Geology topics

Christopher R. Sherwood

Publications and source records attributed to Christopher R. Sherwood.

At least 19 recordsLinked to original sources

USGS2026

Exploring future ecogeomorphic state transitions of an undeveloped barrier island: Multidecadal model projections for North Core Banks, NC, USA

Ecogeomorphic state transitions in coastal barrier systems will be impacted and likely amplified by projected accelerated sea-level rise and enhanced storm intensity over the next several decades. When, where, and how these transitions will take place remain uncertain and complex, yet are of primary interest to coastal managers looking to prepare for future changes. Here, we apply the new Mesoscale Explicit Ecogeomorphic Barrier model to generate probabilistic projections of future ecogeomorphic state transitions up to year 2050 for the undeveloped North Core Banks (NCB), North Carolina, United States. In our full probabilistic projection, which accounts for stochasticity from uncertainty in sea-level rise and high-water event (HWE) projections, loss of barrier interior to passive sea-level rise submergence dominates ecogeomorphic state transitions, suggesting that the biggest threat to many undeveloped barriers in the next several decades will come from the back-barrier rather than ocean-side. Additionally, this projection suggests that dune and unvegetated interior states are most volatile, with the intensity of state transitions varying significantly alongshore. In projections simulating a range of deterministic sea-level rise rates, higher rates enhance: overwash frequency; loss of beach and dune states; and interior submergence. We also find that state transitions are less sensitive to HWE intensity than sea-level rise, and that more frequent, moderate HWEs—rather than the largest events—may be the principal drivers of mesoscale ecogeomorphic state change. Our projections highlight important future mesoscale trends of ecogeomorphic state transitions for NCB that are likely relevant to other stable, sediment-rich barrier systems of U.S. coastlines.

North Carolina↗

USGS2025

Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0

Models of coastal barrier geomorphic and ecologic change are valuable tools for understanding and predicting when, where, and how barriers evolve and transition between ecogeomorphic states. Few existing models of barrier systems are designed to operate over spatiotemporal scales congruous with effective management practices (i.e., decades/kilometers, referred to herein as “mesoscales”), incorporate important ecogeomorphic feedbacks, and provide probabilistic projections of future change. Here, we present a new numerical model designed to address these gaps by explicitly yet efficiently simulating coupled aeolian, marine, vegetation, and shoreline components of barrier evolution over spatiotemporal scales relevant to management. The Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) simulates subaerial ecomorphologic change of undeveloped barrier systems over kilometers and decades using meter-scale spatial resolution and weekly time steps. MEEB applies simplified parameterizations to represent and couple key ecogeomorphic processes: dune growth, vegetation expansion and mortality, beach and foredune erosion, barrier overwash, and shoreline and shoreface change. The model is parameterized and calibrated with observed elevation, vegetation, and water level data for a case study site of North Core Banks, NC, USA. Simulated ecogeomorphic change in model hindcasts agrees well with observations, demonstrating both favorable skill scores and qualitatively correct behavior. We also describe an additional model framework for producing probabilistic projections that account for uncertainties related to future forcing conditions and intrinsic stochastic dynamics and demonstrate the probabilistic framework's utility with example forecast simulations. As a mesoscale model, MEEB is designed to investigate questions about future barrier ecogeomorphic change of moderate complexity, offering semi-qualitative predictions and semi-quantitative explanations. For example, MEEB can be used to investigate how climate-induced shifts in ecological composition may alter the likelihood of morphologic impacts or to generate probabilistic projections of ecogeomorphic state change.

Geoscientific Model Development↗

USGS2025

Inundation processes, barrier island breaching, and structure impacts during Hurricane Michael (2018)

We demonstrate the increased ability to forecast hurricane impacts with a coupled numerical modeling system by simulating ocean waves, water levels, currents, sediment transport, and structural damage to predict inundation, coastal morphological change, and residential building impacts. The Coupled-Ocean-Atmosphere-Waves-Sediment-Transport (COAWST) modeling system is applied to simulate Hurricane Michael (category 5, 2018) that made landfall near Tyndall Air Force Base, FL, in the northern Gulf of America, causing severe devastation and flooding. Atmospheric forcings from the Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) are used to drive the ocean and wave models on a series of nested grids. Results identify that coastal inundation at Mexico Beach is due to surge from winds and waves, supplemented by pulses of infragravity wave motions that propagate landward into the inundation region. Seed lines observed on interior building walls also demonstrate variable changes in water level. In addition, a machine learning model was applied to hindcast structure damages, caused mostly by waves and winds, with a 72% accuracy estimate of substantial damage in proximity of landfall. The storm also created a breach across Cape San Blas, the adjacent barrier spit, due to large surge and low dune elevations. Dune locations with vegetated land cover are shown to reduce wave-energy dissipation and reduce erosion, whereas locations without land cover had increased breaching potential. The breach occurred during the maximum ocean-side water level, and the delayed high water on the bay side allowed a pressure gradient to drive flow seaward and promote breach development.

