Cape Lookout National Seashore storm characterization: Evaluation in support of cultural resource management
No abstract available.
North Carolina↗
Geology topics
P. Soupy Dalyander
Publications and source records attributed to P. Soupy Dalyander.
Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state
Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.
Louisiana↗
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↗
Fusing geophysical and remotely sensed data for observing overwash occurrence, frequency, and impact
Overwash is an important process that enables a barrier island to migrate landward to adapt to rising sea levels but can also impact vegetated areas and create coastal hazards for populated barrier islands. Our overall objectives were to hindcast overwash events from September 2008 to November 2009 and assess whether overwash impacts could be detected using moderate-resolution imagery (30 m). Estimates of wave and still water levels can be benchmarked against morphological characteristics from elevation datasets to predict overwash events. These observations can be combined with optical remote sensing data used to monitor for changes in vegetation greenness over time to evaluate potential impacts from overwash. This study highlighted how physical-based overwash data can be paired with observations of greenness. The results from our study highlighted that a discernable drop in greenness can be detected for major hurricanes, such as Hurricane Gustav in 2008, with a weaker signal observed for smaller magnitude events in 2009 like Hurricane Ida. Tracking overwash impacts to vegetation can be helpful for observing impacts to vegetation associated with restoration efforts and advancing our understanding of general overwash impacts and recovery.
Conference Paper↗
Assessing habitat change and migration of barrier islands
Barrier islands are dynamic environments that experience gradual change from waves, tides, and currents, and rapid change from extreme storms. These islands are expected to change drastically over the coming century due to accelerated sea-level rise and changes in frequency and intensity of storm events. The dynamic nature of barrier islands coupled with the importance of these environments make it critical for natural resource managers to understand how habitats on barrier islands are changing or may change over time to determine when and where management actions may be needed. In this study, we applied a habitat change assessment framework, which included exploring areal coverage and distribution changes and change component analysis. Change component analysis, which breaks differences into net gain/loss and allocation difference (i.e., habitat oscillation), has not previously been used to study barrier island habitat evolution. Here, we demonstrate the approach using habitat predictions from a geomorphic modeling effort on Dauphin Island, Alabama (USA). We explored differences of habitat predictions for potential island configurations with and without a beach and dune restoration action under future conditions related to sea level and storminess. We found a potential linkage between landward migration of barrier islands and exchange, an output of change component analysis. The hypothesis may be tested to explore whether this linkage applies over space and time and whether the approach is applicable to monitoring landward migration of coastal wetlands. Collectively, our results highlight the utility of change component analysis for monitoring and quantifying barrier island habitat change and migration.
Alabama↗
Developing bare-earth digital elevation models from structure-from-motion data on barrier islands
Unoccupied aerial systems can collect aerial imagery that can be used to develop structure-from-motion products with a temporal resolution well-suited to monitoring dynamic barrier island environments. However, topographic data created using photogrammetric techniques such as structure-from-motion represent the surface elevation including the vegetation canopy . Additional processing is required for estimating bare-earth elevation, which is critical for understanding the underlying geomorphology of these islands. In this study, we used a vegetation and elevation survey to produce bare-earth digital elevation models from structure-from-motion-derived elevation products for two sites on Dauphin Island, Alabama (USA). One site was exposed to high wave energy and included a mix of beach, dune, and barrier flat habitats that were dominated by supratidal/upland herbaceous vegetation. The second site was exposed to low wave energy and was dominated by intertidal marsh. Aerial imagery was collected in late fall of 2018 and spring of 2019. We tested several machine learning algorithms for predicting and removing elevation bias for vegetated areas using predictors that included spectral indices from unoccupied aerial systems-based multispectral imagery and landscape position information (e.g., relative topography and distance from shore). Models were developed for each site and season. We also explored how well the model from one season generalized to data from a different season for the same site. For developing initial digital surface models, we found that utilizing a minimum bin algorithm, as opposed to interpolation, led to lower elevation bias. For bias removal, Gaussian process regression performed the best and led to a root mean square error for the bare-earth digital elevation models of around 0.10 m for the high energy site and 0.15 m for the low energy site. Compared to the digital surface models, the root mean square error for the bare-earth digital elevation models was reduced by at least 29 percent for the high energy site and 69 percent for the low energy site. For all models, common predictors included surface elevation, vegetation greenness, and distance from the shoreline. The models produced comparable results when trained using data from a different season. The error estimates for all analyses were within published elevation standards for lidar data for vegetated areas. With calibration, this approach could be portable to other areas or data, such as aerial lidar (conventional or unoccupied), to provide an efficient and repeatable framework for monitoring geomorphology or provide baseline elevations for predicting changes to these environments under future conditions.
