tightly coupled with human behavior. As climate change impacts intensify, demand is increasing for information on where, when, and how coastal areas may change in the future. Although considerable research investments have been made in understanding the physical drivers and processes that modify and shape coastal environments, many do not account for human behavior, compromising the accuracy of comprehensive future change predictions. We outline four social science approaches—historic case studies, simulations, longitudinal studies, and longitudinal studies supported by experimental data—that can be coupled with physical change information to support transdisciplinary understanding of future change. A fundamental need for each approach is more and better empirical data to better gauge human behavior. In addition, foundational investments in transdisciplinary collaboration help research teams support the integration of these approaches.

Earth's Future↗

USGS2024

Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane

The Total Water Level and Coastal Change Forecast (TWL&CC Forecast) provides coastal communities with 6-day notice of potential elevated water levels and coastal change (i.e., dune erosion, overwash, or inundation) on sandy beaches that threatens safety, infrastructure, or resources. This continuously operating model provides hourly information for select regions along U.S. Gulf of Mexico and Atlantic Ocean coastlines. The objective of this work is to assess the skill of forecasts during a period of elevated water levels along the coasts of North Carolina (NC) and South Carolina, USA caused by Hurricane Isaias in August 2020, using a combination of observations and model hindcasts. Water levels and waves were observed throughout the storm at three locations near Wrightsville Beach, NC, which provided information to assess forecast skill; a wave buoy offshore, a tide gage at a local pier, and a pressure sensor deployed at the pier. In addition to observations, the non-hydrostatic phase-resolving model SWASH (Simulating WAves till SHore) was forced with hourly wave energy spectra derived from a coupled Delft3D-SWAN simulation during the peak of Isaias, to complement observations by computing nearshore wave height and wave-induced setup and runup at the shoreline. During the storm peak, SWASH-simulated water levels at the sensor position were comparable to those at the maximum landward extent (bias = −0.05 m; gain = 0.26; r 2 = 0.99), suggesting that observations at the USGS sensor location were a useful proxy for total water level (TWL; sum of tide, surge and wave runup) at the shoreline that are predicted by the TWL&CC Forecast. The TWL forecast at Wrightsville Beach was consistent with observations from the USGS sensor (bias = −0.38 m and −0.74 m, scatter index = 0.22 and 0.28 for the two forecast model grids considered, respectively; weighted regression considering model uncertainty explained 95 percent of variability in observed TWL). Observed TWL was within the confidence interval of the TWL&CC Forecast for the 5 h at the storm peak. Forecast mean water levels (MWL; sum of tide, surge and wave setup) and tide gage observations were also consistent (bias = 0.07 m and 0.02 m for the forecast model grids; scatter index = 0.46; r 2 = 0.80). Forecast MWL at the storm peak was within 0.06 m of the observed MWL from the tide gage for both sites. In the region where Isaias made landfall, eight additional pressure sensors were compared to the peak TWL forecast (bias = 0.14 m; scatter index = 0.18). Forecast TWL explained 90 percent of observed variability in TWL when considering uncertainty of the forecast with a weighted regression. The results demonstrate that wave-driven water levels contributed a significant portion of the forecast TWL during Isaias (52 percent during the three peak hours of the storm), and that TWL were represented using the forecast model. Mean absolute error of the coastal change forecast and observed overwash is 0.4 and 0.14 for the two forecast model grids considered. The skill demonstrated by this computationally efficient method indicates that the forecasting system can provide fast and reliable predictions of TWL across hundreds of km of coastline at sub-km resolution, days to hours in advance of when storms threaten coastal regions.

Coastal Engineering↗

USGS2024

Wave runup and total water level observations from time series imagery at several sites with varying nearshore morphologies

Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. We utilize over 7000 hand-digitized timestacks from six diverse locations to train and validate machine learning models to automate the process of TWL extraction. Using these data, we evaluate two deep learning model architectures for the task of runup detection. One is based on a fully convolutional architecture trained from scratch, and the other is a transformer-based architecture trained using transfer learning. The deep learning models provide a probability of each pixel being either wet or dry. When contoured at the 50% level (equal chance of being wet or dry), the deep learning models more accurately identified TWL maxima than minima at all sites. This resulted in accurate predictions of 2% exceedance runup, but under predictions of significant swash and over predictions of wave setup. Improved agreement with the complete TWL time series was obtained through post-processing by utilizing the wet/dry probability of each pixel to weight the contouring toward lower dryness probabilities for runup minima (maxima agreed well with observations without tuning). Overall, a transformer-based model using transfer learning provided the best agreement with wave runup statistics, including a) the 2% exceedance runup, b) significant swash, and c) wave setup at the shoreline. For a random subset of images, the model was found to be within the uncertainty range of hand-digitization. The relative success of the transfer learning model suggests that fine-tuning a large model has advantages compared to training a smaller model from scratch. Models provide per-pixel probabilistic estimates in less than 10 s per timestack on a single computational unit, versus the more than 5 min required for hand-digitization. The model is therefore well-suited for near real-time applications, allowing for the development of early warning systems for difficult to forecast events. Real-time wave runup and total water level observations can also be incorporated into coastal hazards forecasts for data assimilation and continual model validation and improvement.