Florida↗

USGS2025

RUSH: Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models

Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments.

Florida, Louisiana, North Carolina↗

USGS2025

Numerical simulation of sound-side barrier-island inundation and breaching during Hurricane Dorian (2019)

Hurricane-induced morphological changes and associated community hazards along sandy, barrier-island coastlines have been studied primarily from the perspective of ocean-side attack by storm-driven ocean surge and large waves. Thus, our understanding of long-term barrier island morphological change focuses on beach erosion, overwash, and inlet formation. In contrast, outwash events with inundation from the sound side, such as one that occurred in Cape Lookout National Seashore, North Carolina, USA during Hurricane Dorian (September 2019), are understudied. Studying such events can improve understanding of barrier island response and stability for a broader range of conditions. Here, we model the hydrodynamics and morphological evolution of a barrier island using a coupled wave-current-sediment transport modeling system. Wind-driven surge in Pamlico Sound led to overtopping from the sound side, which eroded outwash channels and transported sediment seaward into the nearshore. Simulations reproduce the channel features observed with aerial imagery and provide information not available from the remote-sensing observations, including channel depths (>2 m) and the fate of the eroded sand. We found that >99% of the eroded sand was deposited in the nearshore, within 1,000 m of the shoreline in depths <10 m, suggesting that the deposited sediment remains available for littoral transport and beach recovery. Simulations with combinations of coarse or fine sediment and vegetated or unvegetated landcover indicate that channel position did not vary with grain size or vegetation, while volume of erosion and channel morphology were more responsive to variations in grain size and less responsive to presence of vegetation.

North Carolina↗

USGS2025

Outwash events inhibit vegetation recovery and prolong coastal vulnerability

Overwash, when high ocean water levels and waves flood a coastline, is a common phenomenon that can lead to washover deposits and barrier rollover. Outwash, by contrast, involves seaward flow, often driven by high back-barrier water levels, and can produce washout channels and nearshore deposition. Our observations show that washout channels were quickly (days to weeks) filled and reshaped into beaches, berms, and washover deposits and ponds often formed at the landward ends. However, there was a significant delay in revegetation of former washout areas compared with washover areas. North Core Banks, North Carolina, was affected by repeat hurricanes in different ways: Hurricane Florence (2018) deposited large washover fans 0.5–1 m thick, and Hurricane Dorian (2019) removed 1–4 m of sediment from washout channels. Aerial surveys captured vegetation recolonization on the Florence washover fans within a year but, after Dorian, surveys showed that although the washout channels and ponds quickly filled with marine sand, the channel throats and new washover platforms remained mostly unvegetated for five years. New vegetation growth was associated with the washout ponds and was characteristic of low-elevation hydrophilic environments. We observed comparable outcomes at washout and washover locations on the coasts of Texas and New York and suggest that outwash interrupts the normal cycle of vegetation and dune growth that is key to rebuilding barrier islands after storms. The lack of vegetation in the former washout channels prolongs vulnerability to overwash, further delaying recovery. Our findings have implications for best-management practices and modeling of coastal geomorphic evolution.

JGR Earth Surface↗

USGS2023

Temporal variability of runup and total water level on Cape Cod sandy beaches

In the present study, we evaluate the temporal variability in runup and total water level for sandy beaches along Cape Cod (Massachusetts, USA), and their impact on dune and beach erosion. We use a 43-year hindcast of waves and water levels and calculate runup and total water level based on the Stockdon formulation using previously extracted beach slopes. The dominant components of the runup are identified and their temporal variability evaluated. The seasonal and interannual variability of total water level is evaluated. For most locations along the outer Cape Cod coast, the comparison between total water level and dune elevations suggested that the coastal response remained predominantly under swash regime. The results over these study locations could be extended to other similar areas at regional scales to provide better characterization of total water level and coastal change at long temporal scales.

Massachusetts↗

USGS2023

Contributions to uncertainty in runup forecasts

The U.S. Geological Survey (USGS) provides operational forecasts of total water levels (TWL) and coastal change. Uncertainties around forecast TWL are based on the temporal and spatial range of observed beach slopes near the forecast site. This paper investigates other sources of uncertainty that are not accounted for, focusing on four beaches where the USGS has deployed remote cameras, and on outer Cape Cod, which has diverse bar morphologies. We find that the range of runup indicated by ten formulae is nearly as large as the variations caused by the range of beach slopes. A formula that accounts for bar morphology substantially decreases calculated runup, and might improve forecasts. Errors in the timing of forecast storm landfall generate uncertainties in TWL where tides are large. Analyses suggest that the effect of off-normal incident waves is relatively small. These results suggest opportunities for improving the TWL forecasts.