Alabama↗
Sensitivity of storm response to antecedent topography in the XBeach model
Antecedent topography is an important aspect of coastal morphology when studying and forecasting coastal change hazards. The uncertainty in morphologic response of storm-impact models and their use in short-term hazard forecasting and decadal forecasting is important to account for when considering a coupled model framework. This study provided a methodology to investigate uncertainty of profile response within the storm impact model XBeach related to varying antecedent topographies. A parameterized island Gaussian fit (PIGF) model generated an idealized baseline profile and a suite of idealized profiles that vary specific characteristics based on collated observed LiDAR data from Dauphin Island, AL, USA. Six synthetic storm scenarios were simulated on each of the idealized profiles with XBeach in both 1- and 2-dimensional setups and analyzed to determine the morphological response and uncertainty related to the varied antecedent topographies. Profile morphologic response tends to scale with storm magnitude but among the varied profiles there is greater uncertainty in profile response to the medium range storm scenarios than to the low and high magnitude storm scenarios. XBeach can be highly sensitive to morphologic thresholds, both antecedent and time-varying, especially with regards to beach slope.
Alabama↗
The roles of storminess and sea level rise in decadal barrier island evolution
Models of alongshore sediment transport during quiescent conditions, storm‐driven barrier island morphology, and poststorm dune recovery are integrated to assess decadal barrier island evolution under scenarios of increased sea levels and variability in storminess (intensity and frequency). Model results indicate barrier island response regimes of keeping pace, narrowing, flattening, deflation (narrowing and flattening), and aggradation. Under lower storminess scenarios, more areas of the island experienced narrowing due to collision. Under higher storminess scenarios, more areas experienced flattening due to overwash and inundation. Both increased sea levels and increased storminess resulted in breaching when the majority of the island was not keeping pace and deflation was the dominant regime due to increased overtopping. Under the highest storminess scenario, the island was unable to recover elevation after storms and drowned in just 10 years.
Alabama↗
Development of a modeling framework for predicting decadal barrier island evolution
Predicting the decadal evolution of barrier island systems is important for coastal managers who propose restoration or preservation alternatives aimed at increasing the resiliency of the island and its associated habitats or communities. Existing numerical models for simulating morphologic changes typically include either long-term (for example, longshore transport under quiescent conditions) or short-term (for example, storm-driven waves) processes, with limited capacity to predict the decadal time-scale that is often most relevant in coastal planning. As part of the Alabama Barrier Island Restoration Assessment, a methodology was developed to predict barrier island evolution on decadal time scales. The developed modeling scheme uses multiple models including (1) Delft3D; (2) the empirical dune growth model (EDGR); and (3) XBeach that run sequentially to simulate evolution of barrier island geomorphology. The model framework was developed and applied to hindcast the evolution of Dauphin Island, Alabama, between 2004 and 2015, and was assessed using lidar data over the same period.
Alabama↗
Application of decadal modeling approach to forecast barrier island evolution, Dauphin Island, Alabama
Forecasting barrier island evolution provides coastal managers and stakeholders the ability to assess the resiliency of these important coastal environments that are home to both established communities and existing natural habitats. This study uses an established coupled model framework to assess how Dauphin Island, Alabama, responds to various storm and sea-level change scenarios, along with a suite of restoration measures, over the course of a decade. The coupled model framework uses validated models for long-term alongshore sediment transport (Delft 3D), short-term storm induced impacts (XBeach), as well as dune building and recovery (empirical dune growth model). This model framework was simulated with the various storm and sea-level change scenarios on a non-restored Dauphin Island, then a subset of the storm and sea-level change scenarios were applied to a suite of seven different restoration measures to determine how they would influence the morphologic evolution over a decadal period. Topographic and bathymetric changes captured in post-simulation digital elevation models were then passed on to partners for various simulations to determine the effects on habitat evolution and water quality as it relates to oyster reef and submerged aquatic vegetation.