Coastal Engineering↗

USGS2024

Developing a decision tree model to forecast runup and assess uncertainty in empirical formulations

The coastal zone is a dynamic region that can change rapidly and significantly with respect to the morphology of the beach and incoming wave conditions. Runup forecasts may be improved by adapting a dynamic approach that allows for different runup models to be implemented in response to changes in beach state. Accurately forecasting wave runup is critical to characterize exposure to coastal hazards and provide an early warning against potential erosion and inundation. Here, we developed a decision tree model to produce a weighted ensemble of existing runup models to predict 1.25 years of runup at Duck, North Carolina, USA. We then applied the calibrated decision tree model to reproduce observed runup during the DUNEX experiment in Pea Island, North Carolina, USA. We found that the decision tree approach yielded a prediction that was comparable or greater in accuracy (i.e. higher r2, lower RMSE) than the individual runup models. We also interrogated the decision tree predictions to determine how the individual models perform relative to each other and why certain models perform better than others under the same observed wave and beach conditions. We found that the decision tree approach drew on the processes represented in the individual models in the ensemble to produce a forecast that is accurate and explainable without relying on prior knowledge of the study site(s) or requiring manual adjustments beyond the initial model training.

North Carolina↗

USGS2023

Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread

Surfzone eddies enhance the dispersion and transport of contaminants, bacteria, and larvae across the nearshore, altering coastal water quality and ecosystem health. During directionally spread wave conditions, vertical vortices (horizontal eddies) are injected near the ends of breaking crests. Energy associated with these eddies may be transferred to larger-scale, low-frequency rotational motions through an inverse energy cascade, consistent with two-dimensional turbulence. However, our understanding of the relationships between the wave conditions and the dynamics and energetics of low-frequency surfzone eddies are largely based on numerical modeling. Here, we test these relationships with remotely sensed and in situ observations from large-scale directional wave basin experiments with varying wave conditions over alongshore-uniform barred bathymetry. Surface velocities derived with particle image velocimetry were employed to assess the spatial scales of low-frequency surfzone eddies and compute structure functions with alongshore velocities. Second-order structure functions for directionally spread waves ( ⁠

Physics of Fluids↗

USGS2023

Operational forecasts of wave-driven water levels and coastal hazards for US Gulf and Atlantic coasts

Predictions of total water levels, the elevation of combined tides, surge, and wave runup at the shoreline, are necessary to provide guidance on potential coastal erosion and flooding. Despite the importance of early warning systems for these hazards, existing real-time meteorological and oceanographic forecast systems at regional and national scales, until now, have lacked estimates of runup necessary to predict wave-driven overwash and erosion. To address this need, we present an approach that includes wave runup in an operational, national-scale modeling system. Using this system, we quantify the contribution of waves to potential dune erosion events along 4,700 km of U.S. Atlantic and Gulf of Mexico sandy coastlines for a one-year period. Dune erosion events were predicted to occur at over 80% of coastal locations, where waves dominated shoreline total water levels, representing 73% of the signal. This shows that models that neglect the wave component underestimate the hazard. This new, national-scale operational modeling system provides communities with timely, local-scale (0.5 km resolution) coastal hazard warnings for all wave conditions, allowing for rapid decision-making related to safety and emergency management. The modeling system also enables continued research into wave-driven processes at a broad range of coastal areas.

Atlantic Ocean, Gulf of Mexico↗

USGS2023

Toward a total water level forecast of the Great Lakes

The combined effect of storm surge and large waves is the main driving mechanism that erodes beaches, inundates low-lying areas, leading to millions of dollars in property damage, loss of natural resources, and lives. The U.S. Geological Survey (USGS) aims to expand the real-time total water level (TWL) forecast provided in the Operational Total Water Level and Coastal Change Forecasts (TWL&CC) to the Great Lakes short- (0 – 36 hours) to medium-term (3 – 5 days) coastal-hazard forecasts to inform planners and emergency responders. This study assesses the skill of forecast water levels and wave characteristics required as input to the TWL forecasts. It finds that, while skill generally decreases as forecast period increases, these data are suitable as input to the TWL forecast system. As the TWL predictions depend on the water level and wave forecasts, validation against field observations allow evaluation of their suitability for the Great Lakes. These results have implications on the prediction of water levels and their potential impacts on coastal resiliency in North America.