Massachusetts↗

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

Processes controlling coastal erosion along Cape Cod Bay, MA

Cape Cod Bay, MA, is a semi-enclosed embayment in the northeastern United States, open on the north to the Gulf of Maine. The coastline experiences impacts typically from strong Nor’easter storms that occur in the late fall or winter months, with some sections of this coastline being affected more severely than others. We investigate the processes that cause spatial variability in storm impacts by using geophysical surveys, shoreline-change analysis, and numerical modeling. We simulated the Gulf of Maine and Cape Cod Bay from Jan–April, 2021, using the COAWST modeling system, including ocean, wave, infragravity wave, and sediment transport models. Results identify bay-scale circulation of alongshore sediment fluxes and convergences at regional shoals. Nearshore modeling also revealed zones of increased wave heights that correlate with regions of increased erosion and coastal angle orientation. Modeled and computed shoreline-change have some correlation but the model does not capture all the variability. This overall approach can potentially be used for other coastal locations to identify regions of storm impacts and to manage coastal resources.

Massachusetts↗

USGS2023

Incorporating wave climate complexity into modeling lower shoreface morphology and transport

The lower shoreface, a transitional subaqueous region extending from the seaward limit of the surf zone to beyond the closure depth, serves as a sediment reservoir and pathway in sandy beach environments over annual to millennial time scales. Despite the important role this region plays in shoreline dynamics, the morphodynamics of the lower shoreface remain poorly quantified and understood. To better understand controls on shoreface morphology, here we combine energetics-based suspended sediment transport formulae (Ortiz & Aston 2016) with empirical wave climate data to incorporate temporal complexity in modeled equilibrium profiles and sediment flux rates. The equilibrium shoreface shape computed using a full wave climate is steeper in shallower water and less steep in the deeper reaches compared to profiles computed using single wave characteristics. Using a full wave climate to simulate steady-state morphology will yield steeper profiles in shallow water. Suspended sediment transport rates also vary in direction and magnitude at different equilibrium profile depths and can potentially inform the location of morphodynamic boundaries in the shoreface. Our results reveal how infrequent storm waves affect shoreface slopes, with large events tending to drive sediment onshore in the deeper portions of the profile. This work explores a few ways to add complexity to simple energetics-based frameworks to reproduce empirical bathymetric data more accurately and provides insight toward refining coastal source-to-sink models.

Conference Paper↗

USGS2023

Sound-side inundation and seaward erosion of a barrier island during hurricane landfall

Barrier islands are especially vulnerable to hurricanes and other large storms, owing to their mobile composition, low elevations, and detachment from the mainland. Conceptual models of barrier-island evolution emphasize ocean-side processes that drive landward migration through overwash, inlet migration, and aeolian transport. In contrast, we found that the impact of Hurricane Dorian (2019) on North Core Banks, a 36-km barrier island on the Outer Banks of North Carolina, was primarily driven by inundation of the island from Pamlico Sound, as evidenced by storm-surge model results and observations of high-water marks and wrack lines. Analysis of photogrammetry products from aerial imagery collected before and after the storm indicate the loss of about 18% of the subaerial volume of the island through the formation of over 80 erosional washout channels extending from the marsh and washover platform, through gaps in the foredunes, to the shoreline. The washout channels were largely co-located with washover fans deposited by earlier events. Net seaward export of sediment resulted in the formation of deltaic bars offshore of the channels, which became part of the post-storm berm recovery by onshore bar migration and partial filling of the washouts with washover deposits within 2 months. This event represents a volumetric setback in the overwash/rollover behavior required for barrier transgression, but the new ponds and lowland habitats may provide beneficial habit for endangered species and will likely persist for years.

North Carolina↗

USGS2022

Modeling of barrier breaching during Hurricanes Sandy and Matthew

Physical processes driving barrier island change during storms are important to understand to mitigate coastal hazards and to evaluate conceptual models for barrier evolution. Spatial variations in barrier island topography, landcover characteristics, and nearshore and back-barrier hydrodynamics can yield complex morphological change that requires models of increasing resolution and physical complexity to predict. Using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, we investigated two barrier island breaches that occurred on Fire Island, NY during Hurricane Sandy (2012) and at Matanzas, FL during Hurricane Matthew (2016). The model employed a recently implemented infragravity (IG) wave driver to represent the important effects of IG waves on nearshore water levels and sediment transport. The model simulated breaching and other changes with good skill at both locations, resolving differences in the processes and evolution. The breach simulated at Fire Island was 250 m west of the observed breach, whereas the breach simulated at Matanzas was within 100 m of the observed breach. Implementation of the vegetation module of COAWST to allow three-dimensional drag over dune vegetation at Fire Island improved model skill by decreasing flows across the back-barrier, as opposed to varying bottom roughness that did not positively alter model response. Analysis of breach processes at Matanzas indicated that both far-field and local hydrodynamics influenced breach creation and evolution, including remotely generated waves and surge, but also surge propagation through back-barrier waterways. This work underscores the importance of resolving the complexity of nearshore and back-barrier systems when predicting barrier island change during extreme events.