Alabama↗
Development of a process-based littoral sediment transport model for Dauphin Island, Alabama
Dauphin Island, Alabama, located in the Northern Gulf of Mexico just outside of Mobile Bay, is Alabama’s only barrier island and provides an array of historical, natural, and economic resources. The dynamic island shoreline of Dauphin Island evolved across time scales while constantly acted upon by waves and currents during both storms and calm periods. Reductions in the vulnerability and enhancements to the resiliency of Dauphin Island—through offshore sand placement, breach closure, berm construction, and other means—have been used to protect the island and its vital resources. Planning for a resilient Dauphin Island requires predicting the long-term evolution of the barrier island system and the dominant, temporally varying processes that influence it, including littoral alongshore sediment transport under typical wave conditions, beach and dune erosion, the island overwash and breaching that occur rapidly during storm events, and the recovery of primary sand dunes through Aeolian transport over decadal time scales. Littoral sediment transport within the Dauphin Island decadal-scale framework was simulated using the Delft-3D modeling software suite. The influences of wind, waves, water levels, and sediment transport are incorporated into the model. Model skill in the prediction of waves, water levels, currents, volumetric flow rates through inlets, and shoreline position was assessed by using a set of deterministic and statistical hindcast simulations. The Delft-3D modeling application described here can be coupled with validated models of storm-response and dune recovery to predict the evolution of Dauphin Island on decadal time scales.
Alabama↗
Event and decadal-scale modeling of barrier island restoration designs for decision support
An interdisciplinary project team was convened to develop a modeling framework that simulates the potential impacts of storms and sea level-rise to habitat availability at Breton Island, Louisiana (Breton) for existing conditions and potential future restoration designs. The model framework was iteratively developed through evaluation of model results at multiple checkpoints. A methodology was developed for characterizing regional wave and water levels, and the numerical model XBeach was used to simulate the potential impacts from a wide range of storm events. Simulations quantified the potential for erosion, overwash, and inundation of the pre- and post-restoration beach and dune system and were used as a preliminary screening of restoration designs. The model framework also incorporated a computationally efficient method to evaluate the impacts of storms, long-term shoreline changes, and relative sea level rise over a 15-year time period in order to evaluate the effect of the preferred restoration alternative on habitat distribution. Results directly informed engineering design decisions and expedited later project stages including the construction permitting process.
Shore & Beach↗
Hydrodynamics and sediment mobility processes over a degraded senile coral reef
Coral reefs can influence hydrodynamics and morphodynamics by dissipating and refracting incident wave energy, modifying circulation patterns, and altering sediment transport pathways. In this study, the sediment and hydrodynamic response of a senile (dead) barrier reef (Crocker Reef, located in the upper portion of the Florida Reef Tract) to storms and quiescent conditions was evaluated using field observations and the Coupled Ocean-Atmosphere-Wave-Sediment Transport model. Waves, circulation, and resultant sediment mobility were modeled across different reef zones. Sediment mobility during quiescent periods and the passage of far-field storms are driven by nonbreaking waves and, to a lesser degree, regional circulation. Spatial variability in these processes produces the present-day distribution of sediment grain size at Crocker Reef, wherein finer-grain material along a shallow central ridge is frequently mobilized (43% to 62% of the time), winnowed away, and deposited along the lower-energy flanks and in the fore reef where sand mobility occurs less frequently (32% to 43% and 1% to 22% of the time, respectively). Analysis of wave conditions for the period of 2006–2014 supports that wave heights rarely exceed the threshold for breaking (0.1% and 0.3% at the reef crest and at the reef flat, respectively), predominantly during the passage of tropical storms. There is a shift to a wave-breaking regime during near-field storms, creating the potential for mobilization of larger material and enhanced reef degradation. Sediment mobility can be enhanced due to wave skewness or the generation of free infragravity waves during periods of depth-induced wave breaking.