Great Lakes↗

USGS2023

Modeling total water level and coastal change at Pea Island, North Carolina, USA

The DUring Nearshore Event eXperiment (DUNEX) was carried out on Pea Island, North Carolina, USA between September-October 2021. We use a coupled numerical model (Windsurf) to hindcast the evolution of the DUNEX transect and produce a time series of hourly water levels at the shoreline from the model output. In addition to assessing the ability of Windsurf to reproduce TWL, we use model output paired with an ensemble of empirical models to assess how TWL forecasts can be improved by incorporating dynamic morphology. The morphological hindcast achieved an RMSE of 0.10 m and a BSS of 0.47, while the total water level (TWL) time series from the model correlates with the U.S. Geological Survey forecast (r 2 = 0.61) for the study period but with a 0.47 m bias that is primarily due to the much steeper beach slope used to produce the forecast compared to that surveyed at the start of the study period. We find that using dynamic morphology provides a small but statistically significant (α = 0.05) improvement in predicting TWL versus applying the pre-storm beach slope to the whole time series.

North Carolina↗

USGS2023

Remotely sensed short-crested breaking waves in a laboratory directional wave basin

Short-crested breaking waves that result from directionally spread wave conditions dissipate energy and generate turbulence within the surf zone, altering sediment transport processes, wave runup, and forces on structures. Additionally, vertical vorticity generated near crest ends during breaking, which depends on the gradient in wave height along a crest, may enhance nearshore dispersion of pollutants, nutrients, and larvae. Although directionally spread irregular wave fields are ubiquitous on ocean and large lake coastlines, the dependence of short-crested breaking wave characteristics (including the along-crest length and number of crest ends) on offshore wave conditions is not well established. To assess this relationship, laboratory experiments with alongshore-uniform barred bathymetry were performed in a large-scale directional wave basin. A three-dimensional scanning lidar, trinocular camera stereo processing methods, and in situ measurements were used to study short-crested wave field breaking characteristics in the laboratory, yielding a dataset with dense spatio-temporal coverage relative to prior laboratory or field measurements. Wave height estimates are similar for remotely sensed and in situ observations, except in the outer surf zone where plunging breaking occurred. Directional wave properties estimated with an array of in situ or remotely sensed sea-surface elevation estimates are similar and yield smaller directional spreads than single-point colocated pressure and velocity based in situ estimates when waves are less directionally spread. Using a breaking crest identification procedure combining visible imagery and stereo sea-surface elevation, we find that the average along-crest length of breaking waves decreases and the average number of crest ends increases with increasing directional spread. Relative to observations, a parameterized relationship between directional spread and crest characteristics based on theory for non-breaking, refracting waves generally over-estimates breaking crest lengths and is similar to or underestimates the total number of crest ends observed in the surf zone. The wave-field-dependent breaking-wave characteristics examined in the laboratory with remote sensing techniques can inform future investigations of depth-limited short-crested wave breaking and resulting surfzone eddy processes.

Coastal Engineering↗

USGS2023

Evaluation of nearshore bathymetric inversion algorithms using camera observations and synthetic numerical input of surface waves during storms

Nearshore bathymetry is difficult to measure using survey methods when wave heights approach the breaking limit. Remote sensing using digital cameras offers a way to observe the surf zone and calculate water depths based on phase speed but comes with its challenges of potentially noisy data that can introduce error into estimates of frequency and wavenumber used in phase speed calculation. This study investigates the robustness of a new version of a bathymetric inversion algorithm (cBathy, version 2.0) in moderate to energetic wave conditions by comparing depth estimates from timeseries’ of pixel intensity with depth estimates from synthetic water level data. The synthetic data are generated by the phase-resolving numerical model, SWASH, and optical data were collected during a field experiment in 2015. Model results from SWASH computed with known bathymetry are used as input to cBathy, and depth estimates are compared to nearshore surveys. Argus camera observations are also used as input to cBathy for the same times as the SWASH simulations. The SWASH simulations resolve breaking waves and do not include (optical) changes to the relation between water surface slope and pixel intensity, termed modulation transfer function, that occur during wave breaking, enabling better estimates from bathymetric inversion algorithms near morphologic features like sand bars. The results indicate that improvements result from eliminating of disruptions to the modulation transfer function caused by wave breaking and residual foam. We show that the use of synthetic wave data is a valuable means of isolating errors in bathymetric inversion algorithms.

North Carolina↗

USGS2023

Vortex trapping of sand grains over ripples under oscillatory flow

Sand ripples significantly impact morphodynamics in the nearshore by generating coherent vortices, which can transport suspended sediment to greater heights in the water column than above flat beds. Coherent vortices can trap sediment grains if the settling velocity of the grain is smaller than the maximum vertical fluid velocity in the vortex (Nielsen 1992). Particle image and tracking velocimetry were used to measure small-scale fluid-sediment interactions over sand ripples in a small oscillatory flow tunnel. Here we present some of the first measurements of vortex-trapped sediment grains under oscillatory flows. Results showed that the vortex-trapped sand grain traversed an orbit offcenter of the vortex near the ripple slope. Some grains then spiralled outward and settled to the bed; others were transported by the flow as the vortex was shed from the crest. Vortex trapping can delay settling and increase settling times, potentially causing inaccurate sediment transport predictions by large-scale numerical models, which do not typically account for this non-linear small-scale process.

Conference Paper↗