Florida, New York↗

USGS2022

Human-in-the-Loop segmentation of earth surface imagery

Segmentation, or the classification of pixels (grid cells) in imagery, is ubiquitously applied in the natural sciences. Manual methods are often prohibitively time-consuming, especially those images consisting of small objects and/or significant spatial heterogeneity of colors or textures. Labeling complicated regions of transition that in Earth surface imagery are represented by collections of mixed-pixels, -textures, and -spectral signatures, can be especially error-prone because it is difficult to reliably unmix, identify and delineate consistently. However, the success of supervised machine learning (ML) approaches is entirely dependent on good label data. We describe a fast, semi-automated, method for interactive segmentation of N-dimensional (x, y, N) images into two-dimensional (x, y) label images. It uses human-in-the-loop ML to achieve consensus between the labeler and a model in an iterative workflow. The technique is reproducible; the sequence of decisions made by human labeler and ML algorithms can be encoded to file, so the entire process can be played back and new outputs generated with alternative decisions and/or algorithms. We illustrate the scientific potential of segmentation of imagery of diverse settings and image types using six case studies from river, estuarine, and open coast environments. These photographic and non-photographic imagery consist of 1- and 3-bands on regular and irregular grids ranging from centimeters to tens of meters. We demonstrate high levels of agreement in label images generated by several labelers on the same imagery, and make suggestions to achieve consensus and measure uncertainty, ideal for widespread application in training supervised ML for image segmentation.

Earth and Space Science↗

USGS2022

Shoaling wave shape estimates from field observations and derived bedload sediment rates

The shoaling transformation from generally linear deep-water waves to asymmetric shallow-water waves modifies wave shapes and causes near-bed orbital velocities to become asymmetrical, contributing to net sediment transport. In this work, we used two methods to estimate the asymmetric wave shape from data at three sites. The first method converted wave measurements made at the surface to idealized near-bottom wave-orbital velocities using a set of empirical equations: the “parameterized” waveforms. The second method involved direct measurements of velocities and pressure made near the seabed: the “direct” waveforms. Estimates from the two methods were well correlated at all three sites (Pearson’s correlation coefficient greater than 0.85). Both methods were used to drive bedload-transport calculations that accounted for asymmetric waves, and the results were compared with a traditional excess-stress formulation and field estimates of bedload transport derived from ripple migration rates based on sonar imagery. The cumulative bedload transport from the parameterized waveform was 25% greater than the direct waveform, mainly because the parameterized waveform did not account for negative skewness. Calculated transport rates were comparable to rates estimated from ripple migration except during the largest event, when calculated rates were as much as 100 times greater, which occurred during high period waves.

Florida, Massachusetts, New York↗

USGS2022

CoastalImageLib: An open-source Python package for creating common coastal image products

CoastalImageLib is a Python library that produces common coastal image products intended for quantitative analysis of coastal environments. This library contains functions to georectify and merge multiple oblique camera views, produce statistical image products for a given set of images, and create subsampled pixel instruments for use in bathymetric inversion, surface current estimation, run-up calculations, and other quantitative analyses. This package intends to be an open-source broadly generalizable front end to future coastal imaging applications, ultimately expanding user accessibility to optical remote sensing of coastal environments. This package was developed and tested on data collected from the Argus Tower, a 43 m tall observation structure in Duck, North Carolina at the US Army Engineer Research and Development Center’s Field Research Facility that holds six stationary cameras which collect twice-hourly coastal image products. Thus, CoastalImageLib also contains functions designed to interface with the file storage and collection system implemented at the Argus Tower.

SoftwareX↗

USGS2022

Modeling morphodynamics of coastal response to extreme events: What shape are we in?

This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash, collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.

Annual Review of Marine Science↗

USGS2021

Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation

Introduction Structure from motion (SFM) has become an integral technique in coastal change assessment; the U.S. Geological Survey (USGS) used Agisoft Metashape Professional Edition photogrammetry software to develop a workflow that processes coastline aerial imagery collected in response to storms since Hurricane Florence in 2018. This report details step-by-step instructions to create three-dimensional (3D) spatial products from both singular and repeated collections of shoreline aerial imagery. The products can be used for real-time hazard guidance and future forecasting and recovery endeavors.

Open-File Report↗