Florida↗
Laboratory observations of artificial sand and oil agglomerates
Sand and oil agglomerates (SOAs) form when weathered oil reaches the surf zone and combines with suspended sediments. The presence of large SOAs in the form of thick mats (up to 10 centimeters [cm] in height and up to 10 square meters [m 2 ] in area) and smaller SOAs, sometimes referred to as surface residual balls (SRBs), may lead to the re-oiling of beaches previously affected by an oil spill. A limited number of numerical modeling and field studies exist on the transport and dynamics of centimeter-scale SOAs and their interaction with the sea floor. Numerical models used to study SOAs have relied on shear-stress formulations to predict incipient motion. However, uncertainty exists as to the accuracy of applying these formulations, originally developed for sand grains in a uniformly sorted sediment bed, to larger, nonspherical SOAs. In the current effort, artificial sand and oil agglomerates (aSOAs) created with the size, density, and shape characteristics of SOAs were studied in a small-oscillatory flow tunnel. These experiments expanded the available data on SOA motion and interaction with the sea floor and were used to examine the applicability of shear-stress formulations to predict SOA mobility. Data collected during these two sets of experiments, including photographs, video, and flow velocity, are presented in this report, along with an analysis of shear-stress-based formulations for incipient motion. The results showed that shear-stress thresholds for typical quartz sand predicted the incipient motion of aSOAs with 0.5–1.0-cm diameters, but were inaccurate for aSOAs with larger diameters (>2.5 cm). This finding implies that modified parameterizations of incipient motion may be necessary under certain combinations of aSOA characteristics and environmental conditions.
Open-File Report↗
A framework for modeling scenario-based barrier island storm impacts
Methods for investigating the vulnerability of existing or proposed coastal features to storm impacts often rely on simplified parametric models or one-dimensional process-based modeling studies that focus on changes to a profile across a dune or barrier island. These simple studies tend to neglect the impacts to curvilinear or alongshore varying island planforms, influence of non-uniform nearshore hydrodynamics and sediment transport, irregular morphology of the offshore bathymetry, and impacts from low magnitude wave events (e.g. cold fronts). Presented here is a framework for simulating regionally specific, low and high magnitude scenario-based storm impacts to assess the alongshore variable vulnerabilities of a coastal feature. Storm scenarios based on historic hydrodynamic conditions were derived and simulated using the process-based morphologic evolution model XBeach. Model results show that the scenarios predicted similar patterns of erosion and overwash when compared to observed qualitative morphologic changes from recent storm events that were not included in the dataset used to build the scenarios. The framework model simulations were capable of predicting specific areas of vulnerability in the existing feature and the results illustrate how this storm vulnerability simulation framework could be used as a tool to help inform the decision-making process for scientists, engineers, and stakeholders involved in coastal zone management or restoration projects.
Chandeleur Islands↗
Correction of elevation offsets in multiple co-located lidar datasets
Introduction Topographic elevation data collected with airborne light detection and ranging (lidar) can be used to analyze short- and long-term changes to beach and dune systems. Analysis of multiple lidar datasets at Dauphin Island, Alabama, revealed systematic, island-wide elevation differences on the order of 10s of centimeters (cm) that were not attributable to real-world change and, therefore, were likely to represent systematic sampling offsets. These offsets vary between the datasets, but appear spatially consistent within a given survey. This report describes a method that was developed to identify and correct offsets between lidar datasets collected over the same site at different times so that true elevation changes over time, associated with sediment accumulation or erosion, can be analyzed.
Alabama↗
A methodology for modeling barrier island storm-impact scenarios
A methodology for developing a representative set of storm scenarios based on historical wave buoy and tide gauge data for a region at the Chandeleur Islands, Louisiana, was developed by the U.S. Geological Survey. The total water level was calculated for a 10-year period and analyzed against existing topographic data to identify when storm-induced wave action would affect island morphology. These events were categorized on the basis of the threshold of total water level and duration to create a set of storm scenarios that were simulated, using a high-fidelity, process-based, morphologic evolution model, on an idealized digital elevation model of the Chandeleur Islands. The simulated morphological changes resulting from these scenarios provide a range of impacts that can help coastal managers determine resiliency of proposed or existing coastal structures and identify vulnerable areas within those structures.
Louisiana